Overview of MS Concentration in Security

1. MS Computer Science Core   12 credits
2. Security Electives     6 credits
3. Electives   12 credits
Total Credits   30 credits

 

MS Computer Science Core Requirements 
Four courses 

1. Students must satisfy the CompSci MS core requirements:  four courses (12 credits) from the Systems, Theory, and AI menus, with the following restrictions:

  • A grade of "B" or better is required for all core classes.
  • COMPSCI 660 must be taken as one of the Systems Cores.
  • One course from the MS COMPSCI Systems Core menu or the Security Systems Core menu (below) must be taken as a second Systems Core (note: not allowed in regular MS degree).
  • One course from the MS Theory Core menu must be taken.
  • One course from the MS AI Core menu must be taken.

Security Systems Core menu:

  • COMPSCI 690B Detecting Interference in Networks
  • COMPSCI 590F Advanced Digital Forensics
  • COMPSCI 661 Secure Distributed Systems
  • COMPSCI 590A System Defense and Test
  • COMPSCI 690C Foundations of Applied Cryptography

12 credits

Security Electives Requirements
Two courses (6 credits)

2. Students must take two (6 credits) security electives from Security Systems Electives menu

A grade of "B" or better is required for these two classes (not required in the normal MS degree).

Security Systems Electives menu:

  • COMPSCI 690B Detecting Interference in Networks
  • COMPSCI 590F Digital Forensics
  • COMPSCI 661 Secure Distributed Systems
  • COMPSCI 590A System Defense and Test
  • COMPSCI 597N Introduction to Computer and Network Security
  • COMPSCI 690C Foundations of Applied Cryptography
  • COMPSCI 563 (INFOSEC 690L) Internet Law & Policy
  • ECE 647: ST - Security Engineering

Outside courses on this list are preapproved and can count toward the CompSci MS course requirements
 

ECE 544/644 may not  be used towards the MS degree (since it overlaps with COMPCSI 597N). Math 571 and ECE 597XX may not be used towards the MS degree (since they overlap with COMPSCI 690C Foundations of Applied Cryptography).

 6 credits

Electives Requirements

Four courses (12 credits)

3. Students must take four additional COMPSCI courses as free electives. These courses are not limited to the security courses. Any CMPSCI graduate level class is acceptable. 

12 credits

Total

30 credits

Other Course Requirements:

  • No more than 9 credits may come from courses outside of CICS. Credit for graduate courses from other departments must be approved by the GPD.
  • No more than 18 of the course credits may come from courses at the 500 level. 500-level classes taken to satisfy core requirements fall into this group.
  • At least 12 of those 18 credits must come from courses at the 600-900 level that are not independent studies. 600-level classes taken to satisfy core requirements fall into this group.
  • No more than 6 credits may be pass/fail.
  • At most 12 credits from independent studies and/or a Master's project (COMPSCI 701).
  • Classes with a grade below a C may not be counted toward the MS degree.
  • No more than 12 credits may be transferred from other programs or institutions.
  • Your overall grade point average for those 30 MS credits must be 3.0 or higher.

 

 

Sample Schedule

Fall I

COMPSCI 590B Detecting Interference in Networks

COMPSCI 514 Algorithms for Data Science

First Systems core

Theory core

Spring I

COMPSCI 660 Advanced Information Assurance

COMPSCI 690A Advanced Methods in HCI

COMPSCI 590V Data Visualization and Exploration

Second System core

First elective

Second elective

Fall II

COMPSCI 591L Internet Law & Policy

COMPSCI 589 Machine Learning

COMPSCI 611 Advanced Algorithms

First Security elective

AL core

Third elective

Spring II

COMPSCI 661 Secure Distributed Systems

COMPSCI 690D Deep Learning for Natural Language Processing

Second Security elective

Fourth elective

 


THEORY CORE MENU

 At least one of the following courses can be used to complete the Theory core requirement:
 

COMPSCI 501

Formal Language Theory

COMPSCI 575

Combinatorics and Graph Theory**

COMPSCI 514

Algorithms for Data Science**

COMPSCI 601

Computation theory

COMPSCI 617

Advanced Algorithms

COMPSCI 690AA

Approximation Algorithms

COMPSCI 513** or COMPSCI 690LG

Logic (cannot do both)

COMPSCI 690M

Machine Learning Theory

COMPSCI 690T

Coding Theory and Applications

 

SYSTEMS CORE MENU

At most one of the following classes may be used to complete systems core requirements (if a course from the Security Systems Core menu is not used):

 

COMPSCI 503**

Embedded Computing Systems

COMPSCI 527**

Introduction to Affective Computing

COMPSCI 590C**

Human Computer Interaction

COMPSCI 590B** 

or 690B

Detecting Interference in Networks (cannot do both)

COMPSCI 590CC

Cloud Computing 

COMPSCI  590F**

Advanced Digital Forensics

COMPSCI 590M**

Introduction to Simulation

COMPSCI 590S**

Systems for Data Science

COMPSCI 590U**

Mobile and Ubiquitous Computing

COMPSCI 610

Compiler Techniques

COMPSCI 520** or 620

Advanced Software Engineering: Synthesis and Development (cannot do both)

COMPSCI 521** or 621

Advanced Software Engineering: Analysis and Evaluation (cannot do both)

COMPSCI 630

Systems

 

COMSCI 631

Programming Languages

COMPSCI 535** or 635

Modern Computer Architecture

COMPSCI 645

Database Design and Implementation

COMPSCI 653

Advanced Computer Networking

COMPSCI 655

Performance Evaluation

COMPSCI 660

Advanced Information Assurance

COMPSCI 661

Secure Distributed Systems

COMPSCI 677

Distributed and Operating Systems

COMPSCI 661**

Secure Distributed Systems

COMPSCI 690A

Advanced Methods in HCI

 

ARTIFICIAL INTELLIGENCE CORE MENU

One of the following may be used to satisfy the AI core requirement:

 

COMPSCI 585**

Introduction to Natural Language Processing

COMPSCI 589** or 689

Machine Learning

COMPSCI 590R**

Applied Information Retrieval

COMPSCI 590V**

Data Visualization and Exploration

COMPSCI 603

Robotics

COMPSCI 646

Information Retrieval

COMPSCI 650

Applied Information Theory

COMPSCI 670

Computer Vision

COMPSCI 682

Neural Networks:Modern Intro

COMPSCI 683

Artificial Intelligence

COMPSCI 687

Reinforcement Learning

COMPSCI 688

Graphical Models

COMPSCI 689

Machine Learning: Pattern Classification

COMPSCI 690D

Deep Learning/Natural Language Processing

COMPSCI 690IV

Intelligent Visual Computing

COMPSCI 690M

Machine Learning Theory

COMPSCI 690N

Advanced Natural Language Processing

COMPSCI 690V

Visual Analytics

CMPSCI 686, aka 691E

Reasoning & Acting Under Uncertainty - No longer offered

CMPSCI 691V

Multi-Agent Systems - No longer offered

 

**500-level courses do not count toward MS/PhD core requirements. Students who potentially could apply to the UMass PhD program should follow the MS/PhD core/course requirements.