REQUEST MORE INFORMATION

MS in Cyber Security

Master of Science in Cyber Security

Course Delivery

On Campus

Total Credits

36

Tuition Per Year

$20,250

Duration

2 years

Master’s in Cyber Security Program Overview

Bay Atlantic University’s MS Cyber Security program teaches students to protect the confidentiality, availability and integrity of information and information systems that support modern organizations. The program focuses on both the fundamentals of information systems as well as advanced topics in areas such as network security, cryptography, risk management, security governance, business continuity, security architecture, physical security and critical infrastructures.

Learning Goals

  • To meet the growing demand for high-level information systems/science skills
  • To provide a path for individuals from diverse fields to rapidly transition to data sciencecareers
  • Enable established IT and computing professionals to upgrade technical management and development skills
  • Prepare graduates to apply data science techniques for knowledge discovery and dissemination to assist researchers or decision-makers in achieving organizational objectives

Who is the Ideal Student for this program?

Cyber Security analysts or experts have analytical mindsets and a detailed understanding of Cyber Security methodologies. They work closesly with businesses to protect their computer and networking systems from potential hackers and cyber-attacks. Cyber Security analysts are expected to have a meticulous attention to detail, outstanding problem-solving skills, work comfortably under pressure and deliver on tight deadlines.

All courses are conducted on campus. To succeed in this program, students should be self-disciplined, self-directed and comfortable scheduling their own coursework.

Career Outlook

Cyber Security MS will prepare students for job titles such as Cryptographer, forensic expert, incident reporter, penetration tester, security administrator, security analyst, security architect, security auditor, security consultant, security director, security engineer, security manager, security software developer, security specialist, security code auditor, vulnerability auditor, and Network Security Engineer.

Request More Information

Please Click here or just give us a call at (202) 644-7200 to speak with an admissions advisor.

ms cyber security




Meet the Department Chair

PipopPipop Nuangpookka, PhD

[email protected]

Dr. Pipop Nuangpookka is the Chair of Information Management Science Program and Director of Distance Education at Bay Atlantic University.

Dr. Pipop Nuangpookka has been working as an Analyst/Programmer, Infrastructure Technologies, and Infrastructure Security since the year 2005. While working in the IT industry as a technical person, He started teaching in Computer Science, Information Technology, and Cybersecurity disciplines at several universities in Washington, DC, and Northern Virginia area in 2007. The various courses include Introduction to Computer Science, Computer Network, Computer Programming Languages (i.e., Java, Python, C, C++, ML, and Prolog), Structure of Programming Languages, Software Engineering, Data Structures & Algorithms, Database Management System (i.e., MS SQL Server, Oracle, MySQL, and SQL/PLSQL), Web Application Development and Security, Technology Management, and Technical Capstone Project. Dr. Nuangpookka graduated with a Bachelor’s Degree in Business Administration from Payap University, Thailand, in 1999, and a Master’s Degree in Computer Science in 2004 from Marymount University, Arlington, Virginia. He also earned a Doctor of Science Degree in Cybersecurity at Marymount University in 2020. His research interests are Non-Destructive Method of Detecting Hardware Attack, Personally Identifiable Information (PII) Security Controls, Web Server Protection, and Bilingual Translator Programming. He is a co-author of scholarly papers published in the Journal of Computing Sciences in Colleges/ACM digital library, including “Hardware-Tampering Security Risks in the Supply Chain” and “Fileless Malware and Programmatic Method of Detection.”

Courses

Students must earn a total of 36 college credit hours to receive this degree. Of these credit hours, 24 credits are core courses, and 12 concentration elective credits.

In addition, students must meet the following criteria:

