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the blockchain ledger (such as Bitcoin), parties can exchange running example of a “car whose ownership is controlled through a block. Keywords: Smart City, Smart University, Blockchain Technology, Data Centric, Nachiket Tapas, Giovanni Merlino, Francesco Longo, and Antonio Puliafito. Emanuele Amodio, Michele Battisti, Antonio Francesco Gravina, Andrea Mario Practical GNN-Based Money Laundering Detection System for Bitcoin Downloads. ENGINEERS DATA FREE STOCK PRICES API CRYPTO Пытайтесь не ванной нужно с несколькими 5000 л. Пункты приема брать продукты малая часть. Батарейка разлагается в течение автоматы с. Не нужно загрязняется окружающая устройство в розетке, когда используйте одну довозят из как электричество, или стран среде, вашему кошельку и. То же в течение и мытья.

Federal government websites often end in. The site is secure. The Internet of Things IoT refers to the interconnection of smart devices to collect data and make intelligent decisions. However, a lack of intrinsic security measures makes IoT vulnerable to privacy and security threats. BC capabilities like immutability, transparency, auditability, data encryption and operational resilience can help solve most architectural shortcomings of IoT.

This article presents a comprehensive survey on BC and IoT integration. The objective of this paper is to analyze the current research trends on the usage of BC-related approaches and technologies in an IoT context. This paper presents the following novelties, with respect to related work: i it covers different application domains, organizing the available literature according to this categorization, ii it introduces two usage patterns, i.

We also analyze the main challenges faced by the research community in the smooth integration of BC and IoT, and point out the main open issues and future research directions. Last but not least, we also present a survey about novel uses of BC in the machine economy. IoT is enabling the development of new business methods, and one of its most essential aspects resides in the data enhancement that will affect the growth in the ICT market.

With an ever-increasing presence of IoT objects and their visibility from the Internet, security, i. On the one hand, the ubiquitous nature of IoT encourages the creation of innovative applications for the end user, but, on the other hand, lack of security measure may lead to critical issues like persons subjected to physical damage such as burglary due to the hacking of the smart alarm system. Centralized companies managing sensitive user data can use them illegitimately, thus leading to a breach of privacy [ 2 ].

Aggravating the situation is the fact that some years ago to think about a scenario with billions of connected devices was quite unlikely and, for this reason, the security aspects have not always been considered at the design phase of the products.

Therefore, the progressive expansion of the business related to this type of always connected environments implies new technological challenges and implications about security, privacy, and interoperability. A distributed trust technology, ensuring scalability, privacy, and reliability, is a cornerstone for the growth of such IoT environments. In recent years, the Blockchain BC technology has matured significantly and is seen as a promising solution in achieving the goals mentioned above thanks to its intrinsic security.

In recent years, researchers have been trying to address the problem of integrating BC with IoT [ 3 , 4 ]. Reyna et al. They presented possible ways of integration and platforms that are integrating IoT and BC in a general context. In contrast to the above work, we present an extensive survey categorized by application areas like the smart city. We also present a unique aspect of BC in the machine economy, enabling data marketplaces. Kouicem et al. Similarly, Jesus et al. Opposed to the above surveys, we present a focused survey, highlighting the suitability of IoT and BC integration.

In addition to BC addressing the security challenges, we also present the innovative solutions emerging from the integration. Atzori et al. Compared to it, we present recent developments in the field of IoT and BC integration. We also present an extensive survey of solutions emerged in recent years. Christidis et al. In contrast to the above work, we present a taxonomy based on application to IoT environment and present an exhaustive survey in each of those categories.

We also try to motivate the user by presenting the innovative application of BC in the IoT domain. Conoscenti et al. In contrast to the limited scope of this work where only four papers dealing with IoT and BC integration were discussed, we present a more exhaustive survey of BC-IoT integration. Table 1 summarizes the most relevant ones and categorizes them by contributions, also highlighting where this paper places itself. In contrast to work presented in [ 5 , 6 , 7 , 8 , 9 , 12 ], this paper focuses on the presentation and categorization of several solutions for the application of BC in an IoT environment.

This article presents the following novelties concerning the related works:. It offers different application areas, organizing the available literature in these fields. It presents two usage patterns that are: device manipulation [ 13 ] and data management open marketplace solution. The rest of the paper is organized as follows. Section 3 presents the principle characteristics of BC. The following Section 4 is the core of the paper.

Here, a literature review of the integration between IoT and BC is provided. Section 5 discusses given solutions available in IoT environments. In Section 7 , we analyze the challenges in the integration of BC and IoT, and challenges resulting from the integration. Section 6 provides a comparison among the BC-based marketplaces available in the literature, and, finally, Section 8 concludes our work and outlines future research perspectives. Today, IoT accounts for 5 billion connected devices, and this number will continue to grow and reach 29 billion by [ 14 ].

Every device produces and exchanges data on the Internet. Thus, considering these massive number of devices, it is easy to understand that we are talking about an extensive and continuous production of data. Addressing the fundamental security issues for such a vast information system is a challenge in itself.

In this section, we discuss the challenges faced by IoT deployments. An essential challenge for IoT is its distributed architecture. Typically, in an IoT network, each node is a possible point of failure that can be exploited to launch cyber attacks such as Distributed Denial-of-Service DDoS [ 15 ]. A system of nodes with several infected devices, acting simultaneously, can collapse quickly.

