research-article

Patching by automatically tending to hub nodes based on social trust

Authors:

Leyi ShiAuthors Info & Claims

Computer Standards & Interfaces, Volume 44, Issue C

Pages 94 - 101

https://doi.org/10.1016/j.csi.2015.08.001

Published: 01 February 2016 Publication History

Abstract

Malicious code can propagate rapidly via software vulnerabilities. In order to prevent the explosion of malicious codes on the Internet, a distributed patching mechanism is proposed in which the patch can tend to hub nodes automatically based on social computing in social networks. A server in social network generates automatic patches and then selects those nodes with maximum degree to push automatic patches to. Those hub nodes then send the patch to their buddies according to their degree in social network. Automatic patches propagate rapidly through hub nodes and patch nodes in social network, which will improve the security of the whole social network. Those receivers accept the patch according to trust value to the sender, which can avoid some malicious codes exploit our scheme to propagate themselves. Experiments show this mechanism is more efficient than other patching mechanisms. A distributed patching scheme which can improve the security of the InternetThe patch can tend to hub nodes automatically.A sender pushes the patch to its buddies according to their degree in social network.The receivers accept the patch according to trust value to the sender.Automatic patches propagate rapidly in social network and patch nodes.

References

[1]

NationalComputer Virus Emergency Response Center, 2013 National Information Security, Computer and Mobile Terminal Virus Epidemic Survey Analysis Report, 2014.

[2]

Microsoft Data Access Components (MDAC) Function Could Allow Code Execution(911562), . http://technet.microsoft.com/zh-cn/security/bulletin/ ms06-014

[3]

M. Vojnovic, A. Ganesh, On the Effectiveness of Automatic Patching, in: Workshop on Rapid Malcode, Fairfax, Virginia, USA, 2005, pp. 41-50.

[4]

L. Xie, S. Zhu, A feasibility study on defending against ultra-fast topological worms, in: Seventh IEEE International Conference on Peer-to-Peer Computing. Galway, Ireland, 2007, pp. 61-70.

Digital Library

[5]

S. Shakkottai, R. Srikant, Peer to peer networks for defense against Internet worms, IEEE J. Sel. Areas Commun., 25 (2007) 1745-1752.

Digital Library

[6]

Friedman. "A. Good Neighbors Can Make Good Fences: A Peer-to-Peer User Security System," IEEE Technology and Society Magazine, Spring 2007, vol. 26, pp.17-24.

[7]

Z. Zhu, G. Cao, S. Zhu, A social network based patching scheme for worm containment in cellular networks, IEEE INFOCOM, 2009.

[8]

S. Sidiroglou, A. Keromytis, Countering network worms through automatic patch generation, IEEE Secur. Priv., 3 (Dec. 2005) 41-49.

Digital Library

[9]

D. Lazer, A. Pentland, L. Adamic, Computational social science, Science, 323 (Feb. 2009) 721-723.

[10]

Golbeck J. "Weaving a Web of Trust. Science Magazine," AAAS, Sep. 2008, vol. 321, pp. 1640-1641.

[11]

R. Sinha, K. Swearingen, Comparing recommendations made by online systems and friends, in: Proceedings of the DELOS-NSF Workshop on Personalization and Recommender Systems in Digital Libraries Dublin, Ireland, 2001.

[12]

J. O'Donovan, B. Smyth, Trust in recommender systems, in: IUI'05: Proceedings of the 10th International Conference on Intelligent User Interfaces, New York, NY, USA, ACM, 2005, pp. 167-174.

Digital Library

[13]

J.S. Kong, B.A. Rezaei, N. Sarshar, Collaborative spam filtering using e-mail networks, IEEE Comput., 39 (Aug. 2006) 67-73.

Digital Library

[14]

M. Sirivianos, K. Kim, X. Yang, SocialFilter: Introducing Social Trust to Collaborative Spam Mitigation, IEEE INFOCOM, 2011.

[15]

F. Zifa, J. Altmann, An empirically validated framework for limiting free-riding in P2P networks through the use of social network information, in: PACIS 2010. Taipei, Taiwan: Pacific Asia Conference on Information Systems, 2010.

[16]

S. Marti, Trust and Reputation in Peer to Peer Networks, Stanford University, 2005.

[17]

H. Yu, M. Kaminsky, P.B. Gibbons, Sybilguard: Defending against Sybil Attacks via Social Networks, in: Proceedings of ACM SIGCOMM, 2006, pp. 576-589.

[18]

Liu Xin, Jia Chunfu, Liu Guoyou, Hu Zhichao, Wang Dong, Collaborative defending scheme against malicious Web pages based on social trust, J. Commun., 33 (Dec. 2012) 11-18.

[19]

J. Golbeck, Computing and Applying Trust in Web-based Social Networks, University of Maryland, College Park, 2005.

[20]

A. Abdul-Rahman, S. Hailes, Supporting trust in virtual communities, in System Sciences, in: Proceedings of the 33rd Annual Hawaii International Conference on. IEEE, 2000, 2000.

[21]

Liu Xin Hu, Liu Guoyou Zhichao, Jia Chunfu, Defending P2P Networks Based on Benign Worms, J. Comput. Inf. Syst., 7 (2011) 2532-2539.

[22]

J. Caverlee, L. Liu, S. Webb, Socialtrust: tamper-resilient trust establishment in online communities, in: Proceedings of the 8th ACM/IEEE-CS joint conference on Digital libraries, ACM, 2008, pp. 104-114.

