Privacy Preservation in Resource-Constrained IoT Devices Using Blockchain—A Survey
Abstract
:1. Introduction
- We highlight some applications of IoT in different fields and see how much it impacts our lives and how crucial it is to preserve user privacy in IoT.
- We highlight privacy-related issues faced by IoT. We discuss the literature on techniques used for privacy preservation in IoT using blockchain.
- We discuss some of the most important applications of blockchain to show how it is being used in different industries. We highlight the strengths of blockchain that IoT can benefit from.
- We provide an analysis on the integration of blockchain in IoT systems. We mainly focus on blockchain’s potential to preserve data privacy in IoT scenario.
- We provide future directions on privacy preservation in IoT.
2. Internet of Things
2.1. Overview
2.2. Characteristics of IoT
- Intelligence: A lot of IoT devices are set to perform some specific actions when need arises, such as generating an alarm when a wearable sensor senses a high blood pressure for a patient. The decisions taken by a certain device depend on the sensitivity. Artificial intelligence and machine learning are making IoT devices smarter.
- Complexity: There is a huge number of devices, links, and actors in IoT, that keep increasing on a rapid rate.
- Heterogeneity: The devices are different from each other on the basis of hardware, software and networks.
- Connectivity: The devices in IoT are connected with each other through Internet to share data. For example, the sensors used to collect patient data on regular intervals need to transmit this data to the concerned medical personnel [36]. The state of data and devices keep changing. Therefore, it is important to keep the devices synchronized.
- Interoperability: The IoT devices are different from each other in nature but yet compatible when it comes to performing the tasks that involve the use of multiple devices at the same time.
- Decentralization: IoT comprises of billions of devices connected with each other using the Internet throughout the globe. No one “owns” IoT. The elements such as access, control and ownership are spread across the actors/nodes that make up IoT.
2.3. Privacy-Related Issues in IoT
2.3.1. IoT Device Limitations
2.3.2. Complex Heterogeneity Impact on IoT
- Sensing: In this layer, the architecture of IoT provides sensing information for cloud computing to make appropriate decisions by recording and monitoring user data with the help of different kind of sensors e.g. color, camera, motion, flame, etc. Node location leakage is one vulnerability in such kind of heterogeneous IoT which can be address by smart sensor nodes.
- Networking: For forwarding data from source to destination, network layer is responsible in heterogeneous IoT. Due to which, higher transmission rates are provided by the network models like hybrid, star, mesh, and tree networks. The transmission of data through super nodes and relay units to cloud servers is done by network models. They also manage efficient construction mechanisms. Data throughput, energy consumption and malicious attacks are the limitations of network models.
- Cloud Computing: Heterogeneous IoT is accurately handling the large amounts of data with cloud computing. Its main function is to receive and transmit data to and from other architecture layers [46]. Strong analytical computing, storage of data, emergency response strategies and efficient decision making are the advantages of cloud computing.
2.4. Applications
2.5. IoT’s Security Mechanism Deployment
3. Blockchain
3.1. Overview
3.2. Applications
3.2.1. Banking
3.2.2. Healthcare
3.2.3. Supply Chain
3.2.4. Electronic Voting
3.2.5. Smart Cities
3.3. Smart Contracts
3.4. Consensus
3.4.1. Proof-Based Consensus
- Proof of Work (POW) Consensus: First use of PoW consensus started with Bitcoin and became popular after it. It was originally used to verify the transactions and for mining purpose. When a miner mines a transaction, he has to solve a mathematical puzzle. The puzzle involves looking for a value that when hashed generates a specific value. This puzzle is fundamentally computationally expensive. A new block cannot be added to the blockchain without successfully mining it. Once a miner finds a solution to the puzzle, it is broadcasted in the network and can be verified by any or all of the peers. Validation is a cheap task in terms of computational resources it consumes, as it only involves hashing a value, and hence can be done by anyone in the network. As it takes lots of computing resources to solve this puzzle, the miners are given an intentive. After Bitcoin, PoW has been implemented in other several cryptocurrencies, namely Litecoin, Dash and Monero.
