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M.S. in Computer Science - Cybersecurity Focus
36
Credit Hours
20
Month Completion
Class Type
Face-to-face, Online courseworkSee state availability
Next Start Date
Sep 30, 2024
Placement Tests
GMAT/GRE not required for admission

Customize your M.S. in computer science with a focus in cybersecurity

Properly functioning software boosts an organization鈥檚 efficiency and effectiveness, while unsecure solutions spell disaster in terms of lost time and productivity. Security-minded computer science professionals make the difference. With Franklin鈥檚 100% online M.S. in Computer Science with a focus in Cybersecurity, you鈥檒l learn how to design systems that align with organizational needs and security best practices. Building on the core principles of Franklin鈥檚 forward-thinking master鈥檚-level computer science program, the cybersecurity focus enables you to customize your degree to your career aspirations.

Finish Fast

Finish your master's in as few as 20 months.

Leading Industry Tools

Get hands-on experience with Netlab+, Burp Suite, Metasploit and openssl.

Customizable Program

Tailor your master's degree program to your interests.

Real-World Practitioners

Learn from experienced technology leaders.

100% Online Classes

Take classes that fit with your busy life.

Game-Changing Skills

Play an important role in communicating emerging technologies to stakeholders.

M.S. in Computer Science - Cybersecurity Focus Overview

Gain essential knowledge in software delivery, verification and testing

As part of your M.S. in Computer Science-Cybersecurity, you鈥檒l earn a  that demonstrates your knowledge of software verification and testing and your competency to deliver high-quality software, especially in large complex systems. Through hands-on coursework, you鈥檒l learn how to design and build software to minimize the presence of flaws or mitigate their impacts. You鈥檒l also gain an understanding of important principles in historical and modern cryptography.

Learn to preserve the confidentiality and integrity of information

You鈥檒l dive into the fundamentals of security including risks and vulnerabilities, threat modeling, policy formation, controls and protection methods, encryption and authentication technologies, network security, cryptography, personnel and physical security issues, as well as ethical and legal issues. You鈥檒l emerge with the ability to prescribe defenses against intrusion, recommend access control plans for systems and software, and perform qualitative and quantitative risk assessments.

Explore principles in historical and modern cryptography

The cryptographic primitives of enciphering/deciphering and hashing are the two main methods of protecting information, so mastery of cryptographic techniques is an important skill. You鈥檒l learn to differentiate between basic cryptographic functionality, including symmetric and asymmetric cryptography, block versus stream ciphers, digital signatures and hash functions. Upon completion of the cryptography course, you鈥檒l also be able to combine different cryptographic functions to secure algorithms, contrast various modes of cryptographic algorithms, choose appropriate cryptographic techniques for specific scenarios and summarize attacks on cryptographic primitives.

Get course credit for (ISC)2 CSSLP certification

Because Franklin鈥檚 M.S. in Computer Science is aligned with industry competencies, you can get credit toward your degree for relevant certifications. Current (ISC)2 CSSLP certification has been evaluated to be equivalent to ISEC 620, which is a required course for the cybersecurity focus area. The (ISC)2 CSSLP certification provides you with 4 hours of graduate level credit and saves you 12 weeks and $2,680 in tuition. Your admissions advisor can provide guidance on how to submit your credential documentation to receive credit.

Read more >

Dimitri V.

M.S. Computer Science '22

"My professors taught me many valuable topics including applications of AI, testing, software architecture as well as industry best practices and insights. My classmates also helped me to learn and put the knowledge to use, and as a result, my experience at Franklin has shaped a complete perspective of the field of Computer Science for me."

Future Start Dates

Start dates for individual programs may vary and are subject to change. Please request free information & speak with an admission advisor for the latest program start dates.

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**Source: 麻豆传媒色情片, Office of Career Development Student Satisfaction Survey (Summer 2023)

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M.S. in Computer Science - Cybersecurity Focus Curriculum

Major Area Required
COMP 611 - Advanced Data Structures and Programming (4)

This course covers key knowledge and skills for advanced software development using the object-oriented approach. The student learns, manipulates and reflects on nonlinear data structures such as trees and heaps. Recursive algorithms, sorting algorithms, algorithm efficiency, and advanced design patterns are addressed. To support the advanced concepts and principles of software development, the student will design, code, test, debug, and document programs with increased scale and complexity using industry's best practices (such as GitHub) and the Java programming language.