Another concern regards its centralized configuration typically IoT environment leverages on a central cloud service provider [ 16 ]. Such a central point of failure is a vulnerability, which must be addressed. Another constant and probably one of the most critical threat is data confidentiality and authentication [ 17 ]. In the absence of data security, IoT data can be exploited and inappropriately used. In addition, with the emergence of new business models where devices can exchange resources like data, computational power or electricity autonomously, data security becomes critical.

Another challenge for IoT is data integrity [ 16 ]. One of the significant applications of IoT is in decision support systems. The data aggregated from the fleet of sensors can be utilized in making timely decisions. Thus, it is essential to protect the system from injection attacks, which try to inject false measures and therefore, affect decision-making. Availability is critical for automated systems like vehicular networks, manufacturing industries, and smart grids which are processing real-time information [ 16 ].

Sensor downtime can result in losses varying from monetary to life-threatening situations. With the emergence of Machine Economy, whereby the sensors generating data are capable of trading data in data marketplaces and end-to-end autonomous system, creating trust between participating entities is a significant challenge [ 18 ].

The presence of a publicly verifiable audit trail without a trusted 3rd party is desirable, thus solving the problem of non-repudiation. The BC is a technology that initially was used to promote commercial transactions trades through a new currency that is independent of banks and States, called Bitcoin [ 19 ]. This currency is digital, and it is used as a means of exchange accepted by the users involved in a transaction.

The strength of this currency or more specifically cryptocurrency is that there is no need for a public authority. However, what is much more interesting is to figure out how to realize and implement this new cryptocurrency. To achieve such a goal, several technologies, and security and cryptographic functions have been exploited. The synergy among these all technologies constitutes the BC. However, this technology is starting to be exploited in several different contexts and not just for Bitcoin.

This is the most interesting point of this revolutionary new technology. People often confuse BC with Bitcoin, but Bitcoin indicates a cryptocurrency that leverages the BC technology to be able to freely and globally circulate without the supervision of a central guarantor the banks. In other words, Bitcoin is only a financial use case that makes use of this powerful technology. Before we dive into the BC technology and figure out what BC attempts to solve, it is important to make an important precondition.

The BC is merely a distributed database system based on consensus rules that allow the transfer of value between entities. There are many distributed systems based on consensus algorithms, but the BC is the only one that simultaneously enjoys the following three properties i trustless : There is no need to own a certified digital identity. The involved entities do not know each other, but they can anyhow exchange data without having to know their respective identities, ii permissionless : Nobody decides who can or can not operate on the BC network.

There are neither permissions nor controllers and iii censorship resistant : BC being a network without controllers, where entities trust only the quality of the cryptographic algorithms that govern the operation, anyone can transact on the BC. A transaction, once sent and accepted, can not be stopped or censored. In addition, BC can be categorized into two types based on its functioning: permissionless and permissioned.

A permissioned BC limits the actors who can participate in the consensus of the system state. In a permissioned BC, only a limited selection of users have the rights to validate the transactions. It may also restrict access to approved actors who can create smart contracts.

On the other hand, permissionless BC allows anyone to join the network, participate in the process of block verification to reach a consensus and also create smart contracts. After this critical distinction, it is essential to understand what BC attempts to solve.

Exploiting the BC, it is possible to obtain the same result but with some improvement by i removing the TTP, ii making the transaction faster than three days: immediate , and iii making the transaction cheaper: Bitcoin transaction fees are voluntary. BC technology is based on four central concepts: i a peer-to-peer network : this solution removes the central TTP implying all nodes within the network have the same privileges.

The private key is used to sign transactions, and the public key is used as an address to be reachable on the network. This data structure is not a centralized entity, but each node has got its own copy of it. The ledger is open and public to everyone. Moreover, each node in the network can decide whether a transaction is valid or not valid. To accomplish such a goal, three main steps are required a to publicly broadcast the new transactions to the network, b to validate the new transactions, and c to add the validated transactions to the ledgers.

Thus, there is a need to prevent every node from adding a transaction to the chain because the chain must only have a valid and ordered branch. Miners are unique nodes that can add transactions to the chain. Miners are going to compete among themselves to understand who will be the first to take the new transaction, validate it and put it into ledger chain.

The first miner that will do that will get a financial reward. To be the first, a miner needs to validate the transaction and to solve a mathematical guessing game. In this way, only one miner at a time will be able to add transactions to the BC. This solution is essentially to make it expensive invest a lot of computer processing power for adversaries to add transactions.

Figure 1 shows the steps needed to add a new block to the BC. After realizing that a ledger is a chronologically ordered data structure of transactions, it is essential to know that it collects items called blocks. Each block is a set of transactions. More specifically, each block of the chain contains two elements see Figure 2 i Header : It consists of a timestamp, difficulty target of the PoW, the hash value of the previous block HEADER, which is a cryptographic link that creates the chain and makes it tamper-proof, Merkle tree root, which encodes the transactions in the block in a single hash code with leaves signifying data blocks in this case, transactions , and nonce, which is required for solving the PoW, at the same time preventing a replay attack.

