Spring 2022 Security Courses
COMPSCI 561 System Defense & Test (formerly COMPSCI 590A)
Instructor: Parviz Kermani
3 credits
Tuesdays 5:30 - 6:45 P.M.
A course on detection and analysis of vulnerabilities in systems from the perspective of an "ethical hacker". Topics include tools and techniques for penetration testing, information gathering, social engineering, and defenses. We also cover malware, DOS attacks, SQL injection, buffer overflow, session hijacking, system hacking, network sniffing and scans, WiF security, IDS evasion, metasploit tools, and setting up honeypots.
COMPSCI 590J Cyber Effects: Reverse Engineering, Exploits Analysis, and Capability Development
This course covers a broad range of topics related to cyber security and operations. Our focus is on real world studies of reverse engineering, exploit analysis, and capability development within the context of computer network operations and attack. The course has an emphasis on hands-on exercises and projects. Topics covered include computer architecture and assembly language, principles of embedded security, the essentials of exploit development and analysis (including using industry standard tools such as Ghidra, and utilizing computer security databases such as CVE), and discussion of real-world events and techniques. Instructors are from the MITRE Corporation.
Instructors: Nick Merlino, Seth Landsman, Daniel Walters, Edward Walters, Adam Woodbury
3 credits
Monday, Wednesday from 5:30 - 6:45 P.M.
COMPSCI 590K Advanced Digital Forensics Systems (formerly COMPSCI 590F)
Marc Liberatore
3 credits
Online
This course offers a broad introduction to the forensic investigation of digital devices. We cover the preservation, recovery, harvesting, and courtroom presentation of information from file systems, operating systems, networks, database systems applications, media files, and embedded systems. The primary goal of the class is to understand why and from where information is recoverable in these systems. We also cover relevant issues from criminology, law, and the study of privacy.
COMPSCI 596E Machine Learning Applied to Child Rescue
Instructor: Jagath Jai Kumar
Day/Time: TBA FULLY REMOTE
3 Credits
This course is a group-based, guided independent study. Our goal is to build practical machine learning models to be used by professionals dedicated to rescuing children from abuse. Students will be encouraged to design and build their own diagnostic and machine learning tools, while also learning from professionals in the fields of digital forensics and law enforcement. The entire student group will meet once a week to share progress via short presentations. Prerequisites: Permission of instructor only. To gain permission, you must be a CS student with a machine learning background. We expect high grades in CS 589 or CS 682. See link for additional information including how to request enrollment. This course will meet weekly at a time that works best for all students enrolled.