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  • Open Access


    Secure Multi-Party Quantum Summation Based on Quantum Homomorphic Encryption

    Gang Xu1,2, Fan Yun1, Xiu-Bo Chen3,*, Shiyuan Xu1, Jingzhong Wang1, Tao Shang4, Yan Chang5, Mianxiong Dong6

    Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 531-541, 2022, DOI:10.32604/iasc.2022.028264

    Abstract Secure multi-party computation has been playing a fundamental role in terms of classical cryptography. Quantum homomorphic encryption (QHE) could compute the encrypted data without decryption. At present, most protocols use a semi-honest third party (TP) to protect participants’ secrets. We use a quantum homomorphic encryption scheme instead of TP to protect the privacy of parties. Based on quantum homomorphic encryption, a secure multi-party quantum summation scheme is proposed in which N participants can delegate a server with strong quantum computing power to assist computation. By delegating the computation and key update processes to a server and a semi-honest key center,… More >

  • Open Access


    Research on Privacy Preserving Data Mining

    Pingshui Wang1,*, Tao Chen1,2, Zecheng Wang1

    Journal of Information Hiding and Privacy Protection, Vol.1, No.2, pp. 61-68, 2019, DOI:10.32604/jihpp.2019.05943

    Abstract In recent years, with the explosive development in Internet, data storage and data processing technologies, privacy preservation has been one of the greater concerns in data mining. A number of methods and techniques have been developed for privacy preserving data mining. This paper provided a wide survey of different privacy preserving data mining algorithms and analyzed the representative techniques for privacy preservation. The existing problems and directions for future research are also discussed. More >

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