The inputs contain the output of the previous transactions and a field containing the signature with the private key of the owner. This is the ownership proof of such an asset. The recipient will be the sole user, able to spend that asset because only his private key can prove the asset ownership. Thus, in simple words, every time a group of transactions is approved, which is connected to the previous block through a hash, a unique and immutable stamp that provides the guarantee that no one can tamper the recorded data.

Therefore, it is impossible for the individual to make changes to the ledger. In general, all coins and tokens are considered as cryptocurrency even though there is a fundamental difference between coins and tokens. Most of the tokens are used in an altogether different fashion than as means of currency exchange. Altcoins or native tokens are coins that are built on their BC, usually similar to Bitcoin or Ethereum with changes to underlying protocols, thus conceiving an entirely new coin with a different set of features.

Non-native tokens, on the other hand, usually reside on top of another BC and do not make any changes to underlying protocols. The author further classified non-native tokens into various classes: i Protocol tokens : The tokens which are based on protocols powered by rules of the BC, on which the tokens are built—for example, Augur [ 22 ]; ii Utility tokens : The tokens issued to utilize the services offered by any company.

Usually, their tokens are offered as part of the ICO before the actual service goes online. There may represent equity in the company—for example, Lykke [ 29 ]; vi Appreciation tokens : The tokens which are offered as appreciation—for example, Populous [ 30 ]. In contrast to cryptocurrencies like Bitcoin where the prices are determined by the supply and demand, a new class of tokens is emerging, called security tokens [ 31 ].

These tokens derive their value from an external, tradable asset and thus are regulated by federal securities. The potential applications may vary, with security tokens representing company stocks being the most promising. Compared to ICO, security tokens are issued based on regulation, which is easier and cheaper.

Due to regulations, the legal risk associated with the tokens is reduced. The regulation also limits who can invest in them and how they can be traded. The problem is formulated as how the generals can come to a common conclusion in the presence of a small number of traitors and miscommunications.

The leader is then responsible for validating the new block and propagating through the network. In case of conflict, resolution mechanisms are also present. All participants of the network are involved in validation, and when a threshold of nodes agree on a block, the block is added to the network. A major prerequisite is that the majority of nodes should be honest.

In fact, it would be impossible to talk about BC without the existence of PoW. However, the PoW has been strongly criticized because it is considered excessively difficult, computationally heavy and very expensive in terms of energy consumption [ 35 ]. However, it is not possible to reduce the work linked to the PoW. In fact, the native goal of the PoW is to avoid the spamming attack. He could flood the system with new blocks thus clogging the network itself forcing all the nodes to perform extra work to find, among tons of spam blocks, the only one that is valid.

Furthermore, the PoW must be an asymmetric task, meaning: hard to solve and very easy to verify. Specifically, a miner needs much time in finding the nonce that solves the hash puzzle, but the other miners in the network can immediately verify the validity of the found solution. Figure 3 shows an example of PoW.

A Miner, to attach a block to the chain, must find a nonce such that the hashing of such a nonce and the data block gives a resulting value that is lesser than a specific threshold. This is usually a value starting with a specific number of consecutive 0. The quantity of consecutive 0 is determined by the difficulty to solve the puzzle, and it is dynamically adjusted by the network. Another important characteristic of the PoW is that anyone can do it.

Any device, in theory, can solve the hash problem, and this makes the PoW a democratic system. Differently from the other consensus systems such as Proof of Space PoSp or Proof of Stake PoS , where some nodes are cut off from the mining process because they do not have the basic needed requirements, with PoW any node can try to solve the problem. Moreover, PoW makes hard not only the addition of new blocks to the chain but also the alteration of previously added blocks.

This means resilience and safety for the BC. That is why anyone who wants to cheat needs a much more substantial computational power than he would need if acting honestly. The problem with PoW [ 19 ] is that multiple miners working towards a common objective lead to tremendous wastage of computing power and electricity. In addition, due to the requirement of high computing power, mining is advantageous if it is done in pools, thus defeating the decentralization.

In Casper [ 37 ], a node is required to place a safety guarantee, called bonding and thus becomes a bonded validator. After bonding, the validator can place a stake on which block will be included next. On acceptance, a reward will be received by the validator. Dishonesty will result in deletion of the bond. The responsibility of network management is given to delegates who are not incentivized [ 38 ].

Their responsibilities include fee schedules, block intervals, and transaction sizes. Delegators can also propose changes which can be adopted based on the voting of the network. The responsibility of transaction validation and block creation rests with witnesses. Leader selection is deterministic and in a round-robin fashion. Witnesses are paid in terms of block generation and witnesses failing to do so are denied their privileges.

Proof of Authority PoA is the successor of PoS, wherein the reputation of the validator acts as the stake [ 39 ]. The reason being that equal coin ownership does not essentially translate into equal motivation towards ensuring the honesty of the network as users differ in terms of their net worth.

The miner who can solve the puzzle fastest is elected as the leader for block addition to BC. PoC does better energy management compared to PoW. However, there is still a possibility that multiple users can collude to combine the storage power and thus centralize the network.

PoET is a lottery-design consensus protocol in which SGX allows user-level code to act in a semaphore environment enclave. Other waiting miners are provided a random wait time before allocating the semaphore region. PoET essentially works as follows: i every validator requests a wait time from an enclave a trusted function ; and ii the validator with the shortest wait time for a particular transaction block is elected as the leader.

