中国科学院软件研究所机构知识库
Advanced  
ISCAS OpenIR  > 信息安全国家重点实验室  > 学位论文
学科主题: 计算机科学技术基础学科::数据安全与计算机安全
题名:
P2P信任模型中的共谋团体识别技术研究
作者: 苗光胜
答辩日期: 2010-05-31
导师: 冯登国
专业: 信息安全
授予单位: 中国科学院研究生院
授予地点: 北京
学位: 博士
关键词: P2P网络 ; 信任模型 ; 共谋团体 ; 共谋
其他题名: Research on Collusion Detecting in P2P Trust Model
摘要: 随着P2P网络的迅猛发展,P2P网络的安全性问题受到越来越多的关注。由于P2P网络先天的开放性、匿名性等特点,信任问题已经成为制约P2P网络发展的瓶颈。信任模型的出现为P2P网络提供了一套有效的安全机制,理论和实践证明P2P信任模型在提高P2P网络安全性和健壮性方面效果显著。但是,P2P信任模型自身的安全性成为另一个需要关注的问题,尤其是共谋团体攻击对P2P信任模型造成的安全威胁最为严重。如何有效抵制共谋团体的攻击、提高P2P网络的安全性成为当前亟需解决的问题。本文针对P2P信任模型中的共谋团体问题进行研究,取得了一系列成果: (1) 针对P2P信任模型中节点的评价行为提出了基于节点行为向量的共谋团体识别方法。通过对节点之间的行为相似度进行聚类分析,可以有效识别网络中存在的共谋团体,在提高信任模型安全性方面具有明显效果。 (2) 基于节点行为的复杂性和模糊性,提出了基于模糊逻辑的共谋团体识别方法。该方法扩展了对节点行为的描述范围,并利用模糊逻辑分析节点行为的相似度,充分考虑了节点评价的模糊特性,更加有利于对共谋团体的识别。 (3) 受恶意代码检测技术的启发,提出基于行为轮廓的共谋团体检测方法。通过构建节点和节点集合的行为轮廓,对节点和节点集合的行为进行了更加全面深入的描述,在此基础上通过分析行为轮廓相似度识别共谋团体。同时,通过引入集合行为轮廓的概念,降低了传统聚类过程中的计算开销,使节点之间的共谋行为更加容易识别。 总的来说,本文针对P2P信任模型中的共谋团体,通过分析共谋团体的行为特征,提出了一系列基于行为相似的共谋团体识别方法,适应当前现实网络环境的需要,可以有效地识别网络中存在的共谋团体,大大提高了P2P信任模型对共谋团体攻击的抵制能力。
英文摘要: As peer-to-peer (P2P) applications have seen enormous success, the security of P2P is getting more and more concerns. The trust has become bottle-neck of P2P network because of the open and anonymous nature of P2P network. Trust model poses a security mechanism for P2P network and is proven to play an important role in improving the robustness of P2P. However, P2P trust model is facing great security threats from collusion attack. Colluding groups have to be paid more and more attention. To address the problem, this paper focuses on the colluding group in P2P trust model, carries out a large amount of research work, and gets a series of fruits: (1) On the basis of peer’ behaviors, we propose a behavioral vetcor-based detector of collusion, which can effectively detect the existing colluding groups in a P2P trust model by measuring behavioral similarity and improve robustness of P2P trust systems in the face of colluding attackers. (2) Considering the fuzziness of peers’ behaviors, a novel collusion detector is presented based on fuzzy logic and linguistic variable. It places more attention on describing the peer’s behavior. It measures behavioral similarity based on fuzzy analysis and achieves good goal in detecting collusion. (3) Inspired by the analysis of malware, a collusion detection mechanism, behavior profile-based detector of collusion (BPD), is developed. BPD uses behavioral profiles to describe the behavior of a peer or a collection of peers. By introduing the concept of collective behavioral profile, colluding peers can be detected more easily. In a word, this paper does a deep research and analysis on detecting collusion in P2P trust models by measuring behavior similarity, and proposes several algorithms and mechanisms, which can effectively detect existing colluding attackers and secure P2P trust model.
语种: 中文
内容类型: 学位论文
URI标识: http://ir.iscas.ac.cn/handle/311060/2377
Appears in Collections:信息安全国家重点实验室_学位论文

Files in This Item:
File Name/ File Size Content Type Version Access License
P2P信任模型中的共谋团体识别技术研究.pdf(1426KB)----限制开放 联系获取全文

Recommended Citation:
苗光胜. P2P信任模型中的共谋团体识别技术研究[D]. 北京. 中国科学院研究生院. 2010-05-31.
Service
Recommend this item
Sava as my favorate item
Show this item's statistics
Export Endnote File
Google Scholar
Similar articles in Google Scholar
[苗光胜]'s Articles
CSDL cross search
Similar articles in CSDL Cross Search
[苗光胜]‘s Articles
Related Copyright Policies
Null
Social Bookmarking
Add to CiteULike Add to Connotea Add to Del.icio.us Add to Digg Add to Reddit
所有评论 (0)
暂无评论
 
评注功能仅针对注册用户开放,请您登录
您对该条目有什么异议,请填写以下表单,管理员会尽快联系您。
内 容:
Email:  *
单位:
验证码:   刷新
您在IR的使用过程中有什么好的想法或者建议可以反馈给我们。
标 题:
 *
内 容:
Email:  *
验证码:   刷新

Items in IR are protected by copyright, with all rights reserved, unless otherwise indicated.

 

 

Valid XHTML 1.0!
Copyright © 2007-2017  中国科学院软件研究所 - Feedback
Powered by CSpace