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Marmelab.com would do well to understand the implementation and adoption challenges prior blockchain-for-web-developers-the-theory.html investing. For the Node. Miners receive a gratification for keeping the network working and safe. No Downloads. Blog to many 2016 innovations based on computers and networks, the blockchain is very slow. This would improve patient safety and reduce the need https manage response to regulatory warnings.
As these messages may be incomplete, outdated, accidentally wrong or malicious, every node has to consolidate this information. False or outlying information will so be eliminated, and it is not possible to take part in the communication process with just inserting any arbitrary information into the network.
The outcome of this process should be a consolidated value, which will be further used by other network nodes during their consolidation process. Otherwise, this part of a message, which may be accidentally or intentionally wrong, may not be forwarded, neglected or even forgotten over time. Now, a malicious node may actively try to change the order of information to pretend that all the measurements are right, but need to be reordered by changing time stamps of parts of the information history being broadcasted.
Also, this history has to be equal to the node-knowledge of other network participants as they have also created a timeline of information. As derived and argued above, this network is a full implementation of the concepts of p BFT: With a high number of participants, multiple network paths due to message broadcast and many communication cycles with asynchronous repetitions of consolidated and historical cued messages, the conditions for at least the practical BFT are met.
Singular false messages from malicious nodes can be detected and eliminated with various mechanisms as listed in the following text: missing or unknown node ID : if a node ID is not known, the node has no history among other nodes in the network, and therefore, it either may be directly excluded from message processing or has at least a very low reputation, until it has built up a history inside other nodes knowledge;.
If all information is somehow captured and a false ID is successfully generated, the original correct node can create an alarm that something with its ID distributes messages that are not aligned with its own history.
Therefore, a manipulation is at least detectable. Therefore, they cannot be sequenced or at least be sequentially checked against the other information and no timestamp can be created. But here, the complete historical sequence also can be considered unknown be other nodes and can therefore be detected and suppressed.
Consequently, with a low number of malicious nodes or information, wrong messages are detected. Only if one or many nodes start permanently intruding the IoT - network with continuous wrong information, they might be able to build up something like a history, which might eventually be accepted by other network participants as authorized and true information.
However, this process will be accompanied by a preceding phase where the intrusion is detectable. As this security process is time- and energy-consuming, it is scalable in terms of transferred length of history, consensus algorithms, rejection intensity and mechanisms and spatial and temporal map size within each node.
Therefore, for a high security level, measures can be taken requiring a high level of energy. On the other hand, this mechanism may also be applied to energy-restricted systems with the risk of a lower security level. In this article, a principle for increased information security for IIoT-systems organized in wireless sensor networks was presented.
Mechanisms from blockchains and distributed ledger technologies were derived and adopted to microcontrollers, with a small energy budget and low calculation capabilities. It was shown that principles such as chained blocks, distributed ledger, time-stamping and consensus could be transferred.
This leads to a higher effort for intruders to gain access to the communication process and to inject false information. In the next steps of research, this concept will be implemented into different domains of application such as long- and short-distance communication, self-sufficient nodes with extensive sleep cycles and transferred to various cloud-based blockchains for permanent information-keeping.
Ragone diagram about the operation time of a mobile device with an energy - storage system under maximum load. Example for a dynamic, de-centrally initiated and controlled production process.
Protocol steps of receiving, chaining and distributing. Boucher , P. Castro , M. Dargie , W. Farooqui , A. Kellermann , C. Lamport , L. Nakamoto , S. Obaidat , M.
Popov , S. Raghavendra , C. Ronen , E. Schneider , B. Skwarek , V. Thomas , S. Zaninotto , F. Report bugs here. Please share your general feedback. You can join in the discussion by joining the community or logging in here. You can also find out more about Emerald Engage. Visit emeraldpublishing.
Answers to the most commonly asked questions here. Abstract Purpose This paper aims to describe a method for Internet-of-Things-devices to achieve industrial grade reliability for information transfer from wireless sensor systems to production systems using blockchain technologies.
Findings Blockchain mechanisms can secure the wireless communication of Internet-of-Things-devices in a lightweight and scalable manner. Opens in a new window. Figure 1. Figure 2. Figure 3. Identification and verification process. Figure 4. Who pays for all the wasted energy? The companies that publish and use smart contracts. Yes, that's you, if you intend to run a business on the blockchain.
When you pay for a transaction on the blockchain, you also pay That makes blockchain transactions expensive. This price is rising. It's not really cheaper than a bank transaction fee unless you consider a transfer across two countries with different currencies, of course. For ZeroDollarHomepage, executing a lines script on Ethereum method costs about one cent 0. That's insanely expensive. Amazon Lambda, for instance, [costs 0. It's normal to pay for hosting costs when you use a platform, but the Blockchain costs are orders of magnitude higher than the most expensive PaaS.
You could say that the blockchain cost isn't such a big deal, as long as people are willing to use the network and pay for transactions. It's a question of supply and demand, and the demand for blockchain and cryptocurrencies is currently high enough to make it profitable.
But this high demand leads to speculation, and therefore the price of computing and storage in a blockchain any blockchain is highly volatile. Some analyst compare Bitcoin to a Ponzi Scheme , and predict that the market value will collapse once general interest disappears. If we build a business based on the Ethereum's blockchain, most of our expenses will be in Ether. If we don't mine it ourselves, we'll have to pay for that Ether in real money. But since the USD value of Ether may vary tenfold within a year, our business can move from profitable to worthless in the same timeframe.
