On the Detection of Malware on Virtual Assistants Based on Behavioral Anomalies | Spiros Mancoridis, Drexel University


Friday, October 18, 2019, 1:30pm to 2:30pm


Harvard University, Maxwell Dworkin G115, 33 Oxford Street, Cambridge MA

IACS seminars are free and open to the public; no registration required.  Lunch will not be provided.

ABSTRACT: Dr. Spiros Mancoridis's work explores some of the security concerns pertaining to running software similar to Amazon Alexa home assistant on IoT-like platforms. Researchers implemented a behavioral-based malware detector and compared the effectiveness of different system attributes that are used in detecting malware, i.e., system calls, network traffic, and the integration of system call and network traffic features. Given the small number of malware samples for IoT devices, researchers created a parameterizable malware sample that mimics Alexa behavior in varying degrees, while exfiltrating data from the device to a remote host. The performance of the anomaly detector was evaluated based on how well it determined the presence of the parameterized malware on an Alexa-enabled IoT device.

BIO: Dr. Mancoridis is the Auerbach Berger Chair in Cybersecurity and a Distinguished Professor of Computer Science at the College of Computing & Informatics (CCI) at Drexel University. He holds a BCSH in computer science from Acadia University (1990) and MSc and PhD degrees from the University of Toronto (1992, 1996). He joined Drexel's faculty in 1996, previously serving as interim department head of the Department of Computer Science, and then as a Senior Associate Dean and then as Interim Dean of CCI. He is a recipient of the National Science Foundation’s 1998 CAREER Award. His expertise includes autonomic computing, reverse engineering, software security, and genetic algorithms.

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