- Proof of Stake (PoS) Consensus: In PoW, multiple miners are attempting to solve the mathematical puzzle at the same time. The first successful miner is given an incentive for adding a block in the blockchain, but for other miners, this process was a waste of computing resources. This limitation of PoW is covered by PoS. In PoS, miners are in no competition with each other. The validator receives a transaction fee for addition of a new block. In this way, the total amount of currency always remains the same in the network. Also, the validator is elected beforehand in PoS, unlike PoW, where anyone with enough computational resources in the nwtwork can mine. No one except this elected validator can add a new block. Anyone who wants to be elected has to put a part of his currency at stake. The amount of currency put at stack is directly proportional to the chances of being elected as a validator. After the successful validation, the validator receives the staked currency as well as the transaction fees, and the other candidates get their staked amount back. PoS is used by Nxt.
- Hybrid PoW and PoS: A comparison between PoS and PoW is given in Table 5. It shows properties of both the consensus mechanisms and hybrid consensus mechanism. However, some schemes use a hybrid of both PoS and PoW consensus mechanisms. The key advantage of using this hybrid is getting the advantages from both of these schemes and using one scheme to overcome the limitation of the other one. A hybrid consensus mechanism has been used by Decred cryptocurrency.
3.4.2. Voting-Based Consensus
- Proof of Capacity (PoC) Consensus: Started with Burstcoin, the PoC mechanism decreases the usage of computational resources and uses storage resources. Before mining is started, miners store the set of possible solutions of the puzzle. The miner who has more storage tends to store more solutions. Thus, the miners with more storage space have higher chances of mining.
- Proof of Burn (PoB) Consensus: A concept named “eater address” is used in PoB. Before starting mining, the miners send coins to an invalid address randomly. Blocks are created and these addresses are changes. The coins sent to these addresses are not usable anymore because of the fact that these addresses are invalid and unknown. The process is repeated until there is only one miner left that has some more coins to invest. This miner receives the mining coins and the transaction fees as a reward. Miners that have been investing in creation of blocks in the past are given more privileges. PoB is used by Slimcoin.
- Proof of Importance (PoI) Consensus: PoI is a score-based protocol that was first used with NEM cryptocurrency. The individual who invests more coins in the network makes the higher score. This score is affected by the number of transactions and the size of transactions. The lower limit for investing coins in 10,000 coins. The user with highest score has the highest chance of being a validator.
4. Integration of Blockchain and IoT
4.1. Opportunities Brought by Blockchain in IoT
4.1.1. Secure Storage
4.1.2. Decentralization
4.1.3. Encryption
4.1.4. Access Control
4.2. Applications of Blockchain in IoT
4.2.1. Healthcare System
4.2.2. Software Defined Network
4.2.3. Crowdsensing Applications
4.2.4. Energy Systems
4.2.5. Internet of Vehicles
4.3. Blockchain-Based IoT Privacy Preserving Schemes
4.3.1. Anonymization
4.3.2. Ring Signatures
- Large size of transactions increases the storage space of blockchain records.
- Size of ring signature is directly proportional to the number of participants, that is why only limited number of outputs are generated.
- Auditing difficulty is also faced due to hidden amount.
4.3.3. Non Interactive Zero Knowledge
4.3.4. Mixing
- For fair exchange of transactions, the executional process or online participants waiting creates a huge delay.
- A single point of failure exists due to centralized nature of the server. This makes the server vulnerable to DoS attacks.
- High mixing fees are a problem for users in fair exchange of transactions. Due to low anonymity level, mixing protocol can easily be compromised through Sybil attacks [145].
- The leakage of transaction privacy through backtracking analysis of transactional graph is a serious issue.