  • Students enrolled in the graduate program must maintain a Cumulative Grade Point Average (CGPA) of at least 2.7 out of 4.0 to qualify for the Master’s degree, to remain in good standing, and to graduate.
  • The Maximum Time Frame (MTF) for completion of the Master’s program is 60 credits.
  • A graduate student may transfer up to 18 credit hours earned at accredited institutions.
CYBER SECURITY CORE REQUIREMENTS
CMPS 502
Cyber Security
3 Credits
This course introduces students to the field of cyber security. The goal is to educate and train students to understand general concepts and use the necessary tools to detect and prevent vulnerabilities in computer networks and systems. Students will be exposed to various cyber security tools used for the analysis , detection and prevention of threats. They will gain a thorough understanding of current cyber security technologies and ways of utilizing them to avoid attacks in the cyber world.
CMPS 515
Network Security & Cryptography
3 Credits
(Prerequisite CMPS 514) This is an introductory course where fundamental concepts in cryptography and network security are explained. After completing the course, students will get basic understanding about encryption, decryption, stream ciphers, block ciphers, public-key cryptography, digital signatures, hash functions, 1message authentication codes and key distribution protocols.
CMPS 514
Management Information Systems
3 Credits
This course studies systems used by companies to accumulate, classify, and organize information to aid managerial decision making. It emphasizes the considerations of upper-level management concerning the development, deployment, and use of information systems.
CMPS 564
Information Security Management
3 Credits
(Prerequisite CMPS 515) The aim of this course is to learn how information can be held securely in businesses and discuss the information security from managerial perspective. Moreover, the standards and approaches used for information security management are discussed. The standard of information security management which is ISO27001 is discussed in detail.
CMPS 578
Cyber Security Law
3 Credits
Information and communication technologies (ICT) are spreading into all aspects of our lives. Our increasing dependency on ICT is making us vulnerable to cyber crimes committed against our information systems. This course provides the necessary knowledge to judicially assess electronic evidence and handle cyber crime incidents.
CAPS 621
Capstone Project
3 Credits
(Prerequisite All Core) Each student in the MS in Big Data Analytics program is required to complete a capstone project. Each student may choose a project of his or her choice, under the guidance of a capstone advisor. The parameters of the course will be determined by the advisor and the student.
BGDA 522
Applied Statistics
3 Credits
The course introduces fundamental topics in statistics and implements its applications to industrial, medical, financial, energy and similar type very large-size datasets to infer meaningful statistical results. The course is for graduate students with no significant background on this subject. Implementations will be performed on the open source statistical software R. Introduction to R programming will be given.
CYBER SECURITY CORE ELECTIVES
BGDA 501
Introduction to Big Data
3 Credits
(Prerequisite CMPS 514) This course will provide insight into the basics of using "Big Data" to quantify operational implications of BAU ACADEMIC CATALOG 123 management choices. You will learn statistical models, mostly using R software, and analyze them to provide insight regarding the assumptions, value drivers, and risks present in a business situation. You will use your statistical models to explore different ways to think about uncertainty, guide decision-making, and persuasively communicate analytical results. Later in the course, by using the statistical tools learned, we will examine simple, introductory methods to text mining, building search engines and recommendation tools.
BGDA 510
Data Mining
3 Credits
(Prerequisite CMPS 514) This course provides an introduction to data mining concepts. Basic concepts in data mining: frequent item set detection, association rules, clustering and classification are covered in depth.
BGDA 511
Big Data and Analytics
3 Credits
(Prerequisite CMPS 514) Big data is a general term used to describe the tremendous amount of unstructured, semi-structured and textual data being created on a daily basis. Big data analytics is the process of examining large amounts of data with different types to discover hidden patterns, unknown correlations and potential useful information. This is important for enterprises as it can provide competitive advantages over rivals and other business benefits, such as more effective marketing and increased revenue. In this course, the technologies associated with big data analytics including NoSQL databases, Hadoop and MapReduce will be covered. These technologies form the core of an open source software framework that supports the processing of large data sets across clustered systems.
BGDA 513
Artificial Intelligence
3 Credits