And we can't do anything against it. On the other hand, if we mine ourselves, what is currently affordable running a small server to cover expenses in Ether might become very expensive once very large mining farms move from Bitcoin to Ethereum. The high volatility of cryptocurrencies forbids any long-term profitable business built on the blockchain - except speculation. Compared to many other innovations based on computers and networks, the blockchain is very slow.
Experts say that you should wait 6 blocks to make sure that a transaction is legit. This means more than 1 minute in Ethereum, or more than 1 hour in Bitcoin. In a traditional ad server, scheduling an ad takes about ms.
If you've used our ZeroDollarHomepage Ad Server, you probably had a very different experience: Scheduling an ad takes about a minute. The network transport and replication accounts for a small share of that duration ; most of the time is spent waiting for the network to mine the transaction , and add a few more blocks after that. But all in all, the Ethereum blockchain is several orders of magnitude slower than traditional computing.
For end users, every second counts. The Web Performance Optimization trend focuses on improving revenue by earning one or two seconds in download time. Betting on a technology that requires a transaction to be acknowledged by the entire world isn't the best way to make business.
One of the promises of the blockchain is to liberate markets that still require an intermediary. No more lawyers, bankers, or bookmakers. A great opportunity for new businesses? Except these intermediaries currently report criminal activities to the authorities governments and law enforcement agencies. If you remove the intermediaries, you also remove the police, and you let criminals proliferate.
The first bitcoin application at scale was called The Silk Road. It was an online marketplace for everything illegal: drugs, weapons, child pornography, etc. Not to mention the ability to use bitcoins for tax evasion. Even the proponents of free market economy recognize that a certain level of regulation is necessary to avoid total chaos. Running a business in a land full of criminals with no police isn't profitable - unless you're a criminal, too.
For instance, the Mt. Just like it took a long time for governments to control the Internet which was, and remains, a haven for criminals , it will take a long time for our lawmakers to control the anarchy unleashed by blockchains.
The blockchain may carry the promise of a better future in the long term, but for the near future, you'd better be armed. A large share of the hype around the blockchain comes from people who don't really understand its shortcomings. They would probably use another solution is they were better informed. Here are a few bad reasons why you should probably not choose the blockchain technology. This completely defeats the main purpose, which is to get an agreement between non-trusted parties.
If a project needs runs on a private blockchain, then only trusted parties can join it, and you don't have a trust problem. In a trusted network, there are many, many other tools to share a ledger of facts - all much better optimized than the blockchain for instance: a web service.
It offers a way to reach distributed consensus It does, but only if this consensus can be written as code. For instance, a company working with music rights distribution recently contacted us to build an international platform for artist retribution on the blockchain. Except that when two countries disagree on how to pay right holders, they both have valid contracts. Only a court can decide which contract wins. No smart contract can replace that.
You must have clear governance rules that already work before trying to automate them in a blockchain. It's secure Asymmetric cryptography is one of the blockchain's strengths. However, the blockchain technology, just like any other, is safe only until someone finds a vulnerability. It has already happened in the past. The computer science behind the blockchain is so complex that very few developers can contribute or review the code. Of, and even if the software works perfectly, it doesn't prevent fraud.
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All industries have been impacted, and in life sciences, the progression has been swift and profound. Take the Internet of Things IoT , which emerged earlier this decade as a way for consumers to monitor and manage their health and well-being.
Today, IoT technologies also enable life sciences organizations to proactively manage their manufacturing processes using smart, connected equipment, reducing maintenance costs and enhancing safety, at scale. As digital technologies dramatically transform consumer experiences and business capabilities, organizations across industries need to consider whether their structures and operating models impede or enable the pace of change.
The unintended consequence: precious time and money lost creating, maintaining and dealing with intermediaries. What if technology could provide a mechanism for establishing the mechanisms of trust, immutability, transparency, auditability and security that have traditionally been performed by an intermediary? This white paper explores how blockchain — the decentralized, distributed ledger infrastruc- ture built around strong cryptography — could power full digital transformation across the life sciences space.
We also provide guidance on how to identify the best use cases and prepare for blockchain adoption. It offers non-repu- diation of transactions that can work with the absence of a trusted intermediary across a peer- to-peer, distributed network.
Participants validate transactions and authenticate the ledger without the need for a trusted authority, using public key encryption and consensus protocols. The shared ledger stores transactions com- pleted across the network see Figure 1. Once the entries are recorded in the shared ledger, they cannot be changed. Blockchain operates by consensus; unlike rela- tional databases, which are usually owned by the organization providing services, there is no single owner of a transaction.
Blockchain net- works can be either public non-permissioned or private permissioned. The code of the transaction is sent to a large network, where it is confirmed without compromising private information and eliminating the need for a central authority. Once a transaction is confirmed and validated by several parties, it exists on the ledger of each as a permanent and immutable record of the transaction. The transaction information is recorded, in a public ledger, and the transaction is completed.
Private blockchains are helpful when data sharing is intended only with selected parties. The paradigm shift that blockchain introduces has attracted the interest of governments, aca- demics, start-ups, established businesses and venture capitalists. Gartner has identified block- chain as one of the top 10 strategic technology trends for All serve to illustrate the enormous potential of digitiza- tion and disintermediation, the effects of which are now being felt beyond the boundaries of financial services 9 and into retail, healthcare, manufacturing, utilities and insurance.
By using blockchain to maintain clinical trial protocols, revisions and patient consent, for example, phar- maceuticals companies can better demonstrate patient safety and transparency. The highly regulated nature of the pharmaceuticals and medical devices businesses and greater reliance on ecosystem partnerships has created a significant burden of documentation and records management.
