FTP: An Approximate Fast Privacy-Preserving Equality Test Protocol for Authentication in Internet of Things

Privacy-preserving string equality test is a fundamental operation of many algorithms, including privacy-preserving authentication in Internet of Things (IoT). Existing secure equality test schemes can theoretically achieve string equality comparison and preserve the private strings. However, they suffer from heavy computation and communication cost, especially while the strings are of hundreds of bits or longer, which is not suitable for IoT applications. In this paper, we propose an approximate F ast privacy-preserving equality T est P rotocol (FTP), which can securely complete string equality test and achieve high running efficiency at the cost of little accuracy loss. We strictly analyze the accuracy of our proposed scheme and formally prove its security. Additionally, we leverage extensive simulation experiments to evaluate the running cost, which confirms our high efficiency; for instance, our proposed FTP can securely compare two -bit strings within seconds on ordinary laptops.

[1]  Jin Li,et al.  Differentially private Naive Bayes learning over multiple data sources , 2018, Inf. Sci..

[2]  Sheng Zhong,et al.  How to Select Optimal Gateway in Multi-Domain Wireless Networks: Alternative Solutions without Learning , 2013, IEEE Transactions on Wireless Communications.

[3]  Mingwu Zhang,et al.  On the Soundness and Security of Privacy-Preserving SVM for Outsourcing Data Classification , 2018, IEEE Transactions on Dependable and Secure Computing.

[4]  Jian Shen,et al.  Cloud-aided lightweight certificateless authentication protocol with anonymity for wireless body area networks , 2018, J. Netw. Comput. Appl..

[5]  Nagiza F. Samatova,et al.  Solving the maximum duo-preservation string mapping problem with linear programming , 2014, Theor. Comput. Sci..

[6]  Fucai Zhou,et al.  Dynamic Fully Homomorphic encryption-based Merkle Tree for lightweight streaming authenticated data structures , 2018, J. Netw. Comput. Appl..

[7]  Rongxing Lu,et al.  Securing the Internet of Things in a Quantum World , 2017, IEEE Communications Magazine.

[8]  Jian Shen,et al.  Anonymous and Traceable Group Data Sharing in Cloud Computing , 2018, IEEE Transactions on Information Forensics and Security.

[9]  Sheng Zhong,et al.  Privacy preserving growing neural gas over arbitrarily partitioned data , 2014, Neurocomputing.

[10]  Gu Si-yang,et al.  Privacy preserving association rule mining in vertically partitioned data , 2006 .

[11]  Yong Xiang,et al.  Achieving Secure and Efficient Dynamic Searchable Symmetric Encryption over Medical Cloud Data , 2020, IEEE Transactions on Cloud Computing.

[12]  Tao Jiang,et al.  A Lightweight Authenticated Communication Scheme for Smart Grid , 2016, IEEE Sensors Journal.

[13]  Yue Zhang,et al.  Fast Secure Scalar Product Protocol with (almost) Optimal Efficiency , 2015, CollaborateCom.

[14]  Pascal Paillier,et al.  Public-Key Cryptosystems Based on Composite Degree Residuosity Classes , 1999, EUROCRYPT.

[15]  Jianzhong Li,et al.  A QDCT- and SVD-based color image watermarking scheme using an optimized encrypted binary computer-generated hologram , 2016, Soft Computing.

[16]  Jin Li,et al.  Multi-authority fine-grained access control with accountability and its application in cloud , 2018, J. Netw. Comput. Appl..

[17]  Jing Li,et al.  Improved collusion‐resisting secure nearest neighbor query over encrypted data in cloud , 2019, Concurr. Comput. Pract. Exp..

[18]  Xuemin Shen,et al.  An Efficient Merkle-Tree-Based Authentication Scheme for Smart Grid , 2014, IEEE Systems Journal.

[19]  Nitesh V. Chawla,et al.  Reliable medical recommendation systems with patient privacy , 2010, IHI 2010.

[20]  Tong Li,et al.  GMM and CNN Hybrid Method for Short Utterance Speaker Recognition , 2018, IEEE Transactions on Industrial Informatics.

