Kasra Abbaszadeh, Christodoulos Pappas, Jonathan Katz, Dimitrios Papadopoulos
A zero-knowledge proof of training (zkPoT) enables a party to prove that they have correctly trained a committed model based on a committed dataset without revealing any additional information about the model or the dataset. An ideal zkPoT should offer provable security and privacy guarantees, succinct proof size and verifier runtime, and practical prover efficiency. In this work, we present Kaizen, a zkPoT targeted for deep neural networks (DNNs) that achieves all these goals at once. Our construction enables a prover to iteratively train their model via (mini-batch) gradient descent, where the number of iterations need not be fixed in advance; at the end of each iteration, the prover generates a commitment to the trained model parameters attached with a succinct zkPoT, attesting to the correctness of the executed iterations. The proof size and verifier time are independent of the number of iterations.
Jose Miguel Lara Rangel, Stefan Schoepf, J. Bennett Foster, David Krueger · 5 authors
Machine unlearning is gaining increasing attention as a way to remove adversarial data poisoning attacks from already trained models and to comply with privacy and AI regulations. The objective is to unlearn the effect of undesired data from a trained model while maintaining performance on the remaining data. This paper introduces HyperForget, a novel machine unlearning framework that leverages hypernetworks - neural networks that generate parameters for other networks - to dynamically sample models that lack knowledge of targeted data while preserving essential capabilities. Leveraging diffusion models, we implement two Diffusion HyperForget Networks and used them to sample unlearned models in Proof-of-Concept experiments. The unlearned models obtained zero accuracy on the forget set, while preserving good accuracy on the retain sets, highlighting the potential of HyperForget for dynamic targeted data removal and a promising direction for developing adaptive machine unlearning algorithms.
Blockchain technology has emerged as a transformative solution for securing distributed networks, offering decentralized and immutable data management. However, the resilience of blockchain systems faces challenges from various security threats, including double-spending, Sybil attacks, and vulnerabilities in smart contracts. This paper explores the effectiveness of various blockchain security protocols in enhancing the security and stability of distributed networks. The study provides a comprehensive review of cryptographic techniques, consensus algorithms, and privacy-enhancing technologies, such as Zero-Knowledge Proofs and Multi-Party Computation. Through a detailed analysis of case studies involving Bitcoin, Ethereum, and Hyperledger Fabric, the paper highlights the strengths and limitations of different security protocols. Additionally, the paper discusses the future direction of blockchain security, including the impact of emerging threats such as quantum computing on current security measures. The findings emphasize the need for ongoing innovation in security protocols to ensure the long-term resilience of blockchain networks. The paper concludes with recommendations for improving the security frameworks in both public and permissioned blockchains, with a focus on scalability, privacy, and resistance to emerging attacks.
Abstract In an Instance-Hiding Interactive Proof (IHIP) (Beaver et al., in: Menezes and Vanstone (eds) Advances in cryptology—CRYPTO 1990, proceedings, lecture notes in computer science (including subseries lecture notes in artificial intelligence and lecture notes in bioinformatics), Springer, pp 326–338, 1990), an efficient verifier with a private input x interacts with an unbounded prover to determine whether x is contained in a language $$\mathcal {L}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>L</mml:mi> </mml:math> . In addition to completeness and soundness, the instance-hiding property requires that the prover should not learn anything about x in the course of the interaction. Such proof systems capture natural privacy properties and may be seen as a generalization of the influential concept of randomized encodings (Ishai and Kushilevitz, in: Proceedings 41st annual symposium on foundations of computer science, pp 294–304, 2000; Applebaum et al., in: 45th annual IEEE symposium on foundations of computer science, pp 166–175, 2004; Agrawal et al., in: Halldórsson, Iwama, Kobayashi, Speckmann (eds) Automata, languages, and programming, Springer, Berlin, Heidelberg, pp 1–13, 2015) and as a counterpart to zero-knowledge proofs (Goldwasser et al., in: Symposium on the theory of computing, 1985). We investigate the properties and power of such instance-hiding proofs and show the following: Any language with an IHIP is contained in $${\mathsf {NP/poly}}\cap {\mathsf {coNP/poly}}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mrow> <mml:mi>NP</mml:mi> <mml:mo>/</mml:mo> <mml:mi>poly</mml:mi> </mml:mrow> <mml:mo>∩</mml:mo> <mml:mrow> <mml:mi>coNP</mml:mi> <mml:mo>/</mml:mo> <mml:mi>poly</mml:mi> </mml:mrow> </mml:mrow> </mml:math> . If an average-case hard language has a constant-round IHIP, then infinitely often non-uniform one-way functions exist. There is an oracle with respect to which there is a language that has an IHIP but not an SZK proof. IHIP’s are closed under composition with any efficiently computable function. We further study a stronger version of IHIP (that we call Simulatable IHIP) where the view of the honest prover can be efficiently simulated. For these, we obtain stronger versions of some of the above: Any language with a Simulatable IHIP is contained in $${\textsf{AM}}\cap {\textsf{coAM}}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>AM</mml:mi> <mml:mo>∩</mml:mo> <mml:mi>coAM</mml:mi> </mml:mrow> </mml:math> . If a worst-case hard language has a Simulatable IHIP, then explicit uniform one-way functions exist.