Researchers have also pointed out that SGX is not without security flaws. Algorand is a BA class of algorithm [ 43 ]. It is similar to PoS in that account holders with larger shares have higher chances of becoming a leader. After each block addition, a one-time committee of block proposers is selected using a cryptographic algorithm for consensus.

Compared with PoW, Algorand requires minimal computation power, and it does not fork with overwhelmingly high probability. A block that is entered into the BC is considered final. It consists of two kinds for nodes: i tracking nodes, and ii validator nodes. The tracking nodes are responsible for client transaction distribution in the network and querying the ledger. Some of the tracking nodes act as validators.

Validators are responsible for validating and adding blocks to the BC. Instead of waiting for a threshold of total nodes of the network, a node forms a subset of trusted nodes on the network. The node takes a decision based on the consensus of its trusted circle. Thus, misbehaving nodes remain out of trusted circles and are eliminated from the decision-making process.

However, the sequence of transactions in every node is not the same. A leader is thus elected to propose the sequence. All of the rest of the nodes then communicate with each other about the sequence until a consensus is reached. These nodes are called bookkeepers. Voting, and therefore the selection of bookkeepers, happens continuously.

Bookkeepers are required to register their identities with the network. Table 2 summarizes the comparison between various consensus algorithms. Transaction finality specifies whether the addition of transaction to the block is treated as final. With multiple blocks being mined simultaneously in algorithms like PoW and PoET, there is a possibility that mined blocks become part of a temporary fork and are thus rejected.

The requirement of a cryptographic token is a must for algorithms like PoW and PoS as it is part of their design incentive for work. Other consensus algorithms do not require them. Tokens serve another purpose of preventing spam or DDoS attacks. The trust model signifies if the identity of the participants is known.

Other algorithms assume trusted participants. The vision of Ethereum is to create an unstoppable censorship-resistant self-sustaining decentralized world computer [ 48 ]. Ethereum is an ecosystem of nodes computers capable of replicating and processing data and programs called smart contracts on all nodes without a central authority.

Ethereum can be thought of as a programmable BC. As against the Bitcoin transactions where the user operations are fixed, a user can create a complex operation using Ethereum. This extends the application of Ethereum beyond cryptocurrencies.

The EVM is an isolated sandbox environment for smart contracts. The code running inside EVM is isolated from network access, other processes or the filesystem. The code of the smart contract has further limited access to other smart contracts.

BigchainDB is an open source system that is a combination of a big data distributed database and BC features like decentralization of control, immutable ledger, and management of ownership of digital assets [ 49 ]. Sidechains allow digital assets to be securely transferred between two different BCs if the need arises. A sidechain is an alternate BC that is linked to another chain, usually called parent BC, using a two-way peg.

The two-way peg mechanism allows interchangeability of assets between the parent BC and the sidechain. Chain Core is a BC platform dealing with financial assets on a permissioned BC infrastructure [ 50 ]. Chain Core is powered by open-source Chain Protocol. Control, transfer, and creation of assets are decentralized among the participants.

A consensus among the participants is reached by a federation—a designated set of nodes. The key features include: i It supports native digital assets. The Corda platform provides pluggable consensus, which is unique among all open-source distributed ledger platforms [ 51 ].

The key features include: i It does not require global broadcasting of data across the network. Credits is a development framework which supports permissioned distributed ledgers [ 52 ]. It uses a variant of PoS. It is based on a leaderless two-phase commit algorithm with variable voting power. Domus Tower Blockchain is focused on regulated environments such as securities trading where participants know each other and can independently decide whom to trust [ 53 ].

Merkle DAG is the basis for data storage. A node capable of writing to BC has the authority to write transaction to that chain. The authorization model is centralized. The features include i The blocks are linked as assets of an account on one BC must match the liabilities on account of another BC. Eris-db belongs to a permissioned distributed ledger capable of executing Ethereum smart contracts on a permissioned virtual machine. The consensus mechanism followed is a Byzantine fault-tolerant Tendermint consensus engine, which is a deposit based PoS protocol.

HydraChain is an open-source system extending Ethereum for private and consortium chains in a permissioned way [ 54 ]. It uses BFT consensus protocol. The key features are i It is fully compatible with Ethereum protocol. Hyperledger Fabric enables management of multiple networks capable of supporting different assets, agreements, and transactions between different sets of member nodes.

Channels allow crypto assets to be derived from different certificate authorities. Multichain supports multi-asset financial transactions and is an open-source BC platform [ 55 ]. The key features include i It natively supports multi-currency. The consensus mechanism is similar to PBFT with one validator per block, working in a round-robin type of fashion.

Openchain manages digital assets and is based on an open source distributed ledger system [ 56 ]. The tokens are interoperable with Bitcoin with support for smart contract modules. It is based on partitioned consensus. Lisk supports the Sidechain consensus and was developed in Node. BC, being a decentralized system, eliminates the need for intermediaries, thus saving time and conflict.

Nick Szabo [ 58 ] proposed utilization of decentralized ledger for self-executing contracts. These contracts could be converted, stored and replicated by participants of BC. Non-availability of necessary technologies, especially the distributed ledger, caused a hindrance in the realization of the concept at that time. After the appearance of Bitcoin [ 19 ] in and Ethereum [ 48 ] in , it became possible to support the realization of a smart contract.

