TY - JOUR
T1 - Collusion-Resilient and Maliciously Secure Cloud-Assisted Two-Party Computation Scheme in Mobile Cloud Computing
AU - Liu, Zhusen
AU - Wang, Weizheng
AU - Ye, Yutong
AU - Min, Nan
AU - Cao, Zhenfu
AU - Zhou, Lu
AU - Liu, Zhe
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - — Mobile smart devices provide convenience for people’s daily life with the users’ data, but also put consumers’ privacy and security at risk. Privacy-enhancing technologies (PETs), including secure two/multi-party computation, have emerged as solutions to alleviate privacy concerns in mobile cloud computing (MCC). However, cloud servers, although capable of easing the burden of PETs, introduce potential risks by being malicious and colluding with computation parties to access additional private data. In this article, we propose a privacy-preserving cloud-assisted two-party computation scheme and the optimized variant with the half-gate method in MCC with a higher security level. To the best of our knowledge, the work is the first cloud-assisted two-party computation, designed to resist all collusion attacks in the malicious model. This is achieved by distributing circuit generation tasks among the parties and separately processing private inputs based on authenticated garbled circuits. Security analysis demonstrates that our scheme ensures correctness and fairness. Performance comparison results indicate the efficiency of our work, even with stronger security against malicious servers and any collusion attack. It outperforms the state-of-the-art scheme, particularly in terms of the server’s communication cost in the online phase, achieving a remarkable reduction of approximately 96.8%.
AB - — Mobile smart devices provide convenience for people’s daily life with the users’ data, but also put consumers’ privacy and security at risk. Privacy-enhancing technologies (PETs), including secure two/multi-party computation, have emerged as solutions to alleviate privacy concerns in mobile cloud computing (MCC). However, cloud servers, although capable of easing the burden of PETs, introduce potential risks by being malicious and colluding with computation parties to access additional private data. In this article, we propose a privacy-preserving cloud-assisted two-party computation scheme and the optimized variant with the half-gate method in MCC with a higher security level. To the best of our knowledge, the work is the first cloud-assisted two-party computation, designed to resist all collusion attacks in the malicious model. This is achieved by distributing circuit generation tasks among the parties and separately processing private inputs based on authenticated garbled circuits. Security analysis demonstrates that our scheme ensures correctness and fairness. Performance comparison results indicate the efficiency of our work, even with stronger security against malicious servers and any collusion attack. It outperforms the state-of-the-art scheme, particularly in terms of the server’s communication cost in the online phase, achieving a remarkable reduction of approximately 96.8%.
KW - Cloud-assisted computation
KW - collusion resilience
KW - garbled circuit
KW - malicious model
KW - mobile cloud computing
KW - secure two-party computation
UR - https://www.scopus.com/pages/publications/85198712041
U2 - 10.1109/TIFS.2024.3428410
DO - 10.1109/TIFS.2024.3428410
M3 - 文章
AN - SCOPUS:85198712041
SN - 1556-6013
VL - 19
SP - 7019
EP - 7032
JO - IEEE Transactions on Information Forensics and Security
JF - IEEE Transactions on Information Forensics and Security
ER -