COMP 620 - Analysis of Algorithms (4)

This course covers various algorithm design paradigms, mathematical analysis of algorithms, empirical analysis of algorithms and NP-completeness.

COMP 630 - Issues in Database Management (4)

This course focuses on the fundamental design considerations in designing a database. Specific topics include performance analysis of design alternatives, system configuration and the administration of a popular database system. The course also offers an in-depth analysis of the algorithms and machine organizations of database systems. Note, this course has proctored exam(s). This exams requires additional technology, if student uses online proctoring.

COMP 655 - Distributed Systems (4)

This course provides a comprehensive understanding of distributed systems, encompassing both fundamental concepts and practical skills for building modern distributed applications. The course will explore the architecture, design goals, and challenges of distributed systems, covering core principles like processes, transparency, communication, consistency, fault tolerance, and security. Throughout the course, students will gain hands-on experience through labs and a team project, where they will design, develop, containerize and deploy a microservice-based cloud native application using industry-standard tools and technologies. Through this course, students will gain in-depth understanding of core concepts of distributed computing, including study of both abstract concepts and practical techniques for building modern distributed applications.

COMP 671 - Verification and Testing (4)

This course focuses on the issues of delivering high-quality software, especially in large complex systems. Topics covered include testing strategies (black box, white box, regression, etc.), unit testing, system integration, system verification and support tools. It also will reinforce the need for requirements that are testable and traceable from the early design stages.

COMP 691 - Capstone (4)

This course, the final one in the Master of Science - Computer Science program, challenges students to research a current topic of interest in Computer Science and produce an original paper and presentation on the topic. In addition to the research paper, students are introduced to the economics of software development and the tools needed to estimate the cost of a software development project for management in a corporate environment. The last topic in the course is a discussion of ethics as it relates to Information Technology. Current topics in ethics will be discussed through the use of relevant case studies.

Major Electives

At least 12 credits from the following courses:

MATH 601 - Introduction to Analytics (4)

This course provides an introductory overview of methods, concepts, and current practices in the growing field of statistics and data analytics. Topics to be covered include data collection, data analysis and visualization as well as probability, statistical inference and regression methods for informed decision-making. Students will explore these topics with current statistical software. Some emphasis will also be given to ethical principles of data analytics.

DATA 605 - Data Visualization & Reporting (4)

This course focuses on collecting, preparing, and analyzing data to create visualizations, dashboards, and stories that can be used to communicate critical business insights. Students will learn how to structure and streamline data analysis projects and highlight their implications efficiently using the most popular visualization tools used by businesses today.

DATA 611 - Applied Machine Learning (4)

This course explores two main areas of machine learning: supervised and unsupervised. Topics include the fundamental concepts, roadmap of a machine learning project, classification algorithms, regression algorithms, dimensionality reduction, model evaluation, natural language processing, neural networks and deep learning, typical issues in real-world machine learning problems, and Python programming in data science.

COMP 645 - Object-Oriented Design & Practice (4)

This course surveys current practices in software development and software design, especially in the area of object-oriented design. The course will examine and contrast current and leading edge methodologies and practices, including agile, extreme programming, test-driven design, patterns, aspect-oriented programming, model-driven architecture, Unified Modeling Language, and integrated development environments.

COMP 650 - System Architecture & Engineering (4)

This course covers topics in software systems engineering. Its scope is the design of the overall architecture for software systems with emphasis on distributed architectures. The issues in an architecture centered software development cycle and project management are addressed.

COMP 670 - Application of Artificial Intelligence (4)

This course is an introduction to Artificial Intelligence (AI) from an applied perspective. After an introduction of some basic concepts and techniques (such as searching and knowledge representation), the course illustrates both the theoretical foundation and application of these techniques with examples from a variety of problems. The course surveys a wide range of active areas in AI such as machine learning, artificial neural networks, evolutionary computing, robotics, intelligent agents and bio-inspired AI approaches. It strikes a balance between engineering approaches and theory. Exercises include hands-on application of basic AI techniques as well as selection of appropriate technologies for a given problem. The principal topics in the selected areas are also coupled with projects where groups of students will participate in the creation of AI-based applications.

