Lanier Watkins, Shreya Aggarwal, Omotola Akeredolu, William H. Robinson and Aviel Rubin

Medical Body Area Networks (MBAN) are created when Wireless Sensor Nodes are either embedded into the patient’s body or strapped onto it. MBANs are used to monitor the health of patients in real-time in their homes. Many cyber protection mechanisms exist for the infrastructure that interfaces with MBANs; however, not many effective cyber security mechanisms exist for MBANs. We introduce a low-overhead security mechanism for MBANs based on having nodes infer anomalous power dissipation in their neighbors to detect compromised nodes. Nodes will infer anomalous power dissipation in their neighbors by detecting a change in their packet send rate. After two consecutive violations, the node will “Tattle” on its neighbor to the gateway, which will alert the Telemedicine administrator and notify all other nodes to ignore the compromised node.

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Thien Duc Nguyen, Phillip Rieger, Markus Miettinen and Ahmad-Reza Sadeghi (TU Darmstadt, Germany)

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IoT Security Solution Distribution via DLT

Le Su (Nanyang Technological University, Singapore); Dinil Mon Divakaran (Trustwave, Singapore); Sze Ling Yeo (Institute for Infocomm Research, Singapore); Jiqiang Lu (Beihang University, China); Vrizlynn Thing (National University of Singapore, Singapore)

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Mining Threat Intelligence from Billion-scale SSH Brute-Force Attacks

Yuming Wu, Phuong Cao (University of Illinois at Urbana Champaign, USA); Alexander Withers (National Center for Supercomputing Application, USA); Zbigniew Kalbarczyk and Ravishankar Iyer (University of Illinois at Urbana Champaign, USA)

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Information Leaks in Sequential Federated Learning

Anastassiya Pustozerova and Rudolf Mayer (SBA Research, Austria)

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