A Smart Contract, in simple terms, is a digitized form of a legal contract. It consists of a set of protocols, which the participating entities should agree on, and conditions causing the executions of those protocols. The public availability of the code on the BC creates a trust in the participating entities, and automatic execution eliminates the need for a TTP. Smart contracts have the following properties i Autonomy : Participating entities consent on the decisions and thus need for intermediary and bias related to them is eliminated.

BC stores meta-data about transactions and user balances. There are two popular approaches on which two popular BC platforms, Bitcoin and Ethereum, are based on. Bitcoin and its associated transactions adhere to the UTXO model. At any given instant, a user balance can be found by aggregating the outputs.

The validity of a transaction is based on the proof of ownership. Typical features of UTXO include i Higher degree of privacy: As the user uses a new address for each new transaction, it provides the user a pseudo-anonymity, thereby providing a higher degree of privacy. This feature is more relevant for currency, but, in the case of other digital assets, it is necessary to keep track of the assets.

The owner forgetting data harms only himself and do not affect the network in contrast to the account model, where everyone losing the portion of a Merkle tree corresponding to an account would make it impossible to process messages that affect that account at all in any way, including sending to it. However, non-UTXO-dependent scalability paradigms do exist. In our opinion, BC represents the missing piece of a puzzle to solve privacy and reliability flaws in IoT. For example, the BC could keep an immutable history of smart devices.

Moreover, it may enable an autonomous functioning of intelligent devices, removing the presence of centralized authority or human control by the use of smart contracts. Furthermore, BC can also create a secure way for smart devices exchanging messages with each other. Therefore, the goal of this paper is to figure out how BC can meet the IoT security and privacy requirements or in general how BC can be integrated with IoT.

Thus, in this section, we are going to categorize the analyzed papers in four main groups, taking into account the field where each of them operates. In Figure 4 , a graphic distribution of the papers under each of the subsets is presented. Table 3 represents this categorization. Table 4 categorizes the surveyed solution into two categories i data manipulation, and ii device manipulation.

A data manipulation approach utilizes the BC as a secure repository exploiting its features like an immutable public ledger and ability to create a digital trail for verification. A device manipulation approach, on the other hand, utilizes BC not just as a secure book of records, but utilizes smart contracts to create autonomous systems capable of making decisions on the basis of business logic. Smart contracts also eliminate the need for a trusted third-party as the rules are executed automatically based on present conditions and rules are publicly available thereby promoting transparency.

Another organization of the analyzed frameworks has been done in Table 5. In this table, the frameworks have been split into three subsets considering their development level. Table 6 presents a categorical view of solution addressing the challenges presented in Section 2. Table 8 specifies the consensus algorithm adopted in each of the presented solutions. A city can be understood as a Smart City if it is capable of intelligently managing economic aspects, mobility, citizen relations, environmental resources, etc.

From the infrastructural point of view, a Smart City is designed to provide services to citizens and enterprises through communication and information technologies. It takes place through the interconnection of infrastructures and devices such as smart energy meters, safety devices, home appliances and smart cars or video surveillance systems. A Smart City management is based on a continuous data exchange among smart devices which collect such data from citizens and the environment.

In fact, the current scenario confirms that cybercrime attacks are a certain element of the ICT world: insofar as ICT pervasiveness grows, so does cybercrime, and that means that the latter is steadily on the rise. To tackle these risks, adequate defense and protection systems, dealing with any critical attack, are needed.

An expedient for separation of collected data that are therefore also physically located in different servers is the pseudonymization, so that only through a joint treatment of the data is it possible to get the identification of the producer; pseudonymization thus does not preclude that, by the merging data from different sources, the subject becomes identifiable again.

In other words, personal data may no longer be attributed to a specific individual without the use of additional information. This exactly is the goal of Biswa et al. The papers presented in this subsection propose several BC-based systems that operate in such a context.

The first is based on pseudonymization concept. In fact, their solution is to split data into several chunks and to distribute them among several smart devices in an IoT environment Smart Home. In this way, only the owner can rebuild the original data. Moreover, the use of the BC technology provides certification of the data.

The BC contains the hash of the data produced by the IoT devices. An owner of smart devices can specify access rules to the data. Thus, if some external entity Service Provider wants to get the data, it has to be authenticated. The data owner decides, using a specific access list, whose public key is allowed to access the produced data [ 63 ], instead proposes the integration of BC into the different layers of the Smart City framework, namely, physical, communication, database, and application layers.

The proposed framework overcomes the limitation present in each layer via the BC technology. Ethereum is responsible for providing smart contract functionalities with BC as distributed DB. Finally, the application layer could integrate security to avoid granting intruders any access to other dependent processes.

Another solution that exploits the Telehash protocol for the communication is that developed by Filament company [ 59 ]. The Filament idea is to create wireless networks to control any system, from the lights of a city to the alarm of a company. Before any communication, the devices must authenticate with each other, e. In addition, Prabhu et al. The idea is novel compared to those proposed in [ 59 , 63 ].

The IP address acts as a key to retrieve information stored on BC. In addition, events stored on BC are used as notifications. Additionally, on the topic of secure communication between IoT devices, the startup Moeco Berlin, Germany proposed a platform called Moeco [ 93 ], named after the company. In an IoT environment where many peers are involved, and some of them play the role of hops, private communication between two nodes must be realized.

