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山东大学学报（理学版） ›› 2018, Vol. 53 ›› Issue (7): 65-74.doi: 10.6040/j.issn.1671-9352.2.2017.304

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基于量子辐射场的大数据安全存储寻址算法

刘利钊1,2,于佳平2,刘健3,李俊祎2,4,韩哨兵5,许华荣1,林怀钏6,朱顺痣1*   

  1. 1. 厦门理工学院计算机与信息工程学院, 福建 厦门 361024;2. 快速制造国家工程研究中心厦门研发中心, 福建 厦门 3610242;3. 南京理工大学经济管理学院, 江苏 南京 210094;4. 北京百度科技有限公司, 北京 100085;5. 厦门市经济和信息化局, 福建 厦门 361005;6. 厦门市发改委重点项目处, 福建 厦门 361005
  • 收稿日期:2017-08-28 出版日期:2018-07-20 发布日期:2018-07-03
  • 作者简介:刘利钊(1983— ),博士,副教授,硕士生导师,研究方向为信息安全、大数据、量子尺度空间.E-mail:493107149@qq.com*通信作者简介:朱顺痣(1973—),博士,教授,硕士生导师,研究方向为大数据. E-mail: szzhu@xmut.edu.cn
  • 基金资助:
    国家自然科学基金资助项目(61503316,61273290,61373147);福建省自然科学基金资助项目(2013HZ0004-1);福建省科技厅A类计划项目(JA13238);厦门市科技计划项目(2014S0048,3502Z20123037);中国博士后科学基金资助项目(2013M530261)

Secure storage addressing algorithm for large data based on quantum radiation field

LIU Li-zhao1,2, YU Jia-ping2, LIU Jian3, LI Jun-yi2,4, HAN Shao-bing5, XU Hua-rong1, LIN Huai-chuan6, ZHU Shun-zhi1*   

  1. 1. College of Computer and Information Engineering, Xiamen University of Technology, Xiamen 361024, Fujian, China;
    2. National Engineering Research Center of Rapid Manufacturing Research and Development Center in Xiamen, Xiamen 3610242, Fujian, China;
    3. School of Economics and Management, Nanjing University of Science and Technology, Nanjing 210094, Jiangsu, China;
    4. Beijing Baidu Technology Co. Ltd., Beijing 100085;
    5. Xiamen Municipal Bureau of Economic and Information Technology, Xiamen 361005, Fujian, China;
    6. Xiamen Development and Reform Commission Emphases Project Office, Xiamen 361005, Fujian, China
  • Received:2017-08-28 Online:2018-07-20 Published:2018-07-03

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摘要： 大数据存储过程面临着与日俱增的各种威胁,而传统数据存储算法难以有效应对这些新型威胁。以量子力学和量子遗传的关系为基础,构建量子辐射与量子遗传迭代的、双向可逆过程的数学函数和计算机程序,为流数据的大规模量子安全存储构建软件基础环境。在量子力学和量子遗传的映射关系下,将量子染色体的定义和交互作用通过量子比特和量子旋转门的计算实现,将量子染色体的交互通过量子引力作用和量子斥力作用的交互实现,将量子染色体动态过程的主要衡量指标通过引力和斥力的叠加态来计算产生。用量子引力和斥力来引导流数据的动态存储寻址、出入栈过程与路径,进而将大数据存储过程双向映射为量子辐射场和量子空间域问题,得到安全存储路径与存储地址。

关键词: 存储寻址, 量子旋转门, 斥力, 量子辐射, 引力, 大数据安全, 量子比特

Abstract: Big data storage processes are faced with increasing threats, and traditional data storage algorithms are difficult to effectively deal with these new threats. Beginning with the relationship between quantum mechanics and quantum genetic, based on that the reversible process of mathematical functions and a computer program are built as the software environment for large-scale quantum secure storage of data streams, they are constructed of iterative quantum radiation and quantum genetic. Then, under the mapping relationship between quantum mechanics and quantum inheritance, the definition and interaction of quantum chromosomes are realized through the calculation of quantum bits and quantum revolving gates. The interaction of quantum chromosome is achieved through the interaction of quantum attraction and quantum repulsion, and quantum is realized. The main measure of chromosomes dynamic processes is calculated by the superposition of gravitational and repulsive forces. Then use the quantum gravity and repulsion to guide the dynamic storage addressing of the stream date and the stacking process and path. Then the bi-level date storage process is bi-directionally mapped to the quantum radiation field and quantum space domain problems, and the secure storage path and storage address are obtained.

