Mark Shaneck

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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)
Wireless sensor networks are envisioned to be deployed in mission-critical applications. Detecting a compromised sensor, whose memory contents have been tampered, is crucial in these settings, as the attacker can reprogram the sensor to act on his behalf. In the case of sensors, the task of verifying the integrity of memory contents is difficult as physical(More)
Network Intrusion Detection is a critical task in today's environment, where network attacks and intrusions are everyday occurrences and state-level cyber warfare is a major concern. At the same time, it is a very difficult task, in part due to the large scale of the data logs where the attack information is hidden, and also in part because of the lack of(More)
With growing dependence upon interconnected networks, defending these networks against intrusions is becoming increasingly important. In the case of attacks that are composed of multiple steps, detecting the entire attack scenario is of vital importance. In this paper, we propose an analysis framework that is able to detect these scenarios with little(More)
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