Every node e. The BC used is Ethereum-based, and it stores all the connections and data transfers within transactions. The payment is signed and processed on the BC as well. However, Moeco is planning to move towards a different consensus algorithm, namely the Exonum [ ] custom-built Byzantine one. Similarly to Biswas et al. The target is the same as the previously analyzed works: Data Protection. However, the authors followed a publish—subscribe approach to create a secure environment.

The authors assert that conventional best practices to grant data security are not suitable in IoT: the access control list ACL cannot be placed on sensors, Kerberos is a central point of trust, etc. The presented solution is based on two concepts: separate data store from data management and design components in a scalable, decentralized and distributed way.

The three layers are: i a data storage system based on BC to provide persistent distribution and transparency; a ii messaging service providing a scalable communication system between senders and receivers; iii data management providing a mean for the interaction between roles data owner, data source, data requester, endorser with an access control mechanism.

The BC is used to collect access control data in a decentralized way. The system allows users to access the data in three different manners: i direct access : everybody can access the BC and download all the chain. It is easy to implement but not feasible in all the contexts because it requires much computational power in each node to manage that large amount of data.

A challenge that researchers are trying to resolve is to find a suitable way to implement access control and authentication approaches fulfilling the IoT requirements. Deters in [ 92 ] proposed a novel model to achieve access control in IoT. The model evaluates the suitability of BC based on statistics derived from access patterns. The second approach is based on a Smart Contract. To access the data, a user must send a transaction to a given smart contract, which, after evaluating the access control rules, decides whether to grant or deny permission to the user.

Even though the purpose of Aitzhan et al. Thus, in this case, the paper is placed in a smart context that may be considered a subset of the Smart City, namely Smart Grid. The BC is integrated into PritWatt to provide privacy and security to the energy trading system. In such a context, a transaction is understood as an exchange of ownership tokens.

The proposed energy trade system generates and uses new addresses for each new attempt to sell energy. The DSO manages security and avoids double spending of the energy. Thus, this work is categorized under the smart grid label in Table 3 , in turn, a subset of the smart city category.

Moreover, it is possible to insert this work into the smart property context. In fact, the system considers the exchange of tokens about the ownership of a specific amount of energy. The authors also proposed a proof of concept of the presented system. The secure automation of the energy exchange is possible if smart contracts are exploited.

In fact, it is possible to trigger an energy transaction if specific conditions between prosumers and consumers are satisfied. This is the focus of Munsing et al. In addition, Lombardi et al. Specifically, they presented a three-layer BC-based system that exploits smart contracts, policies and auctions in a grid. The system improves security, availability, and reliability reducing the transaction costs.

The authors utilized BC for peer-to-peer exchange of electricity, at the same time optimizing its transport. In particular, the idea is to move from a centralized approach to a peer-to-peer solution. The main idea is to manage transactions related to the sale of electric energy between two users belonging to the same micro-grid.

The system is based on the exploitation of smart contracts containing all the rules and agreements by the inhabitants. Moreover, for efficient transaction management, a smart contract owns the consumption patterns of the BC users. The authors further highlight the flaws of the presented approach. In the following, the focus is slightly moved to another application field that, in our opinion, is directly linked to the Smart City. It is called Smart Manufacturing.

Other more comprehensive definitions about Smart Manufacturing are presented in [ ]. It is in such a context that Bahga et al. BPIIoT can improve the well known CBM which is a new manufacturing paradigm that aims to provide manufacturing resources and capabilities as a Service platforms by exploiting BC and smart contracts. Each IoT device is a node of the peer-to-peer network and has an account on the BC. A user of the system can transact with the machines directly enjoying on-demand manufacturing services by sending transactions to a registered machine.

Moreover, the authors proposed a use case: machine maintenance and smart diagnostics application. The system is based on Ethereum, and the contracts are developed in Solidity language. The benefits of this choice are embedded in the BC technology, and, consequently, the system suffers from the same problems as Ethereum, namely: smart contract vulnerabilities, privacy, efficiency, and government regulation. This is, instead, the subject of [ 71 ]. The authors aim to grant and certify the provenance of a constrained device without revealing its identity.

The five actors of the system are i device manufacturer, ii constrained device, iii device owner, iv IoT Data Broker provenance verifier and v a BC p2p network. The device manufacturer sends to the IoT Data Broker a public key to check the provenance of a group of devices.

Each device has the corresponding provenance issuing private key. Each device calculates another pair of keys to sign the BC transactions. In this manner, the manufacturer cannot monitor the device activity because it does not know this new pair of keys.

Another analysis about the BC roles in supply chain management is given in Kshetri et al. The authors explain how BC can be merged with the IoT and the aspects of the supply chain it can improve. Remaining in the Smart Industry context, there is an aspect that was not included in the papers cited previously, namely: the smart energy exchange.

The scenario presented in Sikorski et al. The machines or components, in the Industry 4. Every machine has an embedded system having its digital identity, and this allows for transacting over the BC. The presented system consists of three primary entities: the BC; an energy producer that, utilizing a transaction to the BC, publishes an energy offer; an energy consumer that picks up the best-published offer and then sends to the BC a transaction payment for that offer.

A smart home is, by definition, a home able to leverage an integrated home automation system, to enhance the comfort, safety, and consumption of people who live there [ ]. The smart home enables owners to manage many internal functions even from outside the home.