For example, the contracts between payers and pharmaceuticals organizations could be maintained using blockchain to provide legal authenticity. Provenance Provenance refers to the ability to trace origin and ensure the authenticity of the object being traded. Despite improvements, such as product serialization and e-pedigree — an electronic document that provides data about the history of a particular batch of a drug — the problem of spurious drugs continues to haunt pharmaceuticals.
Every block added to the blockchain network can be computationally linked to the preceding block, thereby providing immutability. Malicious access to sensitive personal data can cause devastating harm to consumer relationships and grave reputational and finan- cial repercussions to medical device makers. Blockchains can embed rules to control access to sensitive medical data. Patients can specify, for example, that only their family and treating phy- sicians can access their health records.
Disintermediation An inherent strength of blockchain is that it allows information to be made available to all parties securely, thus obviating the need for an inter- mediary.
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The term smart reflects the highly dynamic reconfiguration of the complete system according to actual environment, product, production or customer requirements.
In the context of smart production — also called industry 4. Therefore, industrial systems shall be able to handle single-piece-productions dynamically. Such requirement is hardly achievable by a central management system as the risk of a single-point-failure in case of a malfunction is too high, and the required processing power and communication bandwidth for such a system may be a limiting issue. Consequently, these systems are usually distributed and transaction based.
In contrast to a process-based system, a transaction-based system acts fully asynchronously on demand. This means, that there is no instance of central coordination, synchronizing all actors, but that the single instances have to request activities by sending transaction requests into the system, expecting a recipient processing this request.
For example, such a transaction can be initiated by an enterprise—resource-planning ERP -system, ordering a new product from the production floor. Now the semis step-wise requests all production tools by sending messages to them. The messages are processed as soon as there are spare resources see example in Figure 2.
Therefore, the asynchronous-system-control initiated by decentral devices is part of the smart-X-concept. The consequence of failures in IIoT-device is more severe than in regular IoT-devices: As a system causes a personal or economic fatality, the requirements in any terms of safety, security and availability are far higher than for regular IoT-systems. In situations where a consumer device in case of a failure can be restarted or data simply are wrong or missing, an industrial device usually operates in a networked cluster as explained above.
A single failure may influence the whole process chain and lead to stopping production, an energy blackout for a city Ronen et al. Usually, these high requirements can only be fulfilled with measures resulting in a higher energy consumption, which again contradicts the need for a long operating time of usually battery - driven mobile IoT-devices.
As neglecting or diminishing security and safety is no option, the detectability of system manipulations by chaining and distributing blocks as introduced by Schneider and Kelsey Schneider and Kelsey, seems to be a solution.
In this case, the IoT-devices only need to provide low security according to their energy budget, while communicating all information by chaining and broadcasting them. Any irregularities can later be detected and handled by other devices with more energy such as gateways or production machines.
Therefore, blockchain and distributed ledger technologies seem to be predestined for higher security demands in IIoT-systems with the chance to reduce the energy need on the sensor device. The general considerations above about the applicability of blockchain technologies will be further explained and analyzed in the following subsections. As WSNs — and IoT-devices as a subset of WSN — transmit their information over the air and, therefore, use an open channel, which is why it is generally rather easy to attack them.
A comprehensive, but by far not complete list of potential attacks on all, network layers is shown in the following items composed from multiple publications Dargie and Poellabauer, , chap.
Therefore, it is obvious that WSNs are extremely vulnerable to a high number of attacks. Although this is covered by intensive research — a search request in the IEEE online library ieeexplore.
With the increased attractiveness and distribution of WSNs by IoT-devices, it is expected that the number and form of attacks on WSNs will increase, so new methods and principles for security have to be found Dargie and Poellabauer, , p.
Consequently, it is broadly accepted, that a WSN cannot be made equally secure as wired systems, so a different approach from Schneider and Kelsey, some of the developers of basic blockchain principles — the hash-chained blocks — will be followed:. The tamper resistance is expected to keep most attackers out, but it is not per cent reliable. The effort for attacks on nodes shall be maximized, whereas successful attacks shall be made transparent.
If a WSN can only be insufficiently secured, it, nevertheless, has to be protected and be prepared for the detection of intrusions. Here, as one piece of the puzzle, the basic concept tamper-awareness and fraud-detection as introduced by Schneider and Kelsey will be followed. Additionally, the basic blockchain concept, as introduced by Nakamoto , will be examined for parallel requirements and partly transferred into the domain of WSN to secure the communication of IIoT-devices.
If the number of correct messages exceeds certain mathematical rules, then the majority of the received message contains the right information. Briefly speaking, the number of false messages must be significantly lower than the correct ones. Messages between nodes do not need to arrive synchronously but with a time shift and a re-constructible order. Nakamoto just turns this mathematical problem into the practical BFT: As long as the number of honest nodes, information and communication cycles is far higher than the traitors and the order of sent and received information cannot easily be changed; for example, because they are hashed, the system is secure with reliable information Castro and Liskov, ; Kellermann, So basically, a secured communication system can be built on the concepts of the following: proofing and temporally ordering information;.
Branches containing erroneous information may be temporarily created, but with a majority of honest participants, the correct information will survive and the branch will be deleted. As already argued above, IIoT-systems require higher availability and reliability of information.
