Verifiable privacy-preserving single-layer perceptron training scheme in cloud computing

Soft Computing

Volumn 22, Issue 23, 2018, Pages 7719-7732

  Zhang, Xiaoyu ^a   Chen, Xiaofeng ^a   Wang, Jianfeng ^a   Zhan, Zhihui ^b   Li, Jin ^c  

^a XIDIAN UNIVERSITY   (China)

^b SOUTH CHINA UNIVERSITY OF TECHNOLOGY   (China)

^c GUANGZHOU UNIVERSITY   (China)

Author keywords

Batch training; Cloud computing; Privacy preservation; Single layer perceptron; Verifiability

Indexed keywords

ARTIFICIAL INTELLIGENCE; CLOUD COMPUTING; IMAGE PROCESSING; LEARNING SYSTEMS; OUTSOURCING; PATTERN RECOGNITION;

COMPUTATION TECHNIQUES; EXPERIMENTAL EVALUATION; PREDICTIVE ALGORITHMS; PRIVACY PRESERVATION; SECURE TWO-PARTY COMPUTATIONS; SECURITY PROPERTIES; SINGLE LAYER PERCEPTRON; VERIFIABILITY;

DATA PRIVACY;

EID: 85047134011     PISSN: 14327643     EISSN: 14337479     Source Type: Journal    
DOI: 10.1007/s00500-018-3233-7     Document Type: Article

References (55)