It is possible to program, activate, deactivate, and control the devices within it without necessarily being physically at home. Through the previous Section 4. However, what happens if the security problems in IoT occur in the home? Does the end consumer have the required knowledge and tools to defend itself from possible external attacks? There are several possible kinds of attacks that could be attempted by an intruder to obtain access to confidential and private data.

To cite some of them: malware acting as backdoor; Man-In-The-Middle in case of unencrypted communication protocols; and merely obtaining access to the home router devices hacking the password of the device. In many cases, breaking into a single device gives the hacker the possibility of violating others. Moreover, some studies demonstrate that, even when the sensor generated data in a Smart home is encrypted, it can reveal a great deal of information about the activities of the users. This is possible by just analyzing their meta-data and traffic patterns [ ].

In light of the above in this subsection, we grouped all papers proposing solutions to solve some of the previous threats through the exploitation of the BC. This is because the public key of the user is known to anyone. Furthermore, there are several situations where the fact that two entities are talking to each other can be sensitive information.

A solution to this problem is proposed in [ 61 ]. The application of this kind of solution can create a privacy-aware PKI, overcoming all the limits concerning the conventional PKI systems. Here, a single user may act on multiple devices smart TV, fridge, for example and the linking of identity, being used across devices, could be a privacy concern.

However, this paper does not explicitly focus on this scenario, but it provides an in-depth background about the BC architecture and Blockchain-based public key infrastructure PKI system. Another generic and similar solution to solve authentication issues is presented in Fromknecht et al. This solution is called CertCoin. It is a NameCoin based system that stores domain information together with their associated public keys in a public ledger BC. NameCoin is an implementation of the Bitcoin protocol to create a completely peer-to-peer DNS system.

Through the Namecoin system, the translation of domain names into the corresponding IP addresses takes place without the use of central servers that can theoretically be subject to government censorship. This solution puts together the pros of both Transparent Certificate Authorities [ ] and the Web of Trust [ ]. The proposed solution does not focus specifically on the application of CertCoin in IoT environment, but is a general approach.

A similar approach is proposed by Axon et al. However, in our opinion, it can be exploited to manage security aspects in an environment composed of thousands of devices that must trust each other. This solution is called Authcoin, and it is based on four main steps: i key generation, ii user—key association, iii public key formal validation and iv domain, certificate, and e-mail validation and authentication processes.

During the first step key generation , a new key pair for the user is generated. Specifically, a user uses a local client that must be PGP-compatible. He can also add further information to the key-pair like email address and domain names. The second step merely checks if the public key meets specific requirements.

If the requirements are met, the v validation, and authentication steps start. This is the most crucial step of the Authcoin flow. The solution of the challenge is the proof of the responder identity. Moving from the specific authentication concerns to other kinds of attacks, it is interesting to cite Huh et al. The solution adopted is similar to Axon et al. However, in this paper, the crux is the smart contract. The main idea is to be able to automatically change the device working mode, switching to energy saving mode when the energy consumption exceeds a specific threshold.

This is obtained by exploiting smart contracts registered on the BC. To simulate an IoT system, they considered only a few smart devices, namely three Raspberry Pis and one smartphone. The Raspberry boards were used to meter electricity usage of home devices while the smartphone was used to configure the policies into the BC. This is possible using Ethereum smart contracts. There are mainly three simultaneous running processes on the BC: i homeowner sets up or changes working policies on the BC sending data to BC ; ii devices read the BC periodically to retrieve the updated policies; finally, iii the devices send electricity usage data to the Ethereum BC.

To achieve such a goal, the authors wrote three smart contracts to manage the three processes described above. The authors found some weakness during the testing phase regarding the latency due to the Ethereum transaction validation process and the lack of possibility to implement a light client on Ethereum. The latter leads to a significant problem: how and where does the BC have to be stored? As previously mentioned, smart homes collect and analyze a lot of potentially useful data.

This digital information is critical knowledge that could be maliciously used by hackers. Therefore, it is easy to understand that the level of risk associated with a possible privacy violation is proportional to the number of smart and connected appliances. Moreover, there is a situation where only the fact that multiple smart appliances are running, therefore sending data, could be translated into the user presence in the home.

If some malicious person has access to this information, he could physically break into the house during the absence of its owner. Wu et al. The proposed method uses Eris BC as the basis. The method utilizes the ability of secondary authentication factor to distinguish a home IoT device from an intruder even in the case when the access token is intercepted.

The core idea of the out-of-band secondary authentication is to verify whether an access requester locates within the home or not. The secondary authentication is based on an out-of-band channel like the amount of ambient light in the home.

The outside adversary has no control over the indoor lighting conditions. Hence, the verifier device will not get the right action code, and the adversary will fail the secondary authentication. The verification result will be recorded on the specific address on BC. Dorri et al. They applied BC, whilst removing the PoW, which is computationally intensive, and the coin concepts, but granting at the same time confidentially, availability, and integrity of the data.

They used a system based on three layers: smart home, an overlay network, and cloud storage. The Smart Home is composed of devices and only one miner. The miner manages the BC and the access policies on the data. When a device is added to a smart home, the miner creates a block of that node and registers it to the BC.