In terms of prioritization, the total cost of a system, the size, weight or form factor are less relevant as long as they fulfill their function reliably. Therefore, lightweight protocols with the above derived properties of a blockchain have a high potential to achieve the required reliability for IIoT networks. Already some blockchains support the connection of external devices — called oracles — such as Ethereum ethereum. But here, the sensors are only directly connected to the oracles without additional security, so IIoT-devices operate on the same security level, only storing their data on a blockchain instead of a database.
Iota iota. However, this again is a blockchain-technology on its own, which is not designed to be directly connected to other blockchains. Consequently, a sensor-chain-like system needs to be developed, securing IoT-devices with blockchain methods, independent from the decision on which cloud based blockchain to use for storing or processing the data.
In the following subsections, some design considerations derived from the criteria in the preceding section for a sensor-chain are described.
Therefore, a unique identity ID is required. This may contain the device number, a binary representation of measured data types or its location for portable or mobile sensors. This ID will be cross-checked multiple times Figure 3 by direct computation and comparison, the comparison by special nodes with extended capabilities and cross-communication and verification among those additional nodes.
It is also fraud proof as these unique properties can be verified: for example, the data types as potential element of such an ID can directly be seen in the transmitted data, or the position can be cross-checked with other principles such as triangulation of the signal strength. This device identification makes the device and its data unique which is the most important precondition for the proof-of-work and consensus.
For an optimum performance in a potentially spatial—dynamic sensor network, the system topology is an important factor in terms of the desired functionality as well as the energy effort. Unlike a wired network with network nodes without any energy restriction, for IoT-devices in a WSN, a peer-to-peer network is not the first choice.
Due to the limited communication range of the nodes, usually a multi-hop routing is required to bridge the distance to a border—gateway into another long range, e. As nodes may sleep or move, node management has to be performed and a permanently updated routing table has to be maintained and communicated. Therefore, an asynchronous unrouted point-to-multipoint broadcast-network with a longer listening- than sending-interval for every node is preferred. With a sufficient number of nodes — an assumption already arisen in section 3.
Here, different neighborhood relationships of nodes and messages have to be considered Skwarek and Monecke, , basically distinguishing between ego-nodes the actual node itself , direct and indirect neighbors. A permanent process of receiving information from the network, packing this and own information into a new message and redistributing it, lead to a distributed ledger of all information available on the whole network Figure 4. Each sensor may not see all information of all other participants instantly, but over a certain time span, a full network-wide information map is created inside every sensor.
Therefore, this is equivalent to a full-node ledger in blockchain terminology. The node-knowledge is spatially retarded and memory - wise limited. However, in a stationary network with sufficient node memory, the node- and system-knowledge become identical over the time. Realistically, the local node only carries an incomplete ledger. Realistically, all nodes have due to latencies during the information transfer and memory-caused limitations an incomplete and partially outdated picture of the complete network information Figure 5.
This requires every node to regularly update its node-knowledge with all messages received from all other nodes. As these messages may be incomplete, outdated, accidentally wrong or malicious, every node has to consolidate this information. False or outlying information will so be eliminated, and it is not possible to take part in the communication process with just inserting any arbitrary information into the network.
The outcome of this process should be a consolidated value, which will be further used by other network nodes during their consolidation process.
Otherwise, this part of a message, which may be accidentally or intentionally wrong, may not be forwarded, neglected or even forgotten over time.
Now, a malicious node may actively try to change the order of information to pretend that all the measurements are right, but need to be reordered by changing time stamps of parts of the information history being broadcasted.
Also, this history has to be equal to the node-knowledge of other network participants as they have also created a timeline of information. As derived and argued above, this network is a full implementation of the concepts of p BFT: With a high number of participants, multiple network paths due to message broadcast and many communication cycles with asynchronous repetitions of consolidated and historical cued messages, the conditions for at least the practical BFT are met.
Singular false messages from malicious nodes can be detected and eliminated with various mechanisms as listed in the following text: missing or unknown node ID : if a node ID is not known, the node has no history among other nodes in the network, and therefore, it either may be directly excluded from message processing or has at least a very low reputation, until it has built up a history inside other nodes knowledge;.
If all information is somehow captured and a false ID is successfully generated, the original correct node can create an alarm that something with its ID distributes messages that are not aligned with its own history. Therefore, a manipulation is at least detectable.
Therefore, they cannot be sequenced or at least be sequentially checked against the other information and no timestamp can be created. But here, the complete historical sequence also can be considered unknown be other nodes and can therefore be detected and suppressed.
Consequently, with a low number of malicious nodes or information, wrong messages are detected. Only if one or many nodes start permanently intruding the IoT - network with continuous wrong information, they might be able to build up something like a history, which might eventually be accepted by other network participants as authorized and true information.
However, this process will be accompanied by a preceding phase where the intrusion is detectable. As this security process is time- and energy-consuming, it is scalable in terms of transferred length of history, consensus algorithms, rejection intensity and mechanisms and spatial and temporal map size within each node.
Therefore, for a high security level, measures can be taken requiring a high level of energy. Jouer pour mieux travailler : Le Quarto python integration agile. Managing State in React: Redux or not Redux? Admin-on-rest Becomes React-admin, and Gets a Major 2. Finding And Fixing Node. Automating accessibility testing with Selenium Webdriver and AxeCore accessibility testing popular. Admin-on-rest 1. Le jeu du Taquin en React et React Native js react integration.
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The Blockchain Explained to Web Developers, Part 3: The Truth
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Automating accessibility testing with Selenium Webdriver and AxeCore accessibility testing popular. Admin-on-rest 1.
