| 对等网络主动型恶意代码与免疫疫苗的对抗传播模型 |
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| 引用本文： | 徐小龙,杨庚,熊婧夷. 对等网络主动型恶意代码与免疫疫苗的对抗传播模型[J]. 北京理工大学学报, 2013, 33(6): 605-611 |
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| 作者姓名： | 徐小龙 杨庚 熊婧夷 |
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| 作者单位： | 南京邮电大学计算机学院,江苏,南京210003;南京大学计算机软件新技术国家重点实验室,江苏,南京210046;江苏省无线传感网高技术研究重点实验室,江苏,南京 210003;南京邮电大学计算机学院,江苏,南京210003 |
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| 基金项目： | 国家"九七三"计划项目(2011CB302903);国家自然科学基金资助项目(61202004,61272084,61202353);国家教育部高等学校博士学科点专项科研基金资助课题(20093223120001);中国博士后科学基金资助项目(2012T50514,2011M500095);江苏省自然科学基金资助项目(BK2011754,BK2009426);江苏省博士后科研资助计划资助项目(1102103C); 江苏省高校自然科学研究计划资助项目(12KJB520007);江苏省高校自然科学研究计划重大项目(11KJA520002) |
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| 摘 要： | 通过深入分析P2P网络中的主动型恶意代码的特征,提出一种适合于P2P网络环境的主动型恶意代码与免疫疫苗的对抗传播模型. 模型根据Peer节点受主动型恶意代码及免疫疫苗的双重影响情况将节点细分为易感染、已感染、已免疫和失效这4种典型状态,并指出了节点在不同状态之间的转换规律. 对所提出对抗传播模型及其相关参数展开细致的仿真实验,实验结果说明所提出的模型与实际情况相符,证明了模型的正确合理性.
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| 关 键 词： | 对等网络 恶意代码 主动传播 数字免疫 反病毒 |
| 收稿时间： | 2011-12-24 |
Model of Proactive Malicious Code Propagation and Vaccine Contradiction in P2P Network |
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| XU Xiao-long,YANG Geng and XIONG Jing-yi. Model of Proactive Malicious Code Propagation and Vaccine Contradiction in P2P Network[J]. Journal of Beijing Institute of Technology(Natural Science Edition), 2013, 33(6): 605-611 |
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| Authors: | XU Xiao-long YANG Geng XIONG Jing-yi |
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| Affiliation: | 1.College of Computer, Nanjing University of Posts and Telecommunications, Jiangsu, Nanjing 210003, China;State Key Laboratory for Novel Software Technology, Nanjing University, Jiangsu, Nanjing 210046, China2.Jiangsu High Technology Research Key Laboratory for Wireless Sensor Networks, Jiangsu, Nanjing 210003, China3.College of Computer, Nanjing University of Posts and Telecommunications, Jiangsu, Nanjing 210003, China |
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| Abstract: | A new contradiction and propagation model of proactive malicious code and vaccine in P2P network is proposed based on in-depth analysis of the active malicious code characteristics in P2P network. Considering two factors of active malicious codes and vaccines, the model differentiates peers into 4 kinds of status, such as susceptible status, infected status, healed status and disabled status. The node conversion law between different states is also pointed out. The proposed model and its related parameters have been tested by simulation experiments. Experimental results indicate that the proposed model is in accordance with the actual situations and its correctness and rationality is verified. |
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| Keywords: | peer-to-peer network malicious code active propagation digital immune anti-virus |
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