The official PGP user's guide
NSPW '97 Proceedings of the 1997 workshop on New security paradigms
An evidential model of distributed reputation management
Proceedings of the first international joint conference on Autonomous agents and multiagent systems: part 1
A Memory-Based Approach to Anti-Spam Filtering for Mailing Lists
Information Retrieval
A Computational Model of Trust and Reputation for E-businesses
HICSS '02 Proceedings of the 35th Annual Hawaii International Conference on System Sciences (HICSS'02)-Volume 7 - Volume 7
Collaborative Reputation Mechanisms in Electronic Marketplaces
HICSS '99 Proceedings of the Thirty-second Annual Hawaii International Conference on System Sciences-Volume 8 - Volume 8
Bayesian Network-Based Trust Model
WI '03 Proceedings of the 2003 IEEE/WIC International Conference on Web Intelligence
Journal of Functional Programming
Dynamic Control of Worm Propagation
ITCC '04 Proceedings of the International Conference on Information Technology: Coding and Computing (ITCC'04) Volume 2 - Volume 2
Collision Module Integration in a Specific Graphic Engine for Terrain Visualization
IV '04 Proceedings of the Information Visualisation, Eighth International Conference
A Distributed Trust Model for e-Commerce Applications
EEE '05 Proceedings of the 2005 IEEE International Conference on e-Technology, e-Commerce and e-Service (EEE'05) on e-Technology, e-Commerce and e-Service
Review on Computational Trust and Reputation Models
Artificial Intelligence Review
Detecting spam in VoIP networks
SRUTI'05 Proceedings of the Steps to Reducing Unwanted Traffic on the Internet on Steps to Reducing Unwanted Traffic on the Internet Workshop
Using Trust for Secure Collaboration in Uncertain Environments
IEEE Pervasive Computing
From simulations to theorems: a position paper on research in the field of computational trust
FAST'06 Proceedings of the 4th international conference on Formal aspects in security and trust
Multilateral decisions for collaborative defense against unsolicited bulk e-mail
iTrust'06 Proceedings of the 4th international conference on Trust Management
Nuisance level of a voice call
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
Engineering of Software-Intensive Systems: State of the Art and Research Challenges
Software-Intensive Systems and New Computing Paradigms
Can machines call people?: user experience while answering telephone calls initiated by machine
CHI '09 Extended Abstracts on Human Factors in Computing Systems
A Survey of Voice over IP Security Research
ICISS '09 Proceedings of the 5th International Conference on Information Systems Security
A provider-level reputation system for assessing the quality of SPIT mitigation algorithms
ICC'09 Proceedings of the 2009 IEEE international conference on Communications
Towards ubiquitous computing with call prediction
ACM SIGMOBILE Mobile Computing and Communications Review
Behavior-based adaptive call predictor
ACM Transactions on Autonomous and Adaptive Systems (TAAS)
SPRT for SPIT: using the sequential probability ratio test for spam in VoIP prevention
AIMS'12 Proceedings of the 6th IFIP WG 6.6 international autonomous infrastructure, management, and security conference on Dependable Networks and Services
Outbound SPIT filter with optimal performance guarantees
Computer Networks: The International Journal of Computer and Telecommunications Networking
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Voice over IP (VoIP) is a key enabling technology for migration of circuit-switched PSTN (Public Switched Telephone Network) architectures to packet-based networks. One problem of the present VoIP networks is filtering spam calls referred to as SPIT (Spam over Internet Telephony). Unlike spam in e-mail systems, VoIP spam calls have to be identified in real time. Many of the techniques devised for e-mail spam detection rely upon content analysis, and in the case of VoIP, it is too late to analyze the content (voice) as the user would have already attended the call. Therefore, the real challenge is to block a spam call before the telephone rings. In addition, we believe it is imperative that spam filters integrate human behavioral aspects to gauge the legitimacy of voice calls. We know that, when it comes to receiving or rejecting a voice call, people use the social meaning of trust, reputation, friendship of the calling party and their own mood. In this article, we describe a multi-stage, adaptive spam filter based on presence (location, mood, time), trust, and reputation to detect spam in voice calls. In particular, we describe a closed-loop feedback control between different stages to decide whether an incoming call is spam. We further propose formalism for voice-specific trust and reputation analysis. We base this formal model on a human intuitive behavior for detecting spam based on the called party's direct and indirect relationships with the calling party. No VoIP corpus is available for testing the detection mechanism. Therefore, for verifying the detection accuracy, we used a laboratory setup of several soft-phones, real IP phones and a commercial-grade proxy server that receives and processes incoming calls. We experimentally validated the proposed filtering mechanisms by simulating spam calls and measured the filter's accuracy by applying the trust and reputation formalism. We observed that, while the filter blocks a second spam call from a spammer calling from the same end IP host and domain, the filter needs only a maximum of three calls---even in the case when spammer moves to a new host and domain. Finally, we present a detailed sensitivity analysis for examining the influence of parameters such as spam volume and network size on the filter's accuracy.