1. Abadi M, Chu A, Goodfellow I, McMahan H, Mironov I, Talwar K, Zhang L (2016) Deep learning with differential privacy. In: Proceedings of 2016 ACM SIGSAC Conference on Computer and Communications Security, pp 308–318
2. Adshead A (2014) Data set to grow 10-fold by 2020 as internet of things takes off. ComputerWeekly.com, 9
3. AlZain M, Li A, Soh B, Pardede E (2015) Multi-cloud data management using Shamir’s secret sharing and quantum byzantine agreement schemes. Int J Cloud Appl Comput 5(3):35–52
4. Atallah M, Pantazopoulos K, Rice J, Spafford E (2002) Secure outsourcing of scientific computations. Adv Comput 54:215–272
5. Bansal A, Chen T, Zhong S (2001) Privacy preserving back-propagation neural network learning over arbitrarily partitioned data. Neural Comput Appl 20(1):143–150
6. Bhushan K, Gupta B (2018) A novel approach to defend multimedia flash crowd in cloud environment. Multimed Tools Appl 77(4):4609–4639
7. Chang X, Ma Z, Lin M, Yang Y, Hauptmann A (2017) Feature interaction augmented sparse learning for fast kinect motion detection. IEEE Trans Image Process 26(8):3911–3920
8. Chang X, Ma Z, Yang Y, Zeng Z, Hauptmann A (2017) Bi-level semantic representation analysis for multimedia event detection. IEEE Trans Cybern 47(5):1180–1197
9. Chang X, Yang Y (2017) Semisupervised feature analysis by mining correlations among multiple tasks. IEEE Trans Neural Netw Learn Syst 28(10):2294–2305
10. Chang X, Yu Y, Yang Y, Xing E (2017) Semantic pooling for complex event analysis in untrimmed videos. IEEE Trans Pattern Anal Mach Intell 39(8):1617–1632
11. Chen T, Zhong S (2009) Privacy-preserving backpropagation neural network learning. IEEE Trans Neural Netw 20(10):1554–1564
12. Chen X, Li J, Weng J, Ma J, Lou W (2016) Verifiable computation over large database with incremental updates. IEEE Trans Comput 65(10):3184–3195
13. Chen X, Li J, Huang X, Ma J, Lou W (2015) New publicly verifiable databases with efficient updates. IEEE Trans Dependable Sec Comput 12(5):546–556
14. Chen X, Huang X, Li J, Ma J, Lou W, Wong D (2015) New algorithms for secure outsourcing of large-scale systems of linear equations. IEEE Trans Inf Forensics Secur 10(1):69–78
15. Chen X, Li J, Ma J, Tang Q, Lou W (2014) New algorithms for secure outsourcing of modular exponentiations. IEEE Trans Paral Distr Syst 25(9):2386–2396
16. Chen X, Zhang F, Susilo W, Tian H, Li J, Kim K (2014) Identity-based chameleon hashing and signatures without key exposure. Inf Sci 265:198–210
17. Clifton C, Kantarcioglu M, Vaidya J, Lin X, Zhu M (2002) Tools for privacy preserving distributed data mining. Sigkdd Explor Newsl 4(2):28–34
18. Fakoor R, Ladhak F, Nazi A, Huber M (2013) Using deep learning to enhance cancer diagnosis and classification. InProceedings of the 30th International Conference on Machine Learning, 28
19. Gao CZ, Cheng Q, Li X, Xia SB (2018) Cloud-assisted privacy-preserving profile-matching scheme under multiple keys in mobile social network. Clust Comput. 10.1007/s10586-017-1649-y
20. Gao CZ, Cheng Q, He P, Susilo W, Li J (2018) Privacy-preserving naive bayes classifiers secure against the substitution-then-comparison attack. Inf Sci. 10.1016/j.ins.2018.02.058
21. Goldreich O, Micali S, Wigderson A (1987) How to play any mental game. In: Proceedings of the 19th Annual ACM Symposium on Theory of Computing, pp 218–229
22. Graepel T, Lauter K, Naehrig M (2012) ML zon encrypted data. In: Proceedings of the International Conference on Information Security Cryptol, pp 1–21
23. Gupta B, Agrawal DP, Yamaguchi S (2016) Handbook of research on modern cryptographic solutions for computer and cyber security. IGI Global, Hershey
24. Ibtihal M, Naanani H (2017) Homomorphic encryption as a service for outsourced images in mobile cloud computing environment. Int J Cloud Appl Comput 7(2):27–40
25. Jiang T, Chen X, Wu Q, Ma J, Susilo W, Lou W (2017) Secure and efficient cloud data deduplication with randomized tag. IEEE Trans Inf Foren Secur 12(3):532–543
26. Jiang T, Chen X, Ma J (2016) Public integrity auditing for shared dynamic cloud data with group user revocation. IEEE Trans Comput 65(8):2363–2373
27. Jiang J, Wen S, Yu S, Xiang Y, Zhou W (2018) Rumor source identification in social networks with time-varying topology. IEEE Trans Dependable Sec Comput 15(1):166–179
28. Lei X, Liao X, Huang T, Heriniaina F (2014) Achieving security, robust cheating resistance, and high-efficiency for outsourcing large matrix multiplication computation to a malicious cloud. Inf Sci 280:205–217
