Digital Forensics Graduate Courses

Click on any course title below to read its description. Courses offered in the upcoming semester include a schedule, and are indicated by a label to the right of the title.

Overview of data communication and computer networks, including network hardware and software, as well as reference models, example networks, data communication services and network standardization. The OSI and the Internet (TCP/IP) network models are discussed. The course covers each network layer in details, starting from the Physical layer to towards the Application layer, and includes an overview of network security topics. Other topics covered include encoding digital and analog signals, transmission media, protocols. circuit, packet, message, switching techniques, internetworking devices, topologies. LANs/WANs, Ethernet, IP, TCP, UDP, and Web applications. Labs on network analysis. Prereq: MET CS 575 and MET CS 201 or MET CS 231 or MET CS 232. Or instructor's consent. Restrictions: This course may not be taken in conjunction with MET CS 625 or MET CS 425 (undergraduate). Only one of these courses can be counted towards degree requirements.  [ 4 cr. ]

Sum1 2017
Section Type Instructor Location Days Times
BHA IND Nourai M 6:00 pm – 9:30 pm
SC1 IND Day CAS M 6:00 pm – 9:30 pm
Fall 2017
Section Type Instructor Location Days Times
D1 IND Day MCS B33 R 6:00 pm – 8:45 pm

This course presents the foundations of data communications and takes a bottom-up approach to computer networks. The course concludes with an overview of basic network security and management concepts. Prereq: MET CS 200, or instructor's consent. This course may not be taken in conjunction with MET CS 425 (undergraduate) or MET CS 535. Only one of these courses can be counted towards degree requirements.  [ 4 cr. ]

Sum1 2017
Section Type Instructor Location Days Times
SC1 IND Arena SHA T 6:00 pm – 9:30 pm
SEL IND Arena SHA T 6:00 pm – 9:30 pm
SO1 IND Chitkushev ARR
Fall 2017
Section Type Instructor Location Days Times
B1 IND Arena FLR 109 T 6:00 pm – 8:45 pm
E1 IND Arena FLR 109 T 6:00 pm – 8:45 pm
O1 IND Rizinski ARR
O2 IND Mansur ARR

Provides a comprehensive understanding of digital forensics and investigation tools and techniques. Learn what computer forensics and investigation is as a profession and gain an understanding of the overall investigative process. Operating system architectures and disk structures are discussed. Studies how to set up an investigator's office and laboratory, as well as what computer forensic hardware and software tools are available. Other topics covered include importance of digital evidence controls and how to process crime and incident scenes, details of data acquisition, computer forensic analysis, e-mail investigations, image file recovery, investigative report writing, and expert witness requirements. Provides a range of laboratory and hands-on assignments either in solo or in teams. With rapid growth of computer systems and digital data this area has grown in importance. Prereq: Working knowledge of windows computers, including installing and removing software. Access to a PC meeting the minimum system requirements defined in the course syllabus.  [ 4 cr. ]

Sum1 2017
Section Type Instructor Location Days Times
SEL IND Arena FLR S 1:00 pm – 3:00 pm
Fall 2017
Section Type Instructor Location Days Times
E1 IND Sheehan FLR 123 S 9:00 am – 12:00 pm
O1 IND Navarro ARR

Overview of mobile forensics investigation techniques and tools. Topics include mobile forensics procedures and principles, related legal issues, mobile platform internals, bypassing passcode, rooting or jailbreaking process, logical and physical acquisition, data recovery and analysis, and reporting. Provides in-depth coverage of both iOS and Android platforms. Laboratory and hands-on exercises using current tools are provided and required.  [ 4 cr. ]

Section Type Instructor Location Days Times
SO1 IND Zhang ARR

Data mining and investigation is a key goal behind any data warehouse effort. The course provides an introduction to concepts behind data mining, text mining, and web mining. Algorithms will be tested on data sets using the Weka Data mining software and Microsoft SQL Server 2005 (Business Intelligence Development Studio). Prereq: MS CS Prerequisites: MET CS 579; or instructor's consent. MS CIS Prerequisites: MET CS 669 and MET CS 546; or instructor's consent.  [ 4 cr. ]

Sum1 2017
Section Type Instructor Location Days Times
SO1 IND Lee ARR
Fall 2017
Section Type Instructor Location Days Times
D1 IND Lee FLR 267 R 6:00 pm – 8:45 pm
E1 IND Lee FLR 267 R 6:00 pm – 8:45 pm
O1 IND Lee ARR

This course provides a comprehensive understanding of network forensic analysis principles. Within the context of forensics security, network infrastructures, topologies, and protocols are introduced. Students understand the relationship between network forensic analysis and network security technologies. Students will learn to identify network security incidents and potential sources of digital evidence and demonstrate the ability to perform basic network data acquisition and analysis using computer based applications and utilities. Students will also identify potential applications for the integration of network forensic technologies and demonstrate the ability to accurately document network forensic processes and analysis. Prereq: MET CS 625 and MET CS 695; or instructor's consent.  [ 4 cr. ]

Section Type Instructor Location Days Times
E1 IND Staff FLR 109 S 1:00 pm – 4:00 pm

This course provides an introduction to the advanced digital forensic topic relating to malicious software (malware), which represents an increasing information security threat to computer systems and networks. Students will review software engineering design fundamentals and reverse engineering techniques utilized to conduct static and dynamic forensic analysis on computer systems and networks. Students will learn about the importance of forensic principles, legal considerations, digital evidence controls, and documentation of forensic procedures. This course will incorporate demonstrations and laboratory exercises to reinforce practical applications of course instruction and will require an independent research paper related to the course topic. Prereq: MET CS 693 and MET CS 703; or instructor's consent.  [ 4 cr. ]

View the full list of Computer Science & IT graduate courses.