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IoT Blockchain Integration
Published in Mohiuddin Ahmed, Abu S. S. M. Barkat Ullah, Al-Sakib Khan Pathan, Security Analytics for the Internet of Everything, 2020
Kazım Rıfat Özyılmaz, Arda Yurdakul
Zero-knowledge proofs are becoming widely used in blockchain domain for ensuring both privacy and security. By using zero-knowledge proofs, it is possible to create non-traceable transactions and design a new kind of secure authentication systems. A list of projects that leverage this technology are as follows: ▪ Zcash implemented a digital currency with strong privacy guarantees, leveraging the recent advances in zero-knowledge Succinct Non-interactive ARguments of Knowledge (zk-SNARKs) [61].▪ Bulletproofs is a new non-interactive zero-knowledge proof protocol without a trusted setup that has very short proofs [62].▪ Mimblewimble is a blockchain protocol focused on privacy, scalability, and fungibility in digital transactions [63].▪ Anonymous Zero-knowledge Transactions with Efficient Communication (AZTEC) protocol is aiming to enable private transactions on Ethereum [64].
Cryptographic and Consensus Techniques Supporting Privacy and Security Management of Cryptocurrency Transactions
Published in Rajdeep Chakraborty, Anupam Ghosh, Valentina Emilia Bălaş, Ahmed A Elngar, Blockchain, 2023
Zero-knowledge proof is a kind of cryptographic technique with strong privacy-preserving features. The basic concept is that “a certifier can verify to a verifier that an assertion is correct without supplying the verifier with any relevant information. If the certifier and the verifier have a common reference string, it is possible to achieve computational zero-knowledge without the requirement for communication between the certifier and the verifier” [22,24,49,50]. The general ideal of a zero-knowledge proof is described in the reference [51].
Blockchain
Published in E. Golden Julie, J. Jesu Vedha Nayahi, Noor Zaman Jhanjhi, Blockchain Technology, 2020
R. Rajmohan, T. Ananth Kumar, M. Pavithra, S. G. Sandhya
Bhaskaran proposed a data sharing method focused on two fundamental pillars: distributed consent management and double-blind (anonymous) data sharing [8]. Here, blockchain transactions rely on zero-knowledge proofs. An anonymous relationship between a service provider and a requester is proposed. It helps in building a confidential relationship between a service provider and a customer. And it is more useful for multi-party business transactions.
A blockchain-based transaction system with payment statistics and supervision
Published in Connection Science, 2022
Liutao Zhao, Jiawan Zhang, Lin Zhong
As shown in Figure 1, there are four kinds of participants, i.e. a payer, a payee, consensus nodes (or miners) and two independent supervisors, in the blockchain-based transaction system. In generic construction, we will employ a homomorphic encryption scheme, a non-interactive zero-knowledge proof protocol and a digital signature. The main innovation of our transaction system is a homomorphic encryption scheme, which enables the payer, the payee and two supervisors to decrypt the ciphertext payment amounts independently. The transaction system consists of eight procedures, Init, KeyGen, Pay, Ver, PayeeDec, PayerDec, Supervisor1Dec, Supervisor2Dec, for initialising the system, generating keys, paying, verifying, decrypting by the payee, payer and two supervisors, respectively. Private keys are often used to validate transactions and show that a blockchain address belongs to the owner. You can handle cryptocurrency transactions using a public key. It’s a private key that’s linked with a cryptography algorithm. While anybody can submit transaction to the public key, you’ll need to have the secret key to unlock them and show because you own the bitcoin that was acquired. Ciphertext is information that has been encoded using a data encryption. Moreover, a zero-knowledge proof, also known as a zero-knowledge protocol, is a methodology in cryptography through which one participant can establish to some other entity that a particular statement is accurate without providing any further information other than the premise that the argument is correct.
Zero-Knowledge Proof Intelligent Recommendation System to Protect Students’ Data Privacy in the Digital Age
Published in Applied Artificial Intelligence, 2023
Some important considerations regarding the limitations and potential drawbacks of the proposed zero-knowledge proof intelligent recommendation system: Probability of Prover lying: While zero-knowledge proof techniques significantly reduce the likelihood of the Prover lying to practically zero, it is important to note that absolute certainty (100% assurance) is not achievable. Zero-knowledge proofs are designed to provide a high level of confidence in the validity of a claim without revealing sensitive information. However, there is always a small possibility of deception or errors in the cryptographic protocols used.Computational complexity: It is true that zero-knowledge proof protocols can involve multiple interactions between the Prover and the Verifier, as well as a considerable number of calculations. This computational complexity can be resource-intensive and may pose challenges when running the system on slower or mobile devices with limited processing power. Efficient implementation and optimization techniques should be considered to mitigate these concerns.Risk of losing access to secrets: Zero-knowledge proof techniques excel at concealing secrets, but this advantage can also introduce the risk of losing access to the secrets altogether. In scenarios where multiple individuals collectively hold knowledge of a “Top-Secret,” if some of them are no longer available (e.g., due to death), it can indeed result in the loss of access to that secret information. This highlights the importance of proper key management, contingency plans, and ensuring that critical information is appropriately shared among trusted parties.
Flexible, decentralised access control for smart buildings with smart contracts
Published in Cyber-Physical Systems, 2022
Leepakshi Bindra, Kalvin Eng, Omid Ardakanian, Eleni Stroulia
Privacy: Maintaining privacy on blockchain is a complicated issue because transactions and user’s balances in a blockchain are open to public viewing. To tackle the privacy issue, Kosba et al. [45] build a tool, called ‘Hawk’, which helps developers create privacy-preserving smart contracts without the need of cryptography. The tool is responsible for compiling smart-contract code to a privacy-preserving version. Watanabe et al. [46] propose encrypting smart contracts before deploying them to the blockchain network so only those participants who have the key can access the contract’s content (i.e., the state). Bernable et al. [47] provide a comprehensive review of privacy preserving blockchain approaches. For example, secure multi-party computation splits the smart contract between a number of parties with secret keys to compute parts of the smart contract so that a complete picture of a smart contract is not given. Zero-knowledge proofs can provide verification of smart contracts without revealing any information except for the proof to be true; this process can be quite costly. Commitment schemes allow for proofs to be verified with minimal disclosure of secrets. Mixing is also an option where transactions are hidden by generating additional transactions to create noise and hide the original transaction. Furthermore, user privacy can also be maintained in a hybrid blockchain solution where identity is managed by an external public blockchain service, while access smart contracts are maintained on a private blockchain. Our proof-of-concept implementation uses a private Ethereum network which addresses privacy concerns to some extent as all participating nodes are within the organisation. Nevertheless, any of the above approaches can be implemented on top of our access-control service when the meeting participants and times are sensitive and must be protected from some nodes in the network.