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Secure and reliable group communication is an active area of research. Its popularity is fueled by the growing importance of group-oriented and collaborative applications. The central research challenge is secure and efficient group key management. While centralized methods are often appropriate for key distribution in large multicast-style groups, many(More)
Key management is one of the fundamental building blocks of security services. In a network with resource constrained nodes like sensor networks, traditional key management techniques, such as public key cryptography or key distribution center (e.g., Kerberos), are often not effective. To solve this problem, several key pre-distribution schemes have been(More)
This paper gives an overview of our research in building rare class prediction models for identifying known intrusions and their variations and anomaly/outlier detection schemes for detecting novel attacks whose nature is unknown. Experimental results on the KDDCup'99 data set have demonstrated that our rare class predictive models are much more efficient(More)
—Contributory group key agreement protocols generate group keys based on contributions of all group members. Particularly appropriate for relatively small collaborative peer groups, these protocols are resilient to many types of attacks. Unlike most group key distribution protocols, contributory group key agreement protocols offer strong security properties(More)
—In recent years, collaborative and group-oriented applications and protocols have gained popularity. These applications typically involve communication over open networks; security thus is naturally an important requirement. Group key management is one of the basic building blocks in securing group communication. Most prior research in group key management(More)
Data mining is frequently obstructed by privacy concerns. In many cases data is distributed, and bringing the data together in one place for analysis is not possible due to privacy laws (e.g. HIPAA) or policies. Privacy preserving data mining techniques have been developed to address this issue by providing mechanisms to mine the data while giving certain(More)
—Social network-based Sybil defenses exploit the al-gorithmic properties of social graphs to infer the extent to which an arbitrary node in such a graph should be trusted. However, these systems do not consider the different amounts of trust represented by different graphs, and different levels of trust between nodes, though trust is being a crucial(More)