4.3.5. Differential Privacy
5. Conclusions
6. Future Research Directions and Challenges
6.1. IOTA Ledger
6.2. Strong Privacy Preservation Mechanisms
6.3. Security Framework
6.4. Blockchain-Based Infrastructure
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Segment | 2018 | 2019 | 2020 |
---|---|---|---|
Utilities | 0.98 | 1.17 | 1.37 |
Govt | 0.40 | 0.53 | 0.70 |
Building automation | 0.23 | 0.31 | 0.44 |
Physical security | 0.83 | 0.95 | 1.09 |
Manufacturing and natural resources | 0.33 | 0.40 | 0.49 |
Automotive | 0.27 | 0.36 | 0.47 |
Healthcare providers | 0.21 | 0.28 | 0.36 |
Retail and wholesale trade | 0.29 | 0.36 | 0.44 |
Information | 0.37 | 0.37 | 0.37 |
Transportation | 0.06 | 0.07 | 0.08 |
Total | 3.96 | 4.81 | 5.81 |
Top Countries | Count | |
---|---|---|
1 | United States | 21,258 |
2 | China | 8655 |
3 | Germany | 5647 |
4 | Russian Federation | 3869 |
5 | France | 3660 |
6 | Korea | 3407 |
7 | Italy | 2858 |
8 | Taiwan | 2639 |
9 | Japan | 2368 |
10 | United Kingdom | 2176 |
References | Survey Based on Blockchain | Addressed in Our Survey |
---|---|---|
[5,49,50] | Decentralized consensus with blockchain taxonomy | * |
[10,51,52,53] | Blockchain applications | Yes |
[22] | Blockchain-based trust model | * |
[14,17,54,55] | Blockchain-based security services | * |
[47,56,57,58] | IoT/IIoT security and its integration with blockchain | Yes |
[26,58] | Privacy issues in blockchain | x |
[59,60] | Smart Contract | x |
[61] | Sidechain technology | x |
[10,18,22,23,24,25,62] | Ongoing research challenges | Yes |
[63,64] | Blockchain security | * |
[65,66] | Blockchain in industry | x |
[27,67,68] | Privacy protection | * |
Properties | Public Blockchain | Private Blockchain | Consortium Blockchain | Hybrid Blockchain |
---|---|---|---|---|
Access Restrictions | Permissioned for public | Permission needed to join the network | Permissioned | Permissioned |
Transaction Restrictions | Permissioned for public | Restricted | Customized | Customized |
Mining | Permissioned for public | Restricted | Customized | Customized |
Decentralization | Fully decentralized | Centralized | Less centralized than private, and less decentralized than public blockchain. | Decentralized |
Need for a Controlling Entity | None | Managed by a single organization | Managed by multiple organizations | Public and private module |
Transparency | Yes | No | Little transparency | Little transparency |
Incentive for mining | Yes | No | No | No |
Examples | Bitcoin, Ethereum, Litecoin, NEO | Hyperledger and R3 Corda, Multichain, Hyperledger Sawtooth | Marco Polo, Energy Web Foundation, IBM Food Trust | Dragonchain, XinFin’s Hybrid blockchain |
Uses | Voting, fund raising | Supply chain management | Banking, Research | Retail, Real estate |
Criteria | PoW | PoS | Hybrid |
---|---|---|---|
Energy consumption | A lot of energy wastage | Less energy consumed (energy efficient) | A significant amount of energy is consumed |
Scalability | Not scalable | Scalable | Partially scalable |
Centralization | Decentralized | Partially centralized | Partially centralized |
Forking | Likely | Difficult | Possible |
Speed of block creation | Slow | Fast | Low |
Double spending attack | Possible | Difficult | Not as severe as in PoW |
51% hash power attack | Possible | Not applicable | Not applicable |
Advanced hardware requirement | Required | Not required | Required |
Applications | Bitcoin | NextCoin | Blackcoin |
Ref# | Model | Limitations | Parameters | Strengths | Tools-Technology |