(Prerequisite BGDA 511) The fundamentals and techniques of Artificial Intelligence are discussed in this course. The first part of the course begins with an overview of intelligent agents and agent architectures. We then introduce basic search techniques for problem solving and planning. Adversarial search and the principals of game theory are given. Knowledge representation and logical formalisms using propositional and first order logic are explained. Planning in partial observable environments is introduced. In the second part, we first give a summary of probability theory and then explain probabilistic reasoning including Markov Decision process and Reinforcement Learning. Then some basic concepts of Machine Learning algorithms are discussed. Finally, we give examples of AI applications such as Robotics, Computer Vision and Natural Processing
BGDA 521
Technology Management
3 Credits
(Prerequisite BGDA 510) This course is designed to lead the student to understand the importance and the nature of technological innovations, how they are integrated into business level strategies and how technological innovation process is managed. In this course, the aim is not only to understand the theories of technological innovations but also to discuss the practice of technological innovation. Therefore, case studies are important; most of the theoretical parts are followed by case studies.
CMPS 517
Computer Forensics
3 Credits
(Prerequisite CMPS 514) This is an applied course on techniques for computer forensics in Linux and Windows based systems. In this course, the process of computer forensics investigation will be presented in detail. Details on techniques for evidence collection will be given first. Different techniques for analysing the collected evidence will be explained. Finally,students will learn how to go over the found evidence and present it to authorities. Topics such as custody of chain, evidence preservation and verification will be explained in detail.
CMPS 524
Computer Networks and Mobile Communications
3 Credits
(Prerequisite CMPS 514) This course provides a comprehensive overview of computer networks and mobile communications technologies. The topics include computer networks, Internet, TCP/IP, transport layer protocols, routing layer protocols, medium access control protocols, wireless channel models, packet scheduling, multimedia networks, cellular networks (GSM, GPRS, CDMA, 3G, 4G, etc.), and wireless local area networks. The course aims at equipping students with a deeper understanding of computer and mobile networking technologies and related problem solving discipline using mathematics / engineering principles.
CMPS 618
Penetration Testing
3 Credits
(Prerequisite CMPS 564) Penetration testing, the most indispensable component of proactive cyber security, is commonly known as the exposition of information systems to security checks by expert professionals with the purpose of determining security vulnerabilities and thus helping take necessary countermeasures ahead of their possible exploitation by cyber attackers. In this course, the students will be thought methods for detecting security vulnerabilities in information systems and possible exploitation of these vulnerabilities to penetrate into computer systems. Topics covered will include network scanning, exploitation and postexploitation, password attacks, and attacks on wireless and web applications.
CMPS 623
Web Application Security
3 Credits
(Prerequisite CMPS 564) The web application technology stack contains various protocols, standards, frameworks and mechanisms at both the client and server sides. Due to these complexities and the unavoidable rapid technological shift, serious security vulnerabilities are the inevitable by-products, as encountered in insecure portals, web sites and applications. These vulnerabilities are commonly exploited by attacks such SQL Injection, Cross Site Scripting, Cross Site Request Forgery, Session Overloading, Brute Forces, Denial of Service, Log Forging, Dangerous Javascript Callbacks, Race Conditions, JSON Hijacking, Length Extension Attacks, Logical Attacks, etc. This course covers the common critical web application security vulnerabilities and hacking techniques exploited by malicious people. Students will learn solid defence techniques, such as input/output validation, right usages of authentication, authorization, crytographic functions and secure configuration, to thwart these hacking attempts.
CMPS 627
Wireless Sensor Network
3 Credits
(Prerequisite CMPS 524) This course provides a comprehensive overview of wireless sensor networks and their real-world applications. The topics include wireless sensor network protocols, network architectures and management, error control techniques, optimal packet size design, cross-layer communication protocol solutions, localization algorithms, ZigBee, IEEE 802.15.4, 6LowPAN, underwater and underground sensor networks, wireless sensor and actor networks, and wireless multimedia sensor networks. The course aims at equipping students with a deeper understanding of wireless sensor networking technologies and related problem solving discipline using mathematics / engineering principles.
CMPS 630
Machine Learning and Pattern Recognition
3 Credits
(Prerequisite CMPS 524) This course covers fundamental machine learning topics including pattern recognition systems and components; decision theories and classification; discriminant functions; supervised and unsupervised training; clustering; feature extraction and dimensional reduction; sequential and hierarchical classification; applications of training, feature extraction, and decision rules to engineering problems.