COMP 610 - Internship in Computer Science (1-4)

This course provides MSCS students the opportunity to further their education with relevant work experience in the field of Computer Science. This internship is an ongoing seminar between the student, faculty and the employment supervisor. It involves a Learning Contract (Curricular Practical Training [CPT] Information, or other), periodic meetings with the faculty representative, and professional experience at a level equivalent to other electives of the MSCS program. Specification of the materials to be submitted is established in the learning contract. Participation cannot be guaranteed for all applicants.

COMP 699 - Independent Studies in Graduate Computer Science (1-4)

Independent studies courses allow students in good academic standing to pursue learning in areas not covered by the regular curriculum or to extend study in areas presently taught. Study is under faculty supervision and graded on Pass/No Credit basis. For international students, curricular practiced training may be used as an independent study with approval of program chair. (See the "Independent Studies" section of the Academic Bulletin for more details.)

CYSC 610 - Information Assurance (4)

This course covers the fundamentals of security in the enterprise environment. Included are coverage of risks and vulnerabilities, threat modeling, policy formation, controls and protection methods, encryption and authentication technologies, network security, cryptography, personnel and physical security issues, as well as ethical and legal issues. This foundational course serves as an introduction to many of the subsequent topics discussed in depth in later security courses. Note, this course has proctored exam(s). This exam requires additional technology, if student uses online proctoring.

CYSC 620 - Software and App Security (4)

Today, software is at the heart of the business processes of nearly every business from finance to manufacturing. Software pervades everyday life in expected places like phones and computers but also in places that you may not consider such as toasters, thermostats, automobiles, and even light bulbs. Security flaws in software can have impacts ranging from inconvenient to damaging and even catastrophic when it involves life-critical systems. How can software be designed and built to minimize the presence of flaws or mitigate their impacts? This course focuses on software development processes that identify, model, and mitigate threats to all kinds of software. Topics include threat modeling frameworks, attack trees, attack libraries, defensive tactics, secure software development lifecycle, web, cloud, and human factors.

CYSC 640 - Cryptography (4)

The cryptographic primitives of enciphering/deciphering and hashing are the two main methods of preserving confidentiality and integrity of data at rest and in transit. As such, the study of cryptographic techniques is of primary interest to security practitioners. This course will cover the important principles in historical and modern cryptography including the underlying information theory, mathematics, and randomness. Important technologies such as stream and block ciphers, symmetric and asymmetric cryptography, public key infrastructure, and key exchange will be explored. Finally, hashing and message authentication codes will be examined as a way of preserving data integrity.

Students may complete a focus area to fulfill the Major Elective requirement.

Optional Focus Areas

Students may complete a focus area to fulfill the Major Elective requirement.

OR

Data Analytics:

MATH 601 - Introduction to Analytics (4)

This course provides an introductory overview of methods, concepts, and current practices in the growing field of statistics and data analytics. Topics to be covered include data collection, data analysis and visualization as well as probability, statistical inference and regression methods for informed decision-making. Students will explore these topics with current statistical software. Some emphasis will also be given to ethical principles of data analytics.

DATA 605 - Data Visualization & Reporting (4)

This course focuses on collecting, preparing, and analyzing data to create visualizations, dashboards, and stories that can be used to communicate critical business insights. Students will learn how to structure and streamline data analysis projects and highlight their implications efficiently using the most popular visualization tools used by businesses today.

DATA 611 - Applied Machine Learning (4)

This course explores two main areas of machine learning: supervised and unsupervised. Topics include the fundamental concepts, roadmap of a machine learning project, classification algorithms, regression algorithms, dimensionality reduction, model evaluation, natural language processing, neural networks and deep learning, typical issues in real-world machine learning problems, and Python programming in data science.

OR

Cybersecurity:

CYSC 610 - Information Assurance (4)

This course covers the fundamentals of security in the enterprise environment. Included are coverage of risks and vulnerabilities, threat modeling, policy formation, controls and protection methods, encryption and authentication technologies, network security, cryptography, personnel and physical security issues, as well as ethical and legal issues. This foundational course serves as an introduction to many of the subsequent topics discussed in depth in later security courses. Note, this course has proctored exam(s). This exam requires additional technology, if student uses online proctoring.

CYSC 620 - Software and App Security (4)

Today, software is at the heart of the business processes of nearly every business from finance to manufacturing. Software pervades everyday life in expected places like phones and computers but also in places that you may not consider such as toasters, thermostats, automobiles, and even light bulbs. Security flaws in software can have impacts ranging from inconvenient to damaging and even catastrophic when it involves life-critical systems. How can software be designed and built to minimize the presence of flaws or mitigate their impacts? This course focuses on software development processes that identify, model, and mitigate threats to all kinds of software. Topics include threat modeling frameworks, attack trees, attack libraries, defensive tactics, secure software development lifecycle, web, cloud, and human factors.