29. Li N, Lyu M, Su D, Yang W (2016) Differential privacy: from theory to practice. Synth Lect Inf Secur Priv Trust 8(4):1–138
30. Li J, Li Y, Chen X, Lee P, Lou W (2015) A Hybrid cloud approach for secure authorized deduplication. IEEE Trans Paral Distr Syst 26(5):1206–1216
31. Li J, Chen X, Huang X, Tang S, Xiang Y, Hassan M, Alelaiwi A (2015) Secure distributed deduplication systems with improved reliability. IEEE Trans Comput 64(12):3569–3579
32. Li Z, Nie F, Chang X, Yang Y (2017) Beyond trace ratio: weighted harmonic mean of trace ratios for multiclass discriminant analysis. IEEE Trans Knowl Data Eng 29(10):2100–2110
33. Li H, Lu R, Misic JV (2017) Guest editorial big security challenges in big data era. IEEE Internet Things J 4(2):521–523
34. Li H, Yang Y, Luan TH, Liang X, Zhou L, Shen X (2016) Enabling fine-grained multi-keyword search supporting classified sub-dictionaries over encrypted cloud data. IEEE Trans Dependable Sec Comput 13(3):312–325
35. Li T, Li J, Liu Z, Li P, Jia C (2018) Differentially private naive bayes learning over multiple data sources. Inf Sci 444:89–104
36. Li P, Li J, Huang Z, Li T, Gao CZ, Yiu SM, Chen K (2017) Multi-key privacy-preserving deep learning in cloud computing. Future Gener Comput Syst 74:76–85
37. Lin Q, Yan H, Huang Z, Chen W, Shen J, Tang Y (2018) An ID-based linearly homomorphic signature scheme and its application in blockchain. IEEE Access. 10.1109/ACCESS.2018.2809426
38. Liu J, Juuti M, Lu Y, Asokan N (2017) Oblivious neural network predictions via minionn transformations. In: Proceedings of the 2017 ACM SIGSAC Conference on Conference Computer Communications Security, pp 619–631
39. Malek B, Miri A (2006) Secure dot-product protocol using trace functionsm. In: Information Theory, 2006 IEEE International Symposium, pp 927–931
40. Michalski R, Carbonell J, Mitchell T (2013) Machine learning: an artificial intelligence approach. Springer, Berlin
41. Mohassel P, Zhang Y (2017) SecureML: A System for scalable privacy-preserving machine learning. In: 2017 IEEE Symposium on Security and Privacy, pp 19–38
42. Nikolaenko V, Weinsberg U, Ioannidis S, Joye M, Boneh D, Taft N (2013) Privacy-preserving ridge regression on hundreds of millions of records. In: Proceedings of the Security and Privacy, pp 334–348
43. Ohrimenko O, Schuster F, Fournet C, Mehta A, Nowozin S, Vaswani K, Costa M (2016) Oblivious multi-party machine learning on trusted processors. In: USENIX Security Symposium, pp 619–636
44. Shynk J (1990) Performance surfaces of a single-layer perceptron. IEEE Trans Neural Netw 1:268–274
45. Tai R, Ma J, Zhao Y, Chow S (2017) Privacy-preserving decision trees evaluation via linear functions. In: Proceedings of European Symposium on Research in Computer Security, pp 494–512
46. Wang G, Lu R, Huang C (2015) PSLP: Privacy-preserving single-layer perceptron learning for e-Healthcare. In: Proceedings of information, communications and signal processing (ICICS), pp 1–5
47. Wang J, Chen X, Huang X, You I, Xiang Y (2015) Verifiable auditing for outsourced database in cloud computing. IEEE Trans Comput 64(11):3293–3303
48. Wen S, Jiang J, Xiang Y, Yu S, Zhou W, Jia W (2014) To shut them up or to clarify: restraining the spread of rumors in online social networks. IEEE Trans Parallel Distrib Syst 25(12):3306–3316
49. Yu B, Xu Z (2008) A comparative study for content-based dynamic spam classification using four machine learning algorithms. Knowl Based Syst 21(4):355–362
50. Yu L, Wang S, Lai K (2008) Credit risk assessment with a multistage neural network ensemble learning approach. Expert Syst Appl 34(2):1434–1444
51. Zhang C, Zhu L, Xu C, Lu R (2018) PPDP: an efficient and privacy-preserving disease prediction scheme in cloud-based e-Healthcare system. Future Gener Comput Syst 79:16–25
52. Zhang T, Zhu Q (2017) Dynamic differential privacy for ADMM-based distributed classification learning. IEEE Trans Inf Foren Secur 12(1):172–187
53. Zhang X, Jiang T, Li KC, Chen X (2017) New publicly verifiable computation for batch matrix multiplication. In: Proceedings of the GPC’17, pp 53–65
54. Zhang X, Jiang T, Li KC, Castiglione A, Chen X (2017) New publicly verifiable computation for batch matrix multiplication. Inf Sci. 10.1016/j.ins.2017.11.063
55. Zheng Q, Wang X, Khan M, Zhang W, Gupta B, Guo W (2017) A lightweight authentication encryption based on chaotic SCML for railway cloud service. IEEE Access 6:711–722