ACM Home Page
Please provide us with feedback. Feedback
Reputation-based framework for high integrity sensor networks
Full text PdfPdf (468 KB)
Source Workshop on Security of ad hoc and Sensor Networks archive
Proceedings of the 2nd ACM workshop on Security of ad hoc and sensor networks table of contents
Washington DC, USA
SESSION: Sensor networks table of contents
Pages: 66 - 77  
Year of Publication: 2004
ISBN:1-58113-972-1
Authors
Saurabh Ganeriwal  University of California - Los Angeles
Mani B. Srivastava  University of California - Los Angeles
Sponsors
ACM: Association for Computing Machinery
SIGSAC: ACM Special Interest Group on Security, Audit, and Control
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 13,   Downloads (12 Months): 165,   Citation Count: 12
Additional Information:

abstract   references   cited by   index terms   collaborative colleagues  

Tools and Actions: Review this Article  
Save this Article to a Binder    Display Formats: BibTex  EndNote ACM Ref   
DOI Bookmark: Use this link to bookmark this Article: http://doi.acm.org/10.1145/1029102.1029115
What is a DOI?

ABSTRACT

The traditional approach of providing network security has been to borrow tools from cryptography and authentication. However, we argue that the conventional view of security based on cryptography alone is not sufficient for the unique characteristics and novel misbehaviors encountered in sensor networks. Fundamental to this is the observation that cryptography cannot prevent malicious or non-malicious insertion of data from internal adversaries or faulty nodes.

We believe that in general tools from different domains such as economics, statistics and data analysis will have to be combined with cryptography for the development of trustworthy sensor networks. Following this approach, we propose a reputation-based framework for sensor networks where nodes maintain reputation for other nodes and use it to evaluate their trustworthiness. We will show that this framework provides a scalable, diverse and a generalized approach for countering all types of misbehavior resulting from malicious and faulty nodes.

We are currently developing a system within this framework where we employ a Bayesian formulation, specifically a beta reputation system, for reputation representation, updates and integration. We will explain the reasoning behind our design choices, analyzing their pros & cons. We conclude the paper by verifying the efficacy of this system through some preliminary simulation results.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
C. Karlof, D. Wagner. Secure routing in sensor networks: Attacks and countermeasures. Elsevier AdHoc Networks journal, May 2003.
2
 
3
J. Newsome, E. Shi, D. Song, A. Perrig. The sybil attack in sensor networks: Analysis and Defenses. In Proceedings of IPTPS. March 2002.
 
4
 
5
C. Karlof, N. Sastry, D. Wagner. TinySec: Link Layer Encryption for Tiny Devices. To appear in ACM SenSys, 2004.
 
6
J. Deng, R. Han and S. Mishra. The Performance Evaluation of Intrusion-Tolerant Routing in Wireless Sensor Networks. In the Proceedings of IPSN, April, 2003.
7
 
8
S. Ganeriwal, R. Kumar, C. C. Han. S. Lee, M. B. Srivastava. Location & Identity based Secure Event Report Generation for Sensor Networks. NESL Techanical Report, May 2004.
 
9
F. Ye, H. Luo, S. Lu, L. Zhang. Statistical En-route Detection and Filtering of Injected False Data in Sensor Networks. In Proceedings of IEEE Infocom, 2004.
10
 
11
12
 
13
 
14
M. Blaze, J. Feigenbaum, J. Ioannidis and A. Keromytis. RFC2704 - The KeyNote Trust Management System Version 2. 1999.
 
15
 
16
P. Resnick, R. Zeckhauser. Trust among strangers in Internet transactions: Empirical analysis of eBay's reputation system. NBER workshop on empirical studies of electronic commerce, 2000.
17
 
18
19
 
20
S. Buchegger, J. L. Boudec. Coping with false accusations in misbehavior reputation systems for mobile ad-hoc networks. EPFL technical report, 2003.
 
21
S. Buchegger, J. L. Boudec. A Robust Reputation System for P2P and Mobile Ad-hoc Networks. In Proceedings of P2PEcon 2004, Harvard University, Cambridge MA, U.S.A., June 2004.
 
22
23
 
24
R. L. Trivers. The evolution of reciprocal altruism. Quarterly review of biology, 46:35--57.
25
 
26
A. Jsang and R. Ismail. The Beta Reputation System. In Proceedings of the 15th Bled Electronic Commerce Conference, June 2002.
 
27
G. Shafer. A mathematical theory of evidence. Princeton University, 1976.
 
28
 
29
Beta distribution from Mathword. http://mathworld.wolfram.com/BetaDistribution.html
 
30
S. Ganeriwal, V. Tsiatsis, C. Schurgers, M. B. Srivastava. NESLsim: A Parsec based Simulation Platform for Sensor Networks. http://www.ee.ucla.edu/ saurabh/NESLsim?
 
31

CITED BY  12
 
 
 

Collaborative Colleagues:
Saurabh Ganeriwal: colleagues
Mani B. Srivastava: colleagues