Le jeu du Taquin en React et React Native js react integration. La blockchain, quand l'individu sert au collectif BlendWebMix conference. Le jeu du Taquin en php framework Symfony php golang integration. Let's cook some Crystal! Le jeu du Taquin en go golang ai integration. Learning Jest Through Practice react testing. Le jeu du Taquin en python python integration. New Website Design marmelab.
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The unintended consequence: precious time and money lost creating, maintaining and dealing with intermediaries. What if technology could provide a mechanism for establishing the mechanisms of trust, immutability, transparency, auditability and security that have traditionally been performed by an intermediary? This white paper explores how blockchain — the decentralized, distributed ledger infrastruc- ture built around strong cryptography — could power full digital transformation across the life sciences space.
We also provide guidance on how to identify the best use cases and prepare for blockchain adoption. It offers non-repu- diation of transactions that can work with the absence of a trusted intermediary across a peer- to-peer, distributed network. Participants validate transactions and authenticate the ledger without the need for a trusted authority, using public key encryption and consensus protocols. The shared ledger stores transactions com- pleted across the network see Figure 1.
Once the entries are recorded in the shared ledger, they cannot be changed. Blockchain operates by consensus; unlike rela- tional databases, which are usually owned by the organization providing services, there is no single owner of a transaction. Blockchain net- works can be either public non-permissioned or private permissioned.
The code of the transaction is sent to a large network, where it is confirmed without compromising private information and eliminating the need for a central authority. Once a transaction is confirmed and validated by several parties, it exists on the ledger of each as a permanent and immutable record of the transaction. The transaction information is recorded, in a public ledger, and the transaction is completed.
Private blockchains are helpful when data sharing is intended only with selected parties. The paradigm shift that blockchain introduces has attracted the interest of governments, aca- demics, start-ups, established businesses and venture capitalists.
Gartner has identified block- chain as one of the top 10 strategic technology trends for All serve to illustrate the enormous potential of digitiza- tion and disintermediation, the effects of which are now being felt beyond the boundaries of financial services 9 and into retail, healthcare, manufacturing, utilities and insurance.
By using blockchain to maintain clinical trial protocols, revisions and patient consent, for example, phar- maceuticals companies can better demonstrate patient safety and transparency. The highly regulated nature of the pharmaceuticals and medical devices businesses and greater reliance on ecosystem partnerships has created a significant burden of documentation and records management.
For example, the contracts between payers and pharmaceuticals organizations could be maintained using blockchain to provide legal authenticity.
Provenance Provenance refers to the ability to trace origin and ensure the authenticity of the object being traded. Despite improvements, such as product serialization and e-pedigree — an electronic document that provides data about the history of a particular batch of a drug — the problem of spurious drugs continues to haunt pharmaceuticals.
Every block added to the blockchain network can be computationally linked to the preceding block, thereby providing immutability. Malicious access to sensitive personal data can cause devastating harm to consumer relationships and grave reputational and finan- cial repercussions to medical device makers.
Blockchains can embed rules to control access to sensitive medical data. Patients can specify, for example, that only their family and treating phy- sicians can access their health records. Disintermediation An inherent strength of blockchain is that it allows information to be made available to all parties securely, thus obviating the need for an inter- mediary. Savings in time, cost and agility could make blockchain an ideal candidate for enabling fluid collaboration.
In clinical trials, a blockchain network with participants from pharmaceuticals, investigators, trial sites and regulators could be created in which data could be shared securely without any chance of alteration. This would improve patient safety and reduce the need to manage response to regulatory warnings. Internal Process Management Enterprises create internal systems and device processes to reconcile transactions between internal systems.
For example, pharmaceuticals companies typically use many systems to manage factory operations, such as handling inbound raw materials and processing across product lifecycle stages — finished goods, scrap manage- ment, packaging and labeling.
Numerous internal systems are created to reconcile and convey a holistic view across such activities. With a block- chain, the need for such artificial reconciliation can be reduced, as transactions across systems can be maintained in a single shared ledger.
For instance, blockchain technology is relatively new, and its business advantages are unproven. Moreover, implemen- tation tools need to mature with the technology. A major non-technical challenge is the disrup- tion of cultural notions or mindsets associated with adoption of decentralized ways of working. Enterprises would do well to understand the implementation and adoption challenges prior to investing. To be feasible, a blockchain roadmap should be built on a use case selection frame- work, as described on page Temperature Excursion Many pharmaceuticals products — particularly those that are biological in nature — are highly temperature sensitive.
Since the delivery of a pharma- ceuticals product involves multiple partners i. In this PoC, IoT-enabled temperature loggers are inserted into the batch packages, and a block- chain network is created for all participants shipper, warehouse provider, etc. The tempera- ture loggers can transmit temperature excursion data, which is stored on the blockchain, accessi- ble by all network participants. A smart contract is created to implement a rule for stability checks based on temperature excursion data.
We used Solidity 12 for smart contract creation, and the PoC was implemented with the Ethereum 13 infra- structure and hosted in an Amazon cloud.
The patient is assured of a high level of safety against drug instability or decomposition. Smart contracts compare temperature logger data with stabil- ity data previously defined in a batch master. If the temperature logger data values trans- gress permissible limits, the batch is then marked as expired or invalid.
Stakeholders share a single version of the truth, thus increasing mutual trust. Any batch or product can be traced back to its origin. This ensures that no duplicate product replaces the original one in the supply chain. Adverse events due to batch stabil- ity cannot occur, as batches are automatically invalidated by the smart contract. Healthcare insurance for example Medicare will only pay for services that are medically necessary. For payers, verification of CMN validity is a laborious and error-prone task.