[21]  Bart Goethals,et al.  On Private Scalar Product Computation for Privacy-Preserving Data Mining , 2004, ICISC.

[22]  Hao Wang,et al.  New directly revocable attribute-based encryption scheme and its application in cloud storage environment , 2016, Cluster Computing.

[23]  Yuan-Shun Dai,et al.  Personalized Search Over Encrypted Data With Efficient and Secure Updates in Mobile Clouds , 2018, IEEE Transactions on Emerging Topics in Computing.

[24]  Ying Luo,et al.  Efficient anonymous biometric matching in privacy-aware environments , 2014 .

[25]  Jin Li,et al.  Privacy-preserving Naive Bayes classifiers secure against the substitution-then-comparison attack , 2018, Inf. Sci..

[26]  George K. Karagiannidis,et al.  Secure Multiple Amplify-and-Forward Relaying With Cochannel Interference , 2016, IEEE Journal of Selected Topics in Signal Processing.

[27]  Xiaodong Lin,et al.  Querying in Internet of Things with Privacy Preserving: Challenges, Solutions and Opportunities , 2018, IEEE Network.

[28]  Tomas Toft,et al.  Secure Equality and Greater-Than Tests with Sublinear Online Complexity , 2013, ICALP.

[29]  Tsuyoshi Takagi,et al.  Efficient Secure Primitive for Privacy Preserving Distributed Computations , 2012, IWSEC.

[30]  Nenghai Yu,et al.  Two-Cloud Secure Database for Numeric-Related SQL Range Queries With Privacy Preserving , 2017, IEEE Transactions on Information Forensics and Security.

[31]  Zekeriya Erkin,et al.  Efficient and secure equality tests , 2016, 2016 IEEE International Workshop on Information Forensics and Security (WIFS).

[32]  Yuanzhang Li,et al.  A Covert Channel Over VoLTE via Adjusting Silence Periods , 2018, IEEE Access.

[33]  A. Yao,et al.  Fair exchange with a semi-trusted third party (extended abstract) , 1997, CCS '97.

[34]  Jian Shen,et al.  Secure data uploading scheme for a smart home system , 2018, Inf. Sci..

[35]  Andrew Chi-Chih Yao,et al.  Protocols for secure computations , 1982, FOCS 1982.

[36]  Xuemin Shen,et al.  Enabling Efficient Multi-Keyword Ranked Search Over Encrypted Mobile Cloud Data Through Blind Storage , 2015, IEEE Transactions on Emerging Topics in Computing.

[37]  Jian Shen,et al.  An ID-Based Linearly Homomorphic Signature Scheme and Its Application in Blockchain , 2018, IEEE Access.

[38]  Ronald Cramer,et al.  Introduction to Secure Computation , 1998, Lectures on Data Security.

[39]  Artak Amirbekyan,et al.  A New Efficient Privacy-Preserving Scalar Product Protocol , 2007, AusDM.

[40]  Tsuyoshi Takagi,et al.  Secure and controllable k-NN query over encrypted cloud data with key confidentiality , 2016, J. Parallel Distributed Comput..

[41]  Jian Shen,et al.  A Short Linearly Homomorphic Proxy Signature Scheme , 2018, IEEE Access.

[42]  Kiran S. Balagani,et al.  Secure privacy-preserving protocols for outsourcing continuous authentication of smartphone users with touch data , 2013, 2013 IEEE Sixth International Conference on Biometrics: Theory, Applications and Systems (BTAS).

[43]  Yongdae Kim,et al.  Efficient Cryptographic Primitives for Private Data Mining , 2010, 2010 43rd Hawaii International Conference on System Sciences.

[44]  Hao Yue,et al.  RAAC: Robust and Auditable Access Control With Multiple Attribute Authorities for Public Cloud Storage , 2017, IEEE Transactions on Information Forensics and Security.

[45]  Marina Blanton,et al.  Secure and Efficient Protocols for Iris and Fingerprint Identification , 2011, ESORICS.