Open access
2 source records
Cryptography and Data Security
Advanced Steganography and Watermarking Techniques
Passwords remain fundamental to user authentication, including handheld devices, wearables, personal computers, and network devices. Privacy concerns have led to the development of new password guidelines and alternatives, yet these have not seen widespread adoption among users. Increasing skepticism towards the service providers has made users reluctant to share sensitive information, including passwords. While current security protocols ensure data protection in transit, assurances regarding the security and privacy of data at rest are often assumed without verification. Traditional best practices for password storage involve hashing, which still requires the original password to be shared as plaintext or as a hash. Each of these methods has its vulnerabilities. For instance, an adversary can sniff network packets to capture the original password or the hash value, potentially compromising the authentication system. To address these issues, we propose a framework for password-based authentication using graph isomorphism as a zero-knowledge proof technique. This framework aims to replace conventional authentication methods and enhance password privacy. The results demonstrate the proposed framework's effectiveness in ensuring secure and private password authentication.
Current mobile payment schemes gather detailed information about purchases customers make. This data can then be used to infer a customer’s spending behaviour, potentially violating their privacy. To tackle this problem, we propose an untraceable mobile payment scheme that strikes a better balance, preserving user privacy while allowing the Third-Party Service Provider (TPSP) to collect necessary information such as card details and transaction amount for regulatory compliance. Our scheme offers untraceability for legitimate users from malicious adversaries and curious TPSPs using cryptographic primitives such as partially blind signatures, zero-knowledge proofs, and identity-based signatures. It also guarantees that only authorised TPSPs can issue valid payment tokens, and even with limited data, the TPSP can still prevent dishonest customers/merchants from double-spending a payment token. We also propose a comprehensive evaluation framework to assess the untraceable payment schemes against seven key criteria such as untraceability, exculpability—merchant double-spending, exculpability—customer double-spending, unforgeability, confidentiality, message authenticity, efficiency, and regulatory compliance. We rigorously benchmark the security and privacy of our proposed payment scheme against this framework and other established schemes. Furthermore, we formally verify these properties using complexity-based analysis and Proverif modelling.
Jing Jiang, Xiaofeng Wang, Qianqian Xing, Jin Tang
Currently, personal information leakage and identity theft have become risks that cannot be ignored. As a robust authentication mechanism, multi-factor authentication (MFA) has gained prominence. However, many existing MFA schemes based on certificate-less public key cryptography amalgamate multiple authentication factors into a single factor for local verification, which fails to achieve independent authentication of each factor and is difficult to resist internal privilege attacks. To address these issues, this paper proposes a certificate-less multi-factor privacy authentication scheme based on elliptic curve cryptography. The proposed scheme divides the full private key into multiple authentication factors and employs the Schnorr zero-knowledge proof technique to independently generate challenge values for each factor, facilitating separate authentication of multiple factors. Notably, this approach eliminates the need to reconstruct the full private key during the authentication process, thereby effectively mitigating the risk of private key leakage.
Open access
Digital Rights Management and Security
Advanced Authentication Protocols Security
Physical Unclonable Functions (PUFs) and Hardware Security
B Yamini Supriya, B. Shubha, Meda Prajwal, C M Vikas · 8 authors
Abstract: The rise of blockchain technology and cryptography has transformed industries by enhancing security, transparency, and trust. This paper provides a comparative analysis of traditional systems and emerging solutions, focusing on the advances in blockchain and cryptography. Key innovations, challenges, and future trends are discussed. The review leverages research from multiple sources, offering a broad perspective on these fields.This paper explores the rapid advancements in blockchain technology and cryptography, comparing traditional systems with cutting-edge solutions. It highlights the evolution of consensus mechanisms, encryption methods, and their impact on scalability, security, and efficiency. By analyzing key innovations such as zero-knowledge proofs and homomorphic encryption, the study offers insights into overcoming existing limitations like high energy consumption and interoperability issues. The paper provides a comparative analysis of emerging solutions against conventional approaches, showcasing their potential to revolutionize industries. Finally, it outlines the challenges that must be addressed for mainstream adoption.