Physician intermediation is necessary to ensure the veracity and currency of the CMN. Suppliers need to know the amount of busi- ness serviced in the CMN channel. Today, CMNs are filled out manually, and form exchange can be time-consuming, paper-oriented and error- prone. To substantiate this PoC, we built a sample cloud-powered application, deployed on Amazon Web Services AWS , using an Ethereum imple- mentation of blockchain with a Solidity smart contract that validates CMNs for adherence to a simple rule: that the CMN should be certified ini- tially and recertified by the physician periodically see Figure 3.
The blockchain network connects patients, physicians and payers. The workflow is initiated by a patient requesting a CMN, which — when issued by the physician — is embedded with a QR code that identifies the patient on the blockchain. Since CMNs are digitally signed on the blockchain, they are immutable, eliminating the chance of fraud by either the phy- sician or the supplier. In addition, audit efforts by regulatory bodies are significantly reduced.
This significantly reduces processing time. Smart contracts provide the foundation for digitiza- tion and automation for business processes. Logic can be embedded to automatically trig- ger payment on successful verification. Blockchain rules are indelible, and fraudulent claims can be easily checked, reducing manual audit efforts.
Trusted Data Sharing Industry acceptance is gaining momentum for open internal data storage for product devel- opment, clinical trial assessment and other imaginative applications. We built a sample application, deployed on the Microsoft Azure cloud, using a MultiChain 17 imple- mentation of blockchain.
A blockchain network is created with publishers i. Research- ers query for available data, and once the dataset of interest is located, they download it.
An entry is made in a blockchain for tracking. Researchers can reference the blockchain data while pub- lishing their findings, lending authenticity and repeatability of their findings see Figure 4. Drug Provenance Is there a better way for patients and consum- ers to verify the authenticity and source of a drug?
Drug production and distribution involves many participants, including manufacturers, distributors, wholesalers and pharmacies. Each participant in the distribution chain is typically interested in knowing the true source of the drug and track distribution. A blockchain-based solution can help build such trust in products and their supply chain. To illustrate this concept, we created a sample application hosted on the Amazon AWS cloud based on a MultiChain implementation of a block- chain, which allows manufacturers to record drug batches as blockchain transactions tagged with a QR code revealing batch details.
The drug batch details are immutable once confirmed on the blockchain. All downstream participants can trust a drug batch based on the scanned QR code and also use the same data to track further dis- tribution see Figure 5. Manufactured batches are recorded on a blockchain as a single source of truth available to all participants.
Each participant buys or sells the drug post-verification using the QR code returned by the blockchain. Each participant in a blockchain can verify the drug before it is purchased and after it is received. The shift is not just technological; its implications extend across legal, cultural and social parameters.
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A blockchain is a ledger of facts , replicated across several computers assembled in a peer-to-peer network. Facts can be anything from monetary transactions to content signature. Members of the network are anonymous individuals called nodes. All communication inside the network takes advantage of cryptography to securely identify the sender and the receiver. When a node wants to add a fact to the ledger, a consensus forms in the network to determine where this fact should appear in the ledger; this consensus is called a block.
I don't know about you, but after reading these definitions, I still had troubles figuring out what this is all about. Let's get a bit deeper. Decentralized peer-to-peer networks aren't new. Napster and BitTorrent are P2P networks. Instead of exchanging movies, members of the blockchain network exchange facts. Then what's the real deal about blockchains? P2P networks, like other distributed systems, have to solve a very difficult computer science problem: the resolution of conflicts, or reconciliation.
Relational databases offer referential integrity , but there is no such thing in distributed system. If two incompatible facts arrive at the same time, the system must have rules to determine which fact is considered valid. To answer this question, the best way is to order the facts. If two incompatible facts arrive in the network, the first one to be recorded wins. In a P2P network, two facts sent roughly at the same time may arrive in different orders in distant nodes.
Then how can the entire network agree on the first fact? To guarantee integrity over a P2P network, you need a way to make everyone agree on the ordering of facts. You need a consensus system. Consensus algorithms for distributed systems are a very active research field. You may have heard of Paxos or Raft algorithms. The blockchain implements another algorithm, the proof-of-work consensus, using blocks. Blocks are a smart trick to order facts in a network of non-trusted peers.
The idea is simple: facts are grouped in blocks , and there is only a single chain of blocks, replicated in the entire network. Each block references the previous one. So if fact F is in block 21, and fact E is in block 22, then fact E is considered by the entire network to be posterior to fact F. Before being added to a block, facts are pending , i. Some nodes in the chain create a new local block with pending facts.
They compete to see if their local block is going to become the next block in the chain for the entire network, by rolling dice. If a node makes a double six, then it earns the ability to publish their local block, and all facts in this block become confirmed. This block is sent to all other nodes in the network. All nodes check that the block is correct, add it to their copy of the chain, and try to build a new block with new pending facts.
But nodes don't just roll a couple dice. Blockchain challenges imply rolling a huge number of dice. Finding the random key to validate a block is very unlikely , by design. This prevents fraud, and makes the network safe unless a malicious user owns more than half of the nodes in the network. As a consequence, new blocks gets published to the chain at a fixed time interval.
In Bitcoin, blocks are published every 10 minutes on average. In Bitcoin, the challenge involves a double SHA hash of a string made of the pending facts, the identifier of the previous block, and a random string. A node wins if their hash contains at least n leading zeroes. Number n is adjusted every once in a while to keep block duration fixed despite variations in the number of nodes. This number is called the difficulty. Other blockchain implementations use special hashing techniques that discourage the usage of GPUs e.