CYSC 640 - Cryptography (4)

The cryptographic primitives of enciphering/deciphering and hashing are the two main methods of preserving confidentiality and integrity of data at rest and in transit. As such, the study of cryptographic techniques is of primary interest to security practitioners. This course will cover the important principles in historical and modern cryptography including the underlying information theory, mathematics, and randomness. Important technologies such as stream and block ciphers, symmetric and asymmetric cryptography, public key infrastructure, and key exchange will be explored. Finally, hashing and message authentication codes will be examined as a way of preserving data integrity.

OR

Software Systems:

COMP 645 - Object-Oriented Design & Practice (4)

This course surveys current practices in software development and software design, especially in the area of object-oriented design. The course will examine and contrast current and leading edge methodologies and practices, including agile, extreme programming, test-driven design, patterns, aspect-oriented programming, model-driven architecture, Unified Modeling Language, and integrated development environments.

COMP 650 - System Architecture & Engineering (4)

This course covers topics in software systems engineering. Its scope is the design of the overall architecture for software systems with emphasis on distributed architectures. The issues in an architecture centered software development cycle and project management are addressed.

COMP 670 - Application of Artificial Intelligence (4)

This course is an introduction to Artificial Intelligence (AI) from an applied perspective. After an introduction of some basic concepts and techniques (such as searching and knowledge representation), the course illustrates both the theoretical foundation and application of these techniques with examples from a variety of problems. The course surveys a wide range of active areas in AI such as machine learning, artificial neural networks, evolutionary computing, robotics, intelligent agents and bio-inspired AI approaches. It strikes a balance between engineering approaches and theory. Exercises include hands-on application of basic AI techniques as well as selection of appropriate technologies for a given problem. The principal topics in the selected areas are also coupled with projects where groups of students will participate in the creation of AI-based applications.

Corequisites
COMP 501 - Foundations of Programming (4)

This course covers fundamental programming principles. Students will learn about the basic elements of a computer program, such as data types, assignments, conditional branching, loops, functions, recursion, basic data structures, program debugging, and testing.

OR ITEC 136 - Principles of Programming (4)

This course introduces programming to individuals with little or no programming background. The goal of this course is to introduce the fundamentals of structured programming, problem solving, algorithm design, and software lifecycle. Topics will include testing, data types, operations, repetition and selection control structures, functions and procedures, arrays, and top down stepwise refinement. Students will design, code, test, debug, and document programs in a relevant programming language.

OR COMP 111 - Introduction to Computer Science & Object-Oriented Programming (4)

This course provides an introduction to software construction using an object-oriented approach. The student learns and reflects on problem analysis, object-oriented design, implementation, and testing. To support the concepts and principles of software construction, the student will design, code, test, debug, and document programs using the Java programming language. Basic data types, control structures, methods, and classes are used as the building blocks for reusable software components. Automated unit testing, programming style, and industrial practice are emphasized in addition to the object-oriented techniques of abstraction, encapsulation, and composition. Note, this course has proctored exam(s).

COMP 511 - Foundation Data Struc & Obj Orntd Design (4)

This course continues the object-oriented approach to intermediate-level software development. The student will learn and reflect on fundamental object-oriented analysis techniques, basic design patterns, and linear data structures such as lists and queues.

OR COMP 121 - Object-Oriented Data Structures & Algorithms I (4)

This course continues the objected-oriented approach to software construction. The student learns and reflects on advanced object-oriented techniques, algorithm efficiency, class hierarchies, and data structures. To support the concepts and principles of software construction, the student will design, code, test, debug, and document programs using the Java programming language. Design principles, I/O, exception handling, linear data structures (lists, stacks, and queues), and design patterns are emphasized in addition to the object-oriented techniques of inheritance and polymorphism. Note, this course has proctored exam(s).

MATH 503 - Foundations of Mathematics for Computing (4)

This course introduces students to fundamental algebraic, logical, and combinational concepts in mathematics that are needed in upper division computer science courses. Topics include integer representation; algorithms; modular arithmetic and exponentiation; discrete logarithms; cryptography; recursion; primality testing; number theory; graphs and directed graphs; trees; and Boolean Algebra.