---|---|---|---|---|---|
[120] | Software defined networking for IoT | Lack of location privacy | Distributed blockchain cloud architecture | Dos/Dos attacks, Data protection, Access control, reduced end to end delay between IoT devices | SDN controller, 6 desktops, 64 Gb DDR3 ram, intel i7 |
[121] | Collaborative video delivery | Lack of privacy and anonymity | Smart contracts | Provide requested service through network service chains | Hyperledger fabric, pbft consensus, CLCs |
[70] | Crowd sensing app | Collusion attacks | whitewashing attack, QAIM | privacy preserving, impersonation attacks | K anonymity, server with k nodes, EM algo in Ubuntu 16.04 environment |
[122] | Scalable access management | Cryptocurrency fees, processing time | Mobility, accessibility, concurrency, lightweight, scalability, transparency | Access control | Ubuntu 16.04 desktop, intel core i7 -950, 3.07 !GHz |
[11] | Secured Grid monitoring | Lack of location privacy | Sovereign blockchain network, cryptographic keys | Data integrity, data confidentiality, data provenance and auditing | Smart contracts, sha256, smart meters |
[71] | Internet of Energy | data provenance and auditing | SCADA network, data encryption and broadcast | False data injection attacks | 54 generators, 118 nodes, 186 branches, 676 communication channels, 676 sensors. |
[75] | Consortium blockhain in industrial IoT | Lack of privacy and anonymity, optimal energy aggregator selection | Optimal pricing, credit-based payment | Secure energy trading | 50 pairs if IIoT nodes, Traditional blockchain, EAGs |
[72] | Decentralized energy trading through multisig and BC | Collusion attacks | Anonymous encrypted message streams, | Privacy, double spending attacks | Python 2.7 with bitcoinlib, libbitcoin toolkit, PYBitmessage API, pysolar |
[123] | Consortium BC in Mobile devices | Lack of privacy and anonymity | Fuzzy comparison method, MFM | Malware detection | Intel core i7-3770, 16 GB, Ubuntu 15.10, DREbin dataset |
[75] | Secure firmware in IoT environment | Data credibility assessment | Remote firmware updates, p2p sharing | Firmware verification and update | BAN logic, Scyther tool, merkle tree |
[124] | Bitcoin | Public key privacy | Paillier cryptosystem, Overlay attack, Double-spending attack | Provably Secure | Multi-layered Linkable Spontaneous Anony-mous Group signature (MLSAG), ring signature |
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Iftikhar, Z.; Javed, Y.; Zaidi, S.Y.A.; Shah, M.A.; Iqbal Khan, Z.; Mussadiq, S.; Abbasi, K. Privacy Preservation in Resource-Constrained IoT Devices Using Blockchain—A Survey. Electronics 2021, 10, 1732. https://doi.org/10.3390/electronics10141732
Iftikhar Z, Javed Y, Zaidi SYA, Shah MA, Iqbal Khan Z, Mussadiq S, Abbasi K. Privacy Preservation in Resource-Constrained IoT Devices Using Blockchain—A Survey. Electronics. 2021; 10(14):1732. https://doi.org/10.3390/electronics10141732
Chicago/Turabian StyleIftikhar, Zainab, Yasir Javed, Syed Yawar Abbas Zaidi, Munam Ali Shah, Zafar Iqbal Khan, Shafaq Mussadiq, and Kamran Abbasi. 2021. "Privacy Preservation in Resource-Constrained IoT Devices Using Blockchain—A Survey" Electronics 10, no. 14: 1732. https://doi.org/10.3390/electronics10141732
APA StyleIftikhar, Z., Javed, Y., Zaidi, S. Y. A., Shah, M. A., Iqbal Khan, Z., Mussadiq, S., & Abbasi, K. (2021). Privacy Preservation in Resource-Constrained IoT Devices Using Blockchain—A Survey. Electronics, 10(14), 1732. https://doi.org/10.3390/electronics10141732