Key words: quantum radiation, quantum revolving gates, storage addressing, large data security, repulsion, qubit, gravitation

中图分类号: 

  • TP301
[1] 刘利钊,洪江水,刘莉莉,等.面向大数据图像处理的尺度空间挖掘算法及应用[J].上海交通大学学报,2015,49(11):1731-1735. LIU Lizhao, HONG Jiangshui, LIU Lili, et al. Scale space mining algorithm for large data image processing and its application[J]. Journal of Shanghai Jiaotong University, 2015, 49(11):1731-1735.
[2] 严霄凤,张德馨.大数据研究[J].计算机技术与发展, 2013, 23(4):168-172. YAN Xiaofeng, ZHANG Dexin. Big data research [J]. Computer Technology and Development, 2013, 23(4): 168-172.
[3] 孟小峰,慈祥. 大数据管理:概念、技术与挑战[J].计算机研究与发展, 2013,50(1):146-169. MENG Xiaofeng, CI Xiang. Big data management: concepts, technology and challenges [J]. Computer Research and Development, 2013, 50(1):146-169.
[4] LIU Lizhao, LIU Jian. Design and implementation of verification code identificationbased on anisotropic heat kernel[J]. China Communications, 2016, 13(1):100-112.
[5] 王珊, 王会举, 覃雄派, 等. 架构大数据: 挑战、现状与展望[J].计算机学报,2011,34(10):1741-1752. WANG Shan, WAND Huiju, QIN Xiongpai, et al. Architecture big data: challenges, current situation and prospects [J]. Chinese Journal of Computers, 2011, 34(10):1741-1752.
[6] TANG Y, LEE P P, LUI J C, et al. Secure overlay cloud storage with access control and assured deletion[J]. IEEE Transactions on Dependable and Secure Computing, 2012, 9(6):903-916.
[7] TANG Y, LEE P P, LUI J, et al. Secure overlay cloud storage with file assured deletion[M] //JAJODIA S, ZHOU J. Security and Privacy in Communication Networks, Vol. 50 of Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering. Berlin: Springer, 2010:380-397.
[8] LEI Zhen, LIAO Shengcai, PIETIKÄINEN M, et al. Face recognition by exploring information jointly in space, scale and orientation[J]. IEEE Transactions on Image Processing, 2011, 20(1):247-256.
[9] 冯登国, 张敏, 张妍,等. 云计算安全研究[J]. 软件学报, 2011, 22(1): 71-83. FENG Dengguo, ZHANG Min, ZHANG Yan, et al. Cloud computing security[J]. Software Journal, 2011, 22(1): 71-83.
[10] LIU Lizhao, LIU Jian, ZHANG Xiaoyun, et al. Multi-embed nonlinear scale space for image trust root generation[J]. China Communications, 2016, 13(11):170-179.
[11] LIU Lizhao, LIU Jian, ZHU Shunzhi, et al. Gridservices trusted authentication algorithm based on image trustedroot in scale space[J]. Wuhan Univerisity Journal of Natural Sciences,2012, 17(6): 521-530.
[12] HAN K H, KIM J H. Quantum-inspired evolutionary algorithm for a class of combinatorial optimization[J]. IEEE Transactions on Evolutionary Computation, 2002(6):580-593.
[13] QIN A K, HUANG V L, SUGANTHAN P N, et al. Differential evolution algorithm with strategy adaptation for global numerical optimization[J]. IEEE Transactions on Evolutionary Computation, 2009(2):398-417.
[14] JIN Y, OLHOFER M, SENDHOFF B. A framework for evolutionary optimization with approximate fitness functions[J]. IEEE Transactions on Evolutionary Computation, 2002(5):481-494.
[15] 王宇平, 李英华. 求解TSP的量子遗传算法[J]. 计算机学报, 2007, 30(5):748-755. WANG Yuping, LI Yinghua. Quantum genetic algorithm for TSP[J]. Chinese Journal of Computers, 2007, 30(5): 748-755.