Digital Library

[23]

L. Xin, S. Leyi, W. Yao, X. Zhaojun, F. Wenjing, A dynamic trust conference algorithm for social network, in: P2P, Parallel, Grid, Cloud and Internet Computing (3PGCIC), 2013 Eighth International Conference on, IEEE, 2013, pp. 340-346.

[24]

T. Zhuo, L. Zhengding, L. Kai, Time-based dynamic trust model using ant colony algorithm, Wuhan University J. Nat. Sci., 11 (2006) 1462-1466.

[25]

L. Yan, Y. Pan, J. Zhang, Trust cluster head election algorithm based on ant colony systems, in: Computational Science and Optimization (CSO), 2010 Third International Joint Conference on, vol. 2, IEEE, 2010, pp. 419-422.

Digital Library

[26]

F.G. M¿armol, G.M. P¿erez, Providing trust in wireless sensor networks using a bio-inspired technique, Telecommun. Syst., 46 (2011) 163-180.

[27]

P. Bedi, R. Sharma, Trust based recommender system using ant colony for trust computation, Expert Syst. Appl., 39 (2012) 1183-1190.

Digital Library

[28]

Jia Chunfu, Liu Xin, Liu Guoyou, Hu Zhichao, Worm Containment Based on Double-neighbor Lists in P2P Overlay Networks, in: Proceedings of 2010 IEEE International Conference on Information Theory and Information Security (ICITIS 2010), December 17-19, 2010, pp. 558-562.

[29]

Y. Wang, J. Lü, F. Xu, L. Zhang, A trust measurement and evolution model for internetware, J. Softw., 17 (2006) 682-690.

[30]

Datatang, http://www.datatang.com/.

[31]

Zheli Liu, Xiaofeng Chen, Jun Yang, Chunfu Jia, Issue You, New order preserving encryption model for outsourced databases in cloud environments, J. Netw. Comput. Appl. (2014).

[32]

Baojiang Cui, Zheli Liu*, Lingyu Wang, Key-Aggregate Searchable Encryption (KASE) for group data sharing via cloud storage, IEEE Trans. Comput. (2015).

[33]

Jin Li, Qian Wang, Cong Wang, Ning Cao, Kui Ren, Wenjing Lou, Fuzzy Keyword Search over Encrypted Data in Cloud Computing, in: Proceeding of the 29th IEEE International Conference on Computer Communications (INFOCOM 2010), IEEE, 2010, pp. 441-445.

[34]

Jin Li, Kwangjo Kim, Hidden attribute-based signatures without anonymity revocation, Inf. Sci., 180 (2010) 1681-1689.

Digital Library

Cited By

Liu XZou PZhang WZhou JDai CWang FZhang X(2017)CPSFSWireless Communications & Mobile Computing10.1155/2017/14578702017Online publication date: 27-Dec-2017
https://dl.acm.org/doi/10.1155/2017/1457870
Olmedilla MMartínez-Torres MToral S(2016)Harvesting Big Data in social scienceComputer Standards & Interfaces10.1016/j.csi.2016.02.00346:C(79-87)Online publication date: 1-May-2016
https://dl.acm.org/doi/10.1016/j.csi.2016.02.003

Patching by automatically tending to hub nodes based on social trust
1. Social and professional topics
  1. Computing / technology policy

Recommendations

Automatic Patching Based on Social Computing in P2P Network
EIDWT '13: Proceedings of the 2013 Fourth International Conference on Emerging Intelligent Data and Web Technologies

Malicious codes can propagate rapidly by exploiting software vulnerabilities. In order to prevent the explosion of malicious codes in P2P networks, an automatic patching mechanism based on social computing is proposed. The security server generates ...
Social Ties and Generalized Trust, Online and in Person: Contact or Conflict-The Mediating Role of Bonding Social Capital in America

Results of the present survey (n = 888) suggest that having strong social ties (or bonding social capital) fosters generalized trust, in support of conflict theory. There was no link between bridging social capital, or one's more diverse ties, and ...
Building trust communities using social trust
UMAP'11: Proceedings of the 19th international conference on Advances in User Modeling

The growing popularity of Web based social networks has given rise to the need to build trust communities that inspire members to share their experiences, feelings and opinions in an open and honest way. In this paper, we propose a framework for building ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image Computer Standards & Interfaces

Computer Standards & Interfaces Volume 44, Issue C

February 2016

289 pages

ISSN:0920-5489

Issue’s Table of Contents

Copyright © Elsevier B.V.

Publisher

Elsevier Science Publishers B. V.

Netherlands

Publication History

Published: 01 February 2016

Author Tags

Qualifiers

Research-article

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

2
Total Citations
View Citations
0
Total Downloads

Downloads (Last 12 months)0
Downloads (Last 6 weeks)0

Reflects downloads up to 16 Nov 2024

Other Metrics

View Author Metrics

Citations

Cited By

Liu XZou PZhang WZhou JDai CWang FZhang X(2017)CPSFSWireless Communications & Mobile Computing10.1155/2017/14578702017Online publication date: 27-Dec-2017
https://dl.acm.org/doi/10.1155/2017/1457870
Olmedilla MMartínez-Torres MToral S(2016)Harvesting Big Data in social scienceComputer Standards & Interfaces10.1016/j.csi.2016.02.00346:C(79-87)Online publication date: 1-May-2016
https://dl.acm.org/doi/10.1016/j.csi.2016.02.003

View Options

View options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

Media

Figures

Other

Tables

View Issue’s Table of Contents