The rapid evolution of Ethereum’s infrastructure calls for innovative mechanisms to enhance scalability, security, and performance. This paper introduces BeamSNARKS, a cutting-edge framework designed to address critical challenges in zero-knowledge proof systems. BeamSNARKS encompasses two groundbreaking innovations: the Dynamic zkSNARKS Generation Optimization Mechanism and the Dynamic SNARKification Technology. The former revolutionizes computational efficiency by dynamically retrieving state data relevant to proof generation, minimizing bandwidth and storage requirements while maintaining validation accuracy. The latter introduces adaptive circuit design and hierarchical proof aggregation to optimize transaction throughput and reduce the computational and financial overhead of Layer 1 submissions. Together, these innovations establish BeamSNARKS as a pivotal advancement in scalable, efficient, and resource-optimized zero-knowledge proof systems. Through comprehensive analysis and targeted experiments, this paper evaluates the performance of BeamSNARKS’s innovations, demonstrating their potential to transform Ethereum’s decentralized ecosystem and lay the groundwork for future high-throughput applications.
Blockchain technology is significant because it makes data sharing between several parties safe, transparent, and effective. Multi-step transactions that require verification and traceability can benefit from Blockchain technology. However, the Blockchain technology too comes with its own vulnerabilities and often Blockchain networks are attacked by attacks like 51% Attack, Eclipse Attack, Sybil Attack, Time jacking Attack, Selfish Mining Attack, Finney Attack, Race Attack and so on. One among those attacks is the Sybil attacks, which are a big threat to the integrity of Blockchain networks since they assist malicious actors to create several identities, potentially overwhelming the system and defeating the very principle of consensus mechanisms. In this paper, we have captured an approach on designing a multi-layered mechanism for identifying Sybil attacks with the integration of behavioral analysis, Blockchain analysis techniques, Zero-Knowledge Proofs (ZKPs), and a robust security architecture for governance and validator selection. The broad idea is to cancel pseudo-anonymity in the Blockchain systems by detecting behavioral patterns, identifying exchange wallets, and mapping inter-wallet relationships. Integration of these approaches with ZKPs assists in improving identity verification while simultaneously maintaining user anonymity. The proposed architecture for security uses community-based governance and adaptive validator selection processes to strengthen the defense against Sybil attacks. Token concentration analysis traces down the distribution of stakes within the network in order to find potential risks due to centralization. Our findings thus conclude that integration of the security framework along with behavior analysis and ZKPs effectively reduces the proliferation of fraudulent identities in the Blockchain networks.
The research on international trade settlement and tracking system based on blockchain technology aims to solve the problems of low efficiency, lack of transparency and data security in the traditional cross-border trade settlement process. By introducing distributed ledger technology, the system can realize real-time tracking of all links of cross-border trade, ensure the immutability of data, and thus improving data transparency and traceability. The application of zero-knowledge proof technology in this system further guarantees the privacy of transaction data, that is, the legality and authenticity of the transaction can be verified without revealing specific sensitive information. This system can not only significantly reduce the trust cost of relying on intermediaries, but also improve settlement efficiency through automated processes. Through simulation analysis, the test results show that the system shows high stability and reliability when processing high-concurrency transactions, especially in protecting data privacy, reducing trust costs and improving settlement efficiency. The precise data analysis of the simulation results further verifies the feasibility and effectiveness of the system in the actual international trade environment, laying a solid foundation for future promotion and application.
Biometric encryption, especially those that are fingerprint-based, plays a dual, important role in identity authentication as well as in privacy protection. Considering the crucial issue of verifying voters in electronic voting systems, ensuring voter privacy and securing sensitive biometric data is considered important. We provide an innovative approach to the integration of fingerprint authentication through biometrics with zero-knowledge proof, thus serving dual purposes of robustness in identity verification while retaining confidentiality at the level of individual voter data. We have a two-node setup architecture in which one is the Prover Node, and the other is the Verifier Node. It will process the fingerprint of the voter to create a key point cryptographic hash and transmit it to the Verifier Node by using ZKP techniques that assure no revealing of sensitive information. This will be further tested rigorously through performance metrics like latency, bandwidth, CPU usage, and memory consumption. Results have shown very low latency times in relationship to both the Prover Node and the Verifier Node, very low bandwidth usage, and efficient use of CPU and memory, which underlines efficiency and capability related to resource management of the system. The integration of biometric data with ZKP not only enhances the security and privacy of electronic voting systems but also proves viable for real-world application. The findings advocate for the broader adoption of such technologies in digital democracy initiatives, potentially transforming future electoral processes.
