Aug 2026· Electronics· Vol 15, pp. 3837· 0 citations· 17 references
TL;DR
PrivFuzz allows organizations and individuals to collaborate and receive rewards while keeping fuzzing seeds confidential and enabling controlled encrypted seed reuse among untrusted fuzzing nodes, and the key idea is to combine trusted execution environments (TEEs) with blockchain-based smart contracts to support confidentiality and fair reward settlement.
Abstract
Cyber–physical systems (CPSs) increasingly rely on complex software components whose vulnerabilities may affect both digital services and physical processes. Fuzzing is a practical technique for discovering such vulnerabilities in CPS-facing parsers, protocol handlers, and edge services. Distributed fuzzing improves throughput, but outsourcing fuzzing tasks to multiple untrusted nodes introduces privacy risks: valuable seeds, especially crash-triggering samples, may reveal vulnerability information before affected users are protected. In this paper, we propose PrivFuzz, a privacy-preserving collaborative fuzzing framework. PrivFuzz allows organizations and individuals to collaborate and receive rewards while keeping fuzzing seeds confidential and enabling controlled encrypted seed reuse among untrusted fuzzing nodes. The key idea is to combine trusted execution environments (TEEs) with blockchain-based smart contracts to support confidentiality and fair reward settlement. We give game-based definitions and reduction-style arguments for seed confidentiality, worker soundness, outsourcer atomicity, and duplicate-claim resistance under an attested execution model. We implement a PrivFuzz prototype and evaluate it on four open-source parsing targets. Separately, native AFL++ sanity checks suggest that CPS-facing industrial protocol parsers such as Modbus and OPC UA fall within the same fuzzable target domain. Demonstrating end-to-end PrivFuzz on CPS control programs is left as future work. Using PrivFuzz, we discovered nine bugs and reported them to the developers.
This paper introduces a novel PPCC method based on post-quantum fully homomorphic encryption that enables token-based replay fitness computation entirely in the encrypted domain using post-quantum FHE, and is the first method that enables token-based replay fitness computation entirely in the encrypted domain using post-quantum FHE.
Hector A. De la Fuente-Anaya, Miguel Morales-Sandoval, H. Marín-Castro· IEEE Access· 0 citations
This paper introduces Data Communities as a novel paradigm for privacy-preserving, blockchain-enabled cooperative digital infrastructures, formalized within the Cooperative Digital Infrastructure (CDI) framework and formalizes privacy guarantees through an adversarial model encompassing classical, quantum, insider, and governance-level threats.
Security analysis demonstrates that SecuAudit can effectively resist data forgery, metadata tampering, and sub-threshold collusion attacks under the defined threat model, and establishes a feasible framework for secure data circulation under the evaluated deployment assumptions.
Yufa Shi, Jiaxing Hu, Lipeng Wang et al.· Computers, Materials & C...· 0 citations
IoT sensor deployments increasingly export measurement streams to edge gateways and content-addressed storage such as IPFS, but access control decisions must be enforced without disclosing sensor owner policies, requester attributes, or stale data versions. Existing blockchain, CP-ABE, and zero-knowledge approaches reduce parts of this leakage, yet they can still expose public policy structure, accept stale Merkle proofs after sensor stream updates, overload provers when policies grow, or leave IPFS gateways vulnerable to bandwidth abuse. This paper proposes zk-Guard-R, a policy-hidden and replay-safe zk-SNARK access control framework for privacy-preserving IoT sensor data sharing. zk-Guard-R replaces public sparse policy matrices with MiMC-Merkle policy commitments verified inside the proof, separates long-lived logical sensor policy roots from frequently updated physical IPFS data roots, binds every proof to an on-chain nonce, and decouples attribute possession from policy interpretation through a bounded stack-based policy interpreter. Numeric sensor-access predicates are represented through committed values and range check gadgets, while an off-chain verification gateway couples accepted proofs with payment channel vouchers before releasing encrypted IPFS chunks. The design contribution is separated from the measured prototype: the full protocol specifies a bounded policy interpreter, whereas the present gnark prototype evaluates the core committed policy, committed attribute, range check, data root, nonce, Solidity verifier, and gateway-metering mechanisms. We implement a gnark BN254/Groth16 research prototype and benchmark it against a matrix-public zk-Guard prototype, a blockchain ABAC baseline, an IoT token/HMAC baseline, and a CP-ABE-style cryptographic-work proxy. For 128 attributes, the zk-Guard-R prototype with MiMC-Merkle commitments uses 425,574 R1CS constraints, generates proofs in 3.12 s, verifies in 0.73 ms, and uses 641 MB peak Go heap allocation. A three-run repeat of the 128-attribute configuration gives a proof-generation mean of 2.80 s with a 0.54 s standard deviation on the same local host, illustrating the runtime variability of prover measurements. We also deploy the generated Solidity verifier on a local Anvil EVM and measure 241,942 gas for a successful verification transaction, and we evaluate a local Kubo/IPFS gateway under valid, replayed, and voucher-limited flood requests. The results show that zk-Guard-R shifts substantial but measurable work to the prover while improving policy confidentiality, freshness, and gateway metering for IPFS-backed IoT sensor data sharing.
Huiying Hou, Yucong Ma, Zisu Zhao et al.· Italian National Conference...· 0 citations
The transition toward the Web3 ecosystem shifts digital identity management from centralized authorities toward user-controlled decentralized infrastructures. However, blockchain-based academic credentials implemented through Soulbound Tokens (SBTs) may expose privacy risks because credential activities remain publicly observable. This study presents an academic authentication framework that integrates the ERC-5192 Soulbound Token standard with Groth16 zk-SNARKs implemented using Circom, SnarkJS, and client-side WebAssembly (WASM). The framework combines Merkle-tree membership validation and a nullifier mechanism to support privacy-preserving credential verification and replay resistance. Experimental evaluation was conducted under controlled conditions using a Samsung Galaxy A24 mobile device and the Ethereum Sepolia Testnet. Across 50 authentication trials, the prototype achieved a 100% authentication success rate. The measured mean authentication latency was 6.30 s, consisting of wallet connection (0.50 s), witness generation (1.00 s), proof generation (4.59 s), and smart contract verification (0.21 s). These results demonstrate the feasibility of browser-based privacy-preserving academic credential verification under the evaluated experimental configuration, while broader device and deployment validation remain necessary for large-scale implementation.