 

Official Bachelor’s transcript (must be in English)

Photocopy of government-issued ID (International students need a passport)

2 letters of recommendation (from former teachers, employers, coaches, etc.)

Letter of Intent – 1-2 page essay on ONE of the following topics:

 

    • Describe, who you are, your purpose and goals, your accomplishments, and why you want to get a higher education degree.
    • What is the most meaningful contribution to others you have made in your life? How do you understand the value of it on others?
    • What is the biggest challenge you have had in your life and how have you dealt with it?
    • What character in history do you associate yourself most with and why?

 

Additional Documents (For International Students ONLY)

 

    • Bank statement showing proof of adequate financial resources
    • Sponsorship letter (if bank statement is not in the applicant’s name)
    • If the applicant has any dependents, passport copies and additional materials as necessary.
    • Proof of English language proficiency

 

If the Bachelor’s degree was issued by a foreign institution of higher education, the applicant must provide an evaluation of the transcript from a NACES-member (http://www.naces.org) or an AICE member (http://www.aice-eval.org) credential evaluation service to establish U.S. equivalency of a Bachelor’s degree.  The evaluation must be a course-by-course evaluation of the transcript.

If the Bachelor’s degree transcript is NOT in English, the applicant must provide a certified English translation.

If the transcript does not clearly indicate the degree awarded, the applicant must provide a notarized copy of the college or university diploma.

 

Proof of English language proficiency*

All applicants whose first language is not English must submit proof of English language proficiency to Bay Atlantic University (BAU).  The requirement is waived if:

    • the applicant has completed four years of education at an English-language secondary school
    • the applicant has completed Mentora College’s 500C course with a passing grade

 

All other applicants must establish proficiency by providing an official score report of one of our approved standardized English proficiency tests (TOEFL, IELT, TOEIC)

 

EXAM SCORES:

TOEFL (PBT, CBT, IBT): 550, 214, 80

IELTS: 6.0

TOEIC: 700

BAU Placement Test:75 (offered on campus)

Duolingo: 90

Pearson (PTE): 53

Mentora College Intensive English Program: Pass 500C level

 

*For assistance of information on applying, please contact our Admissions team at [email protected]

**For our Frequently Asked Questions, please visit https://bau.edu/faq/

 

Graduation Requirements

The Master of Science in Cyber Security degree is earned by completing the program course requirements of 36 credit hours (12 courses of 3 credit hours), of which 24 credits are core courses and 12 credits are concentration elective courses. To qualify for the Master of Science in Cyber Security degree, students must meet all core and concentration elective credit requirements.

Students should meet the following minimum requirements to qualify for a graduate degree:
Minimum Passing Grade Per Course B-
CGPA 3.00
Total Required Credits 36

LEARN MORE ABOUT OUR GRADUATION REQUIREMENTS
1.  Students enrolled in the graduate program must maintain a Cumulative Grade Point Average (CGPA) of at least 3.0 out of 4.0 to qualify for the graduate degree, to remain in good standing, and to graduate.
2. The Maximum Time Frame (MTF) for completion of the graduate program is 54 credits.
3. A graduate student may transfer up to 50% of credits earned at accredited institutions.

Tuition & Fees

Note: Tuition rates are subject to change and additional fees may vary by program. Please call at (202) 644-2725 for more information.

Per Credit Hour                                                                     Yearly Tuition

$1,125                                                                                            $20,250






Be an Innovator,
Be a Leader,
At BAU!

Complete this form and a BAU Admission Advisor will contact you and provide further assistance.

Phuong Do

I love the experience here at Bay Atlantic University. The university is in the center of Washington D.C., the capital of the US. My friends and I have a wonderful time here at BAU and love the learning experience. It is really an honor to study in a high quality university that gives us top notch education, paving the way for success in our future careers.

Enkhjinzaya Ganbold

I love the fact that the university is so diverse.

Izel Ugur

The professors at Bay Atlantic University are diverse, not only in terms of their international backgrounds, but also their professional backgrounds. Being able to hear how the theories connect to their real-life experiences has been invaluable to my studies.

Qazi Khan

It is great to be a part of such an international environment in my everyday life because it has provided me with a different perspective of the world. And now I have good friends from many different countries.

Uyanga Batsukh

After completing the MBA Entrepreneurship program at BAU, I feel more confident in taking the next step towards starting my own business.

Daniel Giraldo

Great location, great staff, and great learning experience. Qualified teachers with an extended work experience.

Aghamirza Fazel

It has been a great experience here at BAU. Especially learning from the professors who are great and very helpful at any given circumstance. They are always friendly.

Mauricio Facciolla

I had great professors who taught me important skills and concepts that I applied daily in my job. These skills helped me to grow and stand out in the company I work for. The location and the building are awesome, providing great experiences. The student body is very diverse; great to learn about different cultures.

Phuong Vo, Vietnam

“I am a normal girl, but I have a big ambition. That’s living the truest and most beautiful life. I think the risk is always better than the regret. I am happy to be here at BAU and living a life I have always dreamed of. I prayed faithfully and worked hard for this opportunity. Moreover, thank you so much my beloved family for all their unlimited support and unconditional love. Thank you BAU for this opportunity!”