Biometric Identification and Security
Advanced Steganography and Watermarking Techniques
Baowei Wang, Fengxiao Guo, Yuting Liu, Bin Li · 5 authors
Abstract Voting plays a vital role in democratic societies. Adopting electronic voting can effectively increase voter participation and significantly reduce the financial burden on the organizers. In recent years, with the prevalence of blockchain technology, numerous blockchain-based electronic voting schemes have emerged. Compared with traditional electronic voting schemes, they have more favorable security features. However, existing schemes generally suffer from inefficient voting procedures, limited functionality, and dependence on specific blockchain platforms, making them challenging to deploy in diverse voting scenarios. This paper proposes an efficient and versatile electronic voting scheme on blockchain that addresses these problems using our proposed smart contract-based aggregated blind signature, zero-knowledge proofs, and threshold encryption scheme. In the paper, the scheme’s various features, including security, are analyzed in detail, and the scheme is deployed and tested on the Hyperledger Fabric and Ethereum blockchain platform. The experiment results demonstrate that the voting scheme satisfies the security requirement, and it has outstanding advantages in performance.
Open access
Internet Traffic Analysis and Secure E-voting
Cryptography and Data Security
Advanced Steganography and Watermarking Techniques
Janak Dhokrat, Namita Pulgam, Tabassum Maktum, Vanita Mane
In digital landscape of today’s ongoing world, the imperative for enhanced security in cloud-based data processing is paramount. This paper introduces an innovative framework that seamlessly integrates Homomorphic Encryption and Zero-Knowledge Proofs (ZKPs) to bolster data privacy and confidentiality. This paper explores the technical intricacies, real-world applications, and potential implications of this fusion framework. Homomorphic Encryption empowers computations on encrypted data without compromising privacy, while Zero-Knowledge Proofs offer a mechanism to verify computations without exposing sensitive details. The effectiveness and adaptability of the proposed framework is demonstrated through meticulous analysis and practical deployment in safeguarding cloud-based data processing. The proposed framework marks a significant stride towards creating an environment where data security is unequivocally prioritized.
Verifying a secret element’s (non-)membership status to a private set is challenging yet valuable for access control and verifiable computing applications. On the other hand, blockchain technology, known for its decentralized and tamper-proof nature, allows one to commit any data publicly. This work proposes a zero-knowledge Dual Membership Set Commit (zkDMSC) scheme to bridge the two. Our scheme allows the provers to commit their private set on blockchain and prove a secret element’s membership status to the set in a zero-knowledge manner.We introduce the Perfect Hash Function(PHF) into the field of membership query and use the Merkle tree to construct an efficient zero-knowledge dual membership proof. The prover can combine our dual membership proof with other property proofs of the queried element for different verification requirements. In addition, our proposal does not require a trusted setup and only uses post-quantum cryptographic assumptions. We also implement the proposal and show the performance of our implementation that matches or surpasses the state of the art.
Apurva K. Vangujar, Alia Umrani, Ji‐Jian Chin, Paolo Palmieri
Electronic Auctions (e-auctions) must be secure and reliable in the fast-changing digital world. This paper proposes a Blockchain-Based Cluster Consensus Identity-Based Identification (BCCIBI) scheme to enhance e-auction security and privacy. To establish a secure e-auction environment, the BCCIBI scheme utilises advanced cryptographic primitives such as ElGamal encryption, the Boneh-Lynn-Shacham (BLS) signature scheme, Identity-Based Identification (IBI), Zero-Knowledge (ZK) proof, Commitment scheme, and Non-Interactive ZK proof. In the BCCIBI scheme, bids are secure due to the homomorphic properties of ElGamal encryption, which ensure confidentiality and integrity. The BCCIBI scheme, grounded in the Computational Diffie-Hellman assumption, accelerates multiple bid and bidder verifications by IBI, a crucial operation for clustered blockchains ensuring authentication. Meanwhile, ZK proof authenticates bidders anonymously, safeguarding bidder privacy. Our unique scheme assigns pseudo-identities to participants to provide anonymity and ensure unlinkability. The BCCIBI scheme is resilient against cryptographic attacks in an efficient clustered blockchain scenario using smart contracts, addressing blockchain performance issues. The BCCIBI e-auction scheme is based on timestamps to provide aliveness and records on the blockchain. This paper scrutinises the BCCIBI scheme’s technical foundations and practical implications, laying the groundwork for more secure and transparent e-auction systems. The BCCIBI system advances safe e-auctions by employing a multi-faceted cryptographic technique.
Blockchain Technology Applications and Security
Auction Theory and Applications
Advanced Steganography and Watermarking Techniques