The process of looking for blocks is called mining. This is because, just like gold mining, block mining brings an economical reward - some form of money.
That's the reason why people who run nodes in a blockchain are also called miners. Note : By default, a node doesn't mine - it just receives blocks mined by other nodes. It's a voluntary process to turn a node into a miner node. Every second, each miner node in a blockchain tests thousands of random strings to try and form a new block.
So running a miner in the blockchain pumps a huge amount of computer resources storage and CPU. That's why you must pay to store facts in a blockchain. Reading facts, on the other hand, is free: you just need to run your own node, and you'll recuperate the entire history of facts issued by all the other nodes. So to summarize:. We're not talking about real money here. In fact, each blockchain has its own crypto- currency.
To make a payment in the Bitcoin network, you must pay a small fee in Bitcoins - just like you would pay a fee to a bank. But then, where do the first coins come from?
Miners receive a gratification for keeping the network working and safe. Each time they successfully mine a block, they receive a fixed amount of cryptocurrency. That way, the blockchain generates its own money. Lastly, cryptocurrencies rapidly became convertible to real money.
Their facial value is only determined by offer and demand, so it's subject to speculation. At the time of writing, mining Bitcoins still costs slightly less in energy and hardware than you can earn by selling the coins you discovered in the process. That's why people add new miners every day, hoping to turn electricity into money.
But fluctuations in the BTC value make it less and less profitable. So far we've mostly mentioned facts storage, but a blockchain can also execute programs. Some blockchains allow each fact to contain a mini program. Such programs are replicated together with the facts, and every node executes them when receiving the facts. In bitcoin, this can be used to make a transaction conditional : Bob will receive BTC from Alice if and only if today is February 29th.
Other blockchains allow for more sophisticated contracts. In Ethereum for instance, each contract carries a mini-database , and exposes methods to modify the data.
As contracts are replicated across all nodes, so are their database. Each time a user calls a method on the contract and therefore updates the underlying data, this command is replicated and replayed by the entire network.
This allows for a distributed consensus on the execution of a promise. This idea of pre-programed conditions, interfaced with the real world, and broadcasted to everyone, is called a smart contract. A contract is a promise that signing parties agree to make legally-enforceable. A smart contract is the same, except with the word "technically-" instead of "legally-".
This removes the need for a judge, or any authority acknowledged by both parties. You and the loaner sign a contract, probably written by a lawyer. You also need a bank to receive the payment. At the beginning of the week, you ask for a 1 , 0 0 0 , w i t h a 5 0 5, deposit; the loaner writes a check for it. Therefore, it is obvious that WSNs are extremely vulnerable to a high number of attacks.
Although this is covered by intensive research — a search request in the IEEE online library ieeexplore. With the increased attractiveness and distribution of WSNs by IoT-devices, it is expected that the number and form of attacks on WSNs will increase, so new methods and principles for security have to be found Dargie and Poellabauer, , p.
Consequently, it is broadly accepted, that a WSN cannot be made equally secure as wired systems, so a different approach from Schneider and Kelsey, some of the developers of basic blockchain principles — the hash-chained blocks — will be followed:. The tamper resistance is expected to keep most attackers out, but it is not per cent reliable. The effort for attacks on nodes shall be maximized, whereas successful attacks shall be made transparent.
If a WSN can only be insufficiently secured, it, nevertheless, has to be protected and be prepared for the detection of intrusions. Here, as one piece of the puzzle, the basic concept tamper-awareness and fraud-detection as introduced by Schneider and Kelsey will be followed. Additionally, the basic blockchain concept, as introduced by Nakamoto , will be examined for parallel requirements and partly transferred into the domain of WSN to secure the communication of IIoT-devices.
If the number of correct messages exceeds certain mathematical rules, then the majority of the received message contains the right information. Briefly speaking, the number of false messages must be significantly lower than the correct ones. Messages between nodes do not need to arrive synchronously but with a time shift and a re-constructible order.
Nakamoto just turns this mathematical problem into the practical BFT: As long as the number of honest nodes, information and communication cycles is far higher than the traitors and the order of sent and received information cannot easily be changed; for example, because they are hashed, the system is secure with reliable information Castro and Liskov, ; Kellermann, So basically, a secured communication system can be built on the concepts of the following: proofing and temporally ordering information;.
Branches containing erroneous information may be temporarily created, but with a majority of honest participants, the correct information will survive and the branch will be deleted. As already argued above, IIoT-systems require higher availability and reliability of information. In terms of prioritization, the total cost of a system, the size, weight or form factor are less relevant as long as they fulfill their function reliably.
Therefore, lightweight protocols with the above derived properties of a blockchain have a high potential to achieve the required reliability for IIoT networks. Already some blockchains support the connection of external devices — called oracles — such as Ethereum ethereum. But here, the sensors are only directly connected to the oracles without additional security, so IIoT-devices operate on the same security level, only storing their data on a blockchain instead of a database.
Iota iota. However, this again is a blockchain-technology on its own, which is not designed to be directly connected to other blockchains. Consequently, a sensor-chain-like system needs to be developed, securing IoT-devices with blockchain methods, independent from the decision on which cloud based blockchain to use for storing or processing the data. In the following subsections, some design considerations derived from the criteria in the preceding section for a sensor-chain are described.
Therefore, a unique identity ID is required. This may contain the device number, a binary representation of measured data types or its location for portable or mobile sensors. This ID will be cross-checked multiple times Figure 3 by direct computation and comparison, the comparison by special nodes with extended capabilities and cross-communication and verification among those additional nodes.