OR MATH 320 - Discrete Mathematics (4)

This course introduces students to fundamental algebraic, logical, and combinational concepts in mathematics that are needed in upper-division computer science courses. Topics include sets, mappings, and relations; elementary counting principles; proof techniques with an emphasis on mathematical induction; graphs and directed graphs; Boolean algebras; recursion; and applications to computer science.

Students with an undergraduate degree in computer science will be admitted without future prerequisites. However, the students will be expected to possess intermediate Java programming skills as determined by completing COMP 121 or COMP 511, having a Java SE 8 programmer certification from Oracle, or a portfolio of Java-related examples that would include the fundamentals of object-oriented programming, linear and non-liner data structures (stacks, queues, lists, etc.)

Students without a computer science degree will need to have credit for the above 麻豆传媒色情片 courses or the equivalent undergraduate course work for the prerequisites at an institutionally (formerly regionally) accredited institution OR appropriate relevant work experience. Graduate prerequisite courses (500 level) must be completed with a grade of "C" or better. Undergraduate prerequisite courses must be completed with a grade of "C" or better. Work experience as a software engineer, developer, or programmer analyst will be evaluated by the program chair upon request. Resumes, work samples, and personal interviews may all be used to determine the depth of knowledge in these areas.

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M.S. in Computer Science - Cybersecurity Focus Program Details

Manasa K.

M.S. Computer Science '20

"Thank you 麻豆传媒色情片, for helping me reach this important milestone in my career."

Computer Science Cybersecurity Career Opportunities

Information Security Analyst

Information security analysts plan and implement security features to protect an organization鈥檚 computer networks and systems. 

Software Developer

Software developers, also known as computer programmers, help design, create, install, test and maintain relevant and functional computer programs and device applications. 

Cybersecurity Engineer

Cybersecurity engineers lead cybersecurity operations, build technical roadmaps and manage virtual network models.

Computer Science Cybersecurity Employment Outlook

13%

From 2021-2031 jobs in Computer Science are expected to increase by 13%

All Occupations

2021
5,400,282 jobs
2031
6,080,567 jobs
Show Details >

Computer and Information Systems Managers

2023
604,207 jobs
2033
722,584 jobs

Software Developers and Software Quality Assurance Analysts and Testers

2021
1,600,098 jobs
2031
1,924,125 jobs

Web Developers and Digital Interface Designers

2021
198,907 jobs
2031
222,454 jobs

Computer User Support Specialists

2023
604,207 jobs
2033
722,584 jobs

Computer Systems Analysts

2023
593,007 jobs
2033
676,019 jobs


Source information provided by Lightcast.

Knowledge & Skillsets

Gain in-demand skills sought by employers with curriculum that teaches you:

M.S. Computer Science - Cybersecurity, M.S. IT - Cybersecurity or M.S. in Cybersecurity?

Find the Cybersecurity Program That Fits Your Goals

If you鈥檙e interested in advancing your cybersecurity career, Franklin has several great options. Compare programs and identify your perfect match.

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M.S. in Computer Science - Cybersecurity
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M.S. in Information Technology - Cybersecurity
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M.S. in Cybersecurity

Focus: 
Expand your technology capabilities to include identifying and developing security-focused software solutions.
 
Skills:
Advance your software development skills and expand your understanding of cryptography.
 
Careers: 
Use your M.S. in Computer Science-Cybersecurity to lead the development of software solutions that prevent catastrophic loss.
 
How many courses are in the program?
Nine 12-week courses
 
How quickly can I complete the program?
20 months

Focus: 
Develop expertise in the areas of risk management, network security and ethical hacking.
 
Skills:
Deepen your understanding of operational security, risk assessment, mitigation and incident response.
 
Careers: 
Leverage your M.S. in IT-Cybersecurity to become a driving force in systems and data protection.
 
How many courses are in the program?
Nine 12-week courses
 
How quickly can I complete the program?
16 months

Focus: 
Grow your knowledge and experience with emerging cybersecurity technologies, methodologies and strategies.

Skills:
Build leadership and technical skills along with cutting-edge application of cyber defense strategies and tactics.
 
Careers: 
Put your M.S. in Cybersecurity to work delivering risk-based, business-driven security strategies and action plans.
 
How many courses are in the program?
Nine courses (three 6-week courses and six 12-week courses)
 
How quickly can I complete the program?
16 months

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