吉林大学学报(工学版) ›› 2015, Vol. 45 ›› Issue (5): 1581-1585.doi: 10.13229/j.cnki.jdxbgxb201505029

• • 上一篇    下一篇

BT网络中基于声望值的信任管理模型

刘衍珩, 唐伯浩, 李松江, 王爱民   

  1. 吉林大学 计算机科学与技术学院, 长春 130012
  • 收稿日期:2014-07-22 出版日期:2015-09-01 发布日期:2015-09-01
  • 通讯作者: 王爱民(1970-),男,副教授,硕士生导师.研究方向:无线传感网与物联网.E-mail:wangam@jlu.edu.cn
  • 作者简介:刘衍珩(1958-）,男,教授,博士生导师.研究方向:无线传感网与物联网.E-mail:yhliu@jlu.edu.cn
  • 基金资助:
    国家自然科学基金面上项目(61373123); 吉林省科技发展计划项目(20150414004GH, 20120301)

Model of reputation-based trust management in BT network

LIU Yan-heng, TANG Bo-hao, LI Song-jiang, WANG Ai-min   

  1. College of Computer Science and Technology, Jilin University, Changchun 130012, China
  • Received:2014-07-22 Online:2015-09-01 Published:2015-09-01

RICH HTML

0   

PDF (PC)

219

摘要： 针对BitTorrent网络中free-riding行为导致文件分享速率降低、上行带宽浪费的问题,提出一种基于声望值的信任管理模型。模型使用“上传信任值”与“评价可信值”两种评价标准迭代计算的方式对节点在网络中的表现予以评价,结合节点的下载行为和上传行为,避免节点针对单一评价标准做出相应欺骗行为,通过多个指标识别不诚实节点,降低free-riding节点获得资源的机会。PeerSim仿真实验结果表明:该模型可以有效屏蔽free-riding行为,提高BitTorrent网络的文件分享速率,对女巫攻击和勾结攻击具有较好的屏蔽效果。

关键词: 计算机应用, BitTorrent, 声望值, 信任

Abstract: To solve the problem of file-sharing rate reduction and waste of upstream bandwidth caused by free-riding behavior in BitTorrent (BT) network, a new model of reputation-based trust management is proposed. This model iterated "Upload Trust" and "Evaluation Trust" to estimate the performance of each code, which combined the behaviors of upload and download together. It avoids the nodes cheating in one estimate standard and uses more parameters to identify dishonest nodes. So the nodes with free-riding behavior have an only a poor chance to get the resource. Through experiments over PeerSim, the results show that this model can effectively prevent the free-riding behavior and improve the file-sharing rate in BT network. It also has positive effect on dealing with Sybil attack and Collusion attack.

Key words: computer application, BitTorrent, reputation, trust

中图分类号: 