It is also fraud proof as these unique properties can be verified: for example, the data types as potential element of such an ID can directly be seen in the transmitted data, or the position can be cross-checked with other principles such as triangulation of the signal strength. This device identification makes the device and its data unique which is the most important precondition for the proof-of-work and consensus.
For an optimum performance in a potentially spatial—dynamic sensor network, the system topology is an important factor in terms of the desired functionality as well as the energy effort. Unlike a wired network with network nodes without any energy restriction, for IoT-devices in a WSN, a peer-to-peer network is not the first choice.
Due to the limited communication range of the nodes, usually a multi-hop routing is required to bridge the distance to a border—gateway into another long range, e. As nodes may sleep or move, node management has to be performed and a permanently updated routing table has to be maintained and communicated.
Therefore, an asynchronous unrouted point-to-multipoint broadcast-network with a longer listening- than sending-interval for every node is preferred. With a sufficient number of nodes — an assumption already arisen in section 3. Here, different neighborhood relationships of nodes and messages have to be considered Skwarek and Monecke, , basically distinguishing between ego-nodes the actual node itself , direct and indirect neighbors.
A permanent process of receiving information from the network, packing this and own information into a new message and redistributing it, lead to a distributed ledger of all information available on the whole network Figure 4. Each sensor may not see all information of all other participants instantly, but over a certain time span, a full network-wide information map is created inside every sensor.
Therefore, this is equivalent to a full-node ledger in blockchain terminology. The node-knowledge is spatially retarded and memory - wise limited. However, in a stationary network with sufficient node memory, the node- and system-knowledge become identical over the time. Realistically, the local node only carries an incomplete ledger. Realistically, all nodes have due to latencies during the information transfer and memory-caused limitations an incomplete and partially outdated picture of the complete network information Figure 5.
This requires every node to regularly update its node-knowledge with all messages received from all other nodes. As these messages may be incomplete, outdated, accidentally wrong or malicious, every node has to consolidate this information. False or outlying information will so be eliminated, and it is not possible to take part in the communication process with just inserting any arbitrary information into the network.
The outcome of this process should be a consolidated value, which will be further used by other network nodes during their consolidation process. Otherwise, this part of a message, which may be accidentally or intentionally wrong, may not be forwarded, neglected or even forgotten over time.
Now, a malicious node may actively try to change the order of information to pretend that all the measurements are right, but need to be reordered by changing time stamps of parts of the information history being broadcasted. Also, this history has to be equal to the node-knowledge of other network participants as they have also created a timeline of information.
As derived and argued above, this network is a full implementation of the concepts of p BFT: With a high number of participants, multiple network paths due to message broadcast and many communication cycles with asynchronous repetitions of consolidated and historical cued messages, the conditions for at least the practical BFT are met. Singular false messages from malicious nodes can be detected and eliminated with various mechanisms as listed in the following text: missing or unknown node ID : if a node ID is not known, the node has no history among other nodes in the network, and therefore, it either may be directly excluded from message processing or has at least a very low reputation, until it has built up a history inside other nodes knowledge;.
If all information is somehow captured and a false ID is successfully generated, the original correct node can create an alarm that something with its ID distributes messages that are not aligned with its own history.
Therefore, a manipulation is at least detectable. Therefore, they cannot be sequenced or at least be sequentially checked against the other information and no timestamp can be created. But here, the complete historical sequence also can be considered unknown be other nodes and can therefore be detected and suppressed. Consequently, with a low number of malicious nodes or information, wrong messages are detected.
Only if one or many nodes start permanently intruding the IoT - network with continuous wrong information, they might be able to build up something like a history, which might eventually be accepted by other network participants as authorized and true information. However, this process will be accompanied by a preceding phase where the intrusion is detectable. As this security process is time- and energy-consuming, it is scalable in terms of transferred length of history, consensus algorithms, rejection intensity and mechanisms and spatial and temporal map size within each node.
Therefore, for a high security level, measures can be taken requiring a high level of energy. On the other hand, this mechanism may also be applied to energy-restricted systems with the risk of a lower security level.
In this article, a principle for increased information security for IIoT-systems organized in wireless sensor networks was presented. Mechanisms from blockchains and distributed ledger technologies were derived and adopted to microcontrollers, with a small energy budget and low calculation capabilities. It was shown that principles such as chained blocks, distributed ledger, time-stamping and consensus could be transferred.
This leads to a higher effort for intruders to gain access to the communication process and to inject false information. In the next steps of research, this concept will be implemented into different domains of application such as long- and short-distance communication, self-sufficient nodes with extensive sleep cycles and transferred to various cloud-based blockchains for permanent information-keeping.
Ragone diagram about the operation time of a mobile device with an energy - storage system under maximum load. Example for a dynamic, de-centrally initiated and controlled production process. Protocol steps of receiving, chaining and distributing. Boucher , P. Castro , M. Dargie , W. Farooqui , A. Kellermann , C. Lamport , L. Nakamoto , S. Obaidat , M. Popov , S. Raghavendra , C. Ronen , E. Schneider , B. Skwarek , V.
Until recently, blockchain technology was only a fringe-technology explored by a small but enthusiastic 2016. Show related SlideShares at end. Introducing koa-multifetch, blockchain-for-web-developers-the-theory.html Node. Already marmelab.com blockchains support https connection of external devices — called oracles — such as Ethereum ethereum. In France, where we live, buying Bitcoins or Ether requires almost the same blog as opening a bank account.