[16] 刘芳, 王爽, 柳莹莹,等. 基于改进量子旋转门的量子进化数据聚类[J]. 电子学报, 2011, 39(9):2008-2013. LIU Fang, WANG Shuang, LIU Yingying, et al. Based on the quantum evolutionary data clustering[J]. Electronic Journal, 2011, 39(9):2008-2013.
[17] RAY T, LIEW K M. Society and civilization: an optimization algorithm based on the simulation of social behavior[J]. IEEE Transactions on Evolutionary Computation, 2003(4):386-396.
[18] 杨俊安, 庄镇泉, 史亮. 多宇宙并行量子遗传算法[J]. 电子学报, 2004, 32(6):923-928. YANG Junan, ZHUANG Zhenquan, SHI Liang. Multi-universe parallel quantum genetic algorithm[J]. Acta Electronic, 2004, 32(6): 923-928.
[19] FARMANI R, WRIGHT J A. Self-adaptive fitness formulation for constrained optimization[J]. IEEE Transactions on Evolutionary Computation, 2003(5):445-455.
[20] 陈辉, 张家树, 张超. 实数编码混沌量子遗传算法[J]. 控制与决策, 2005, 20(11):1300-1303. CHEN Hui, ZHANG Jiashu, ZHANG Chao. Real-coded chaotic quantum genetic algorithm[J]. Control and Decision, 2005, 20(11): 1300-1303.
[21] 张莎莎, 谷延锋, 张钧萍,等. 一种基于量子遗传算法的红外图像分割方法[J]. 哈尔滨工业大学学报, 2007, 39(9):1427-1430. ZHANG Shasha, GU Yanfeng, ZHANG Junping, et al. An infrared image segmentation method based on quantum genetic algorithm [J]. Journal of Harbin Institute of Technology, 2007, 39(9):1427-1430.
[22] DEB K, PRATAP A, AGARWAL S, et al. A fast and elitist multiobjective genetic algorithm: NSGA-II[J]. IEEE Transactions on Evolutionary Computation, 2002(2):182-197.
[23] RAYMER M L, PUNCH W F, GOODMAN E D, et al. Dimensionality reduction using genetic algorithms[J]. IEEE Transactions on Evolutionary Computation, 2002(2):164-171.
[24] ZHAO Z, PENG Z, ZHENG S, et al. Cognitive radio spectrum allocation using evolutionary algorithms[J]. IEEE Transactions on Wireless Communications, 2009, 8(9):4421-4425.
[25] JIN Y, BRANKE J. Evolutionary optimization in uncertain environments—a survey[J]. IEEE Transactions on Evolutionary Computation, 2005(3):303-317.
[26] LEUNG Y W, WANG Y. An orthogonal genetic algorithm with quantization for global numerical optimization[J]. IEEE Transactions on Evolutionary Computation, 2002(1):41-53.
[27] CHANG W A, RAMAKRISHNA R S. A genetic algorithm for shortest path routing problem and the sizing of populations[J]. IEEE Transactions on Evolutionary Computation, 2003(6):566-579.
[28] REEVES C R. Genetic algorithms and grouping problems[J]. IEEE Transactions on Evolutionary Computation, 2001(3):297-298.
[29] GEAMBASU R, KOHNO T, LEVY A A, et al. Vanish:increasing data privacy with self-destructing data[C] // Proceedings of the 18th USENIX Security Symposium.[S.l.] : [s.n.] , 2009:299-316.
[30] WOLCHOK S, HOFMANN O S, HENINGER N, et al. Defeating vanish with low-cost sybil attacks against large dhts[C] //17th Network and Distributed System Security Symposium. [S.l.] :[s.n.] , 2010.
[31] WANG Guojun, YUE Fengshun, LIU Qin, A secure self-destructing scheme for electronic data[J].Journal of Computer and System Sciences, 2013, 79(2):279-290.
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