  • TP39
[1] Fan X, Li M, Ma J, et al. Behavior-based reputation management in P2P file-sharing networks[J]. Journal of Computer and System Sciences, 2012, 78(6): 1737-1750.
[2] Sarjaz B S, Abbaspour M. Securing BitTorrent using a new reputation-based trust management system[J]. Peer-to-Peer Networking and Applications, 2013, 6(1): 86-100.
[3] Shin K, Reeves D S, Rhee I. Treat-before-trick: Free-riding prevention for BitTorrent-like peer-to-peer networks[C]∥Parallel & Distributed Processing, IEEE, 2009: 1-12.
[4] Gheorghe G, Cigno R L, Montresor A. Security and privacy issues in P2P streaming systems: a survey[J]. Peer-to-Peer Networking and Applications, 2011, 4(2): 75-91.
[5] Douceur J R. The Sybil Attack[M].Berlin:Springer Berlin Heidelberg, 2002: 251-260.
[6] Locher T, Moor P, Schmid S, et al. Free riding in BitTorrent is cheap[C]∥Proc Workshop on Hot Topics in Networks (HotNets),California,USA,2006: 85-90.
[7] Piatek M, Isdal T, Anderson T, et al. Do incentives build robustness in BitTorrent[C]∥Proc of NSDI,Cambridge,2007:1-14.
[8] Levin D, LaCurts K, Spring N, et al. Bittorrent is an auction: analyzing and improving bittorrent's incentives[C]∥ACM SIGCOMM Computer Communication Review, ACM, 2008, 38(4): 243-254.
[9] Shah P, Pâris J F. Incorporating trust in the BitTorrent protocol[C]∥International Symposium on Performance Evaluation of Computer and Telecommunication Systems,San Diego,USA,2007:586-593.
[10] Ge T, Manoharan S. Mitigating free-riding on bittorrent networks[C]∥Digital Telecommunications (ICDT), 2010 Fifth International Conference on, IEEE, 2010: 52-56.
[11] Manoharan S, Ge T. A demerit point strategy to reduce free-riding in BitTorrent[J]. Computer Communications, 2013, 36(8): 875-880.
[12] 陈绵书, 王世朋, 陈贺新, 等. 改进的基于推荐证据的对等网络信任模型[J]. 吉林大学学报: 工学版, 2013,43 (6): 1666-1674. Chen Mian-shu, Wang Shi-peng, Chen He-xin, et al. Improved trust model based on recommendation evidence for P2P networks[J]. Journal of Jilin University (Engineering and Technology Edition), 2013,43 (6): 1666-1674.
[13] Bhakuni A, Sharma P, Kaushal R. Free-rider detection and punishment in BitTorrent based P2P networks[C]∥Advance Computing Conference (IACC), 2014 IEEE International, IEEE, 2014: 155-159.
[1] 刘富,宗宇轩,康冰,张益萌,林彩霞,赵宏伟. 基于优化纹理特征的手背静脉识别系统[J]. 吉林大学学报(工学版), 2018, 48(6): 1844-1850.
[2] 王利民,刘洋,孙铭会,李美慧. 基于Markov blanket的无约束型K阶贝叶斯集成分类模型[J]. 吉林大学学报(工学版), 2018, 48(6): 1851-1858.
[3] 金顺福,王宝帅,郝闪闪,贾晓光,霍占强. 基于备用虚拟机同步休眠的云数据中心节能策略及性能[J]. 吉林大学学报(工学版), 2018, 48(6): 1859-1866.
[4] 赵东,孙明玉,朱金龙,于繁华,刘光洁,陈慧灵. 结合粒子群和单纯形的改进飞蛾优化算法[J]. 吉林大学学报(工学版), 2018, 48(6): 1867-1872.
[5] 刘恩泽,吴文福. 基于机器视觉的农作物表面多特征决策融合病变判断算法[J]. 吉林大学学报(工学版), 2018, 48(6): 1873-1878.
[6] 欧阳丹彤, 范琪. 子句级别语境感知的开放信息抽取方法[J]. 吉林大学学报(工学版), 2018, 48(5): 1563-1570.
[7] 刘富, 兰旭腾, 侯涛, 康冰, 刘云, 林彩霞. 基于优化k-mer频率的宏基因组聚类方法[J]. 吉林大学学报(工学版), 2018, 48(5): 1593-1599.
[8] 桂春, 黄旺星. 基于改进的标签传播算法的网络聚类方法[J]. 吉林大学学报(工学版), 2018, 48(5): 1600-1605.
[9] 刘元宁, 刘帅, 朱晓冬, 陈一浩, 郑少阁, 沈椿壮. 基于高斯拉普拉斯算子与自适应优化伽柏滤波的虹膜识别[J]. 吉林大学学报(工学版), 2018, 48(5): 1606-1613.
[10] 车翔玖, 王利, 郭晓新. 基于多尺度特征融合的边界检测算法[J]. 吉林大学学报(工学版), 2018, 48(5): 1621-1628.
[11] 赵宏伟, 刘宇琦, 董立岩, 王玉, 刘陪. 智能交通混合动态路径优化算法[J]. 吉林大学学报(工学版), 2018, 48(4): 1214-1223.
[12] 黄辉, 冯西安, 魏燕, 许驰, 陈慧灵. 基于增强核极限学习机的专业选择智能系统[J]. 吉林大学学报(工学版), 2018, 48(4): 1224-1230.
[13] 傅文博, 张杰, 陈永乐. 物联网环境下抵抗路由欺骗攻击的网络拓扑发现算法[J]. 吉林大学学报(工学版), 2018, 48(4): 1231-1236.
[14] 曹洁, 苏哲, 李晓旭. 基于Corr-LDA模型的图像标注方法[J]. 吉林大学学报(工学版), 2018, 48(4): 1237-1243.
[15] 侯永宏, 王利伟, 邢家明. 基于HTTP的动态自适应流媒体传输算法[J]. 吉林大学学报(工学版), 2018, 48(4): 1244-1253.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
版权所有 © 《吉林大学学报(工学版)》编辑部
地址：长春市人民大街5988号　电话：+86-431-85095297　传真：+86-431-85094074　E-mail: xbgxb@jlu.edu.cn
本系统由北京玛格泰克科技发展有限公司设计开发