信息网络安全 ›› 2022, Vol. 22 ›› Issue (5): 37-45.doi: 10.3969/j.issn.1671-1122.2022.05.005

• 技术研究 • 上一篇    下一篇

基于模拟退火和粒子群混合改进算法的数据库水印技术

孔嘉琪1,2, 王利明1(), 葛晓雪1,2   

  1. 1.中国科学院信息工程研究所,北京 100093
    2.中国科学院大学网络空间安全学院,北京 100049
  • 收稿日期:2022-02-10 出版日期:2022-05-10 发布日期:2022-06-02
  • 通讯作者: 王利明 E-mail:wangliming@iie.ac.cn
  • 作者简介:孔嘉琪(1997—),女,山西,硕士研究生,主要研究方向为数据安全|王利明(1978—),男,北京,正高级工程师,博士,主要研究方向为云计算安全、网络安全、大数据安全、5G安全、区块链安全|葛晓雪(1997—),女,河北,硕士研究生,主要研究方向为数据安全
  • 基金资助:
    国家重点研发计划(2017YFB0801900)

Simulated Annealing and Particle Swarm Enhanced Relational Database Watermark

KONG Jiaqi1,2, WANG Liming1(), GE Xiaoxue1,2   

  1. 1. Institute of Information Engineering, University of Chinese Academy of Sciences, Beijing 100093, China
    2. School of Cyber Security, University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2022-02-10 Online:2022-05-10 Published:2022-06-02
  • Contact: WANG Liming E-mail:wangliming@iie.ac.cn

摘要:

近年来,随着数据开放程度的提升,数据库水印成为了一种越来越重要的安全手段。数据库水印可以对泄露数据进行版权认证和溯源追责,保障数据的安全。现有的数据库水印嵌入方案存在水印容量低、抗攻击的鲁棒性较弱等问题,无法对数据进行有效保护。文章提出了PADEW数据库水印方案,PADEW使用基于模拟退火改进的粒子群算法寻找更好的水印嵌入位置,以解决一些现有方案容易陷入局部最优解的问题,从而提高水印嵌入容量并降低水印嵌入引起的失真。PADEW提出了基于属性重要度的带权损失函数,以解决现有方案在抗属性维度攻击时鲁棒性较弱的问题。文章使用水印嵌入容量、平均失真和面对多种攻击时的水印检测率评估PADEW的性能,并和现有的一些方案进行对比。实验表明,PADEW能在提高水印容量的同时,降低水印嵌入引起的失真。并且,PADEW有较强的抗攻击的鲁棒性,包括元组删除攻击、元组添加攻击、比特翻转攻击和属性删除攻击。尤其在面对50%的属性删除攻击时,水印检测率仍然高达81%。

关键词: 数据库水印, 模拟退火算法, 粒子群算法, 水印容量, 抗攻击

Abstract:

In recent years, with the improvement of data openness, database watermark has become increasingly important in database security. Database watermark can carry out copyright authentication and traceability of leaked data to ensure data security. However, existing watermark models have low watermark capacity and weak anti-attack robustness. This paper proposes a new database watermark method PADEW. PADEW used an improved particle swarm algorithm based on simulated annealing to avoid falling into the local optimal solution. This enhancement found better watermark embedding positions, thereby increased the watermark capacity and reducing distortion. In addition, this research proposed to use a weighted loss function based on attribute importance to improve the robustness against attribute dimension attacks. The experiments employed watermark capacity, average distortion, and watermark detection rate against multiple attacks to evaluate the performance of PADEW. Experiment results show that PADEW can reduce the distortion caused by watermark embedding while providing more watermark capacity. In addition, PADEW has stronger robustness against various attacks, including tuple deletion attacks, tuple addition attacks, bit flip attacks, and attribute deletion attacks. Especially in the face of 50% attribute deletion attacks, the watermark detection rate is still as high as 81%.

Key words: database watermark, simulated annealing algorithm, particle swarm algorithm, watermark capacity, anti-attack

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