Ling Liu's SC13 paper "Large Graph Processing Without the Overhead" featured by HPCwire.
Another list highlighting Open Source Software Releases.
Second GraphLab workshop should be even bigger than the first! GraphLab is a new programming framework for graph-style data analytics.
Reliable and Resilient Trust Management in Distributed Service Provision Networks
ACM Transactions on the Web.
Zhiyuan Su^, Ling Liu, Mingchu Li^, Xinxin Fan^, Yang Zhou
Georgia Institute of Technology
* Dalian University of Technology
^ Dalian University of Technology & Georgia Institute of Technology
Distributed service networks are popular platforms for service providers to offer services to consumers and for service consumers to acquire services from unknown parties. eBay and Amazon are two well-known examples of enabling and hosting such service networks to connect service providers to service consumers. Trust management is a critical component for scaling such distributed service networks to a large and growing number of participants. In this paper, we present ServiceTrust++, a feedback quality sensitive and attack resilient trust management scheme for empowering distributed service networks with effective trust management capability. Comparing with existing trust models, ServiceTrust++ has several novel features. First, we present six attack models to capture both independent and colluding attacks with malicious cliques, malicious spies and malicious camouflages. Second, we aggregate the feedback ratings based on the variances of participants’ feedback behaviors and incorporate feedback similarity as weight into the local trust algorithm. Third, we compute the global trust of a participant by employing conditional trust propagation based on feedback similarity threshold. This allows ServiceTrust++ to control and prevent malicious spies and malicious camouflage peers to boost their global trust scores by manipulating the feedback ratings of good peers and by taking advantage of the uniform trust propagation. Finally, we systematically combine trust decaying strategy with threshold-value based conditional trust propagation to further strengthen the robustness of our global trust computation against sophisticated malicious feedbacks. Experimental evaluation with both simulation-based networks and real network dataset Epinion show that ServiceTrust++ is highly resilient against all six attack models and highly effective compared to EigenTrust, the most popular and representative trust propagation model to date.
FULL PAPER: pdf