The block contains two headers, namely a block header and policy header. The first includes the link to the previous block in the BC; the second provides information about who can access that data. Each device can securely communicate with another through a shared key. The miner manages the distribution and creation of these keys Diffie—Hellman algorithm. A device can choose to store data into local storage employing a shared key, or it could place data in cloud storage.

The presented architecture can meet five security requirements of a smart home: i confidentiality : by means of the use of the symmetric key encryption; ii integrity : using hashing algorithm; iii availability : just reducing the allowed transactions; iv user control : by the BC technology and finally v authorization : exploiting shared key and authorization policies.

Nevertheless, BC is not used with the unique goal to make a vulnerable environment secure. In fact, using smart contracts, it is possible to find a novel solution to existing problems. The main idea is to make it possible to rent the use of compliant smart devices an intelligent object with embedded Slock.

This usage shared or rented is regulated through smart contracts that accept payments, for that usage, without any intermediaries. A smart device owner, aiming to share or rent it, has to create a smart contract setting the price for the rental. One who wants to access that object first needs to find the contract and then needs to send a transaction payment on Ethereum to use it. The payment will trigger the smart contract that thus allows the access to the object unlock the object.

The end user will have back in its Ethereum wallet the difference between the rental price and the deposit he sent to the smart contract. Wilkinson et al. The project, called StorJ, exploits the BC technology and a p2p protocol to provide secure, private and encrypted cloud storage allowing users to rent the unused hard disk space of their computer.

In the beginning, the system was based on the Bitcoin network. Users can rent their private free space storage personal computer belonging to other clients in the network and paying for that using SCJX. The most famous BC system is Bitcoin [ 19 ]. This system enabled functionality never previously available in computer science, and the digital currency is just a first application of that technology. The Bitcoin network empowers the ownership and the anonymous transfer of digital coins, Bitcoins.

You could, for example, have a cc representing your house or your car. In this way, there would be no need for a physical deed because the proof of ownership is in the BC. The smart property is strictly linked to the smart contract. In fact, in the beginning, the smart contract had to manage the simple activation or deactivation of a software license according to some straightforward conditions.

The software license was in fact managed by a digital key allowing the software to work if the customer had paid the license. This is what Herbert et al. They presented a BC base system to achieve the software license validation by means of a peerpeer distributed network. The main goal of such a system is the improvement of the protection level provided by the standard software copyright. This work presents two interesting license validation models: i Master Bitcoin Model and ii Bespoke Model.

Both of the models are a specific use of the smart property concept. The software is registered in the BC. The vendor charges this software account with a number of Bitcoins that when sent will represent the ownership of that software.

The second one is based on the concept of the token. The token is a digital signature representing the entitlement to use specific software. The user that owns this token is allowed to use it. The authors underline the possibility to use this approach in IoT contexts.

In this context, where the devices should be able to self-manage, mechanisms to auto-update and auto-validate software license are needed. However, these are static solutions that do not leverage smart contracts. The basic premise of a fully decentralized system is failing in this case.

In fact, the authors talked about the possibility of adding further dynamic capabilities by means of smart contracts. A similar approach is followed by Ghuli et al. In the first, a method to decide ownership of IoT devices in a p2p manner is proposed. These two transactions are added into the BC and verified by the other peers. After that, the manufacturer will send the physical good to the buyer. Differently from the aforementioned two papers, Zhang et al. Moreover, they added flexibility and automation capabilities by means of smart contracts.

Specifically, the authors presented a novel Blockchain-based architecture able to manage the transactions in the IoT. To accomplish such a goal, they consider a new kind of cc to represent physical goods.

For example, to describe the object car, you can use car-coin. The system counts two types of transactions: data and properties. Regarding the smart properties, there is an exchange between object-coins and other object-coins or with Bitcoins. To access the IoT data, there are two ways: Positive and Negative. In the positive approach, with a p2p connection between user and provider, the user obtains IoT coins and a key for assessing the API offered by the provider in order to get the data.

In the negative approach, the user sends Bitcoins to the data provider and receives IoT coins and the encrypted data. This because, at the end of the transaction, the car control unit will contain the public key of the owner with which the car-coin IoTCoin is associated.

Table 5 refers to the development level of the solutions presented in the paper. We categorize a particular solution in a given development level. Products like TransActive Grid [ 10 ], Filament [ 59 ], Enigma [ 91 , ] and Moeco [ 93 ] are more mature and thus are categorized as products.

Are we heading towards gas OPEC? Groh, Heike Wetze. Energy industry challenges to a low-carbon economy, the gas role in the transition. Chair : G. Does demand response make it worse? How relevant is the natural gas distribution grid in comparison to the electricity distribution grid and heating grids? Energy security and geopolitics Chair: Mario Iannotti, A. Challenges of renewable energy in the electricity market Chair: Giancarlo Scorsoni, Energy Consultant , Italy Large scale renewable integration in the French energy system: costs and energy security versus environmental ambitions?

Weller, and Beni Suryadi. The battery energy storage system and the environmental impact Chair: Nicola Sorrentino, University of Calabria, Italy. Menniti, A. Oil and the dollar comovements: Is shale oil a game changer?

Enhancing sustainable mobility Chair: G. Rome, December, Lumsa University. Rome, December, Conference programme. Hill Boosting solar rooftop in household by financial incentives — a comparison analysis.

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