Degree Awarded: Master of Science (MS)
Calendar Type: Quarter
Minimum Required Credits: 45.0
Co-op Option: Available for full-time, on-campus master's-level students
Classification of Instructional Programs (CIP) code: 11.1003
Standard Occupational Classification (SOC) code: 15-1122
About the Program
As a greater percentage of people worldwide use computers, there is a marked increase in cybersecurity concerns. Motivated through discussions with the National Security Agency (NSA), Drexel University's MS in Cybersecurity program prepares students with both academic and practical training to be competitive in today's rapidly changing technical landscape. The program provides deeply technical and specialized training and enables graduates to understand, adapt, and develop new techniques to confront emerging threats in cybersecurity.
Administered by the Electrical & Computer Engineering Department in the College of Engineering, this program is interdisciplinary in nature and includes courses from Drexel University's College of Computing & Informatics. Topics covered include computer networking, probability concepts, techniques for analyzing algorithms, dependable software design, reverse software engineering, intrusion detection, ethics, privacy, confidentiality, authenticity, and social networking.
The program offers multidisciplinary "research rotations" as an independent study component of the degree program and an option to participate in the Graduate Co-op Program. For more information relating to Graduate Co-op, please see the Steinbright Career Development Center's website.
For more information about this program, please visit the ECE Department's Cybersecurity degree page.
Applicants must satisfy general requirements for graduate admission, including a minimum 3.00 GPA (on a 4.00 scale) for the last two years of undergraduate study, as well as for any subsequent graduate work. It is preferred, but not necessary, that applicants hold a bachelor's degree in an engineering or computer science discipline. Degrees must be earned from an accredited college or university. An undergraduate degree earned abroad must be deemed equivalent to a US bachelor's.
For full-time applicants, the GRE exam is optional. Students who do not hold a degree from a US institution must take the TOEFL or IELTS exam within two years of application submission.
For more information on how to apply, visit Drexel's Admissions page for Cybersecurity.
The Master of Science in Cybersecurity program encompasses a minimum of 45.0 approved credit hours, chosen in accordance with the requirements listed below. A plan of study should be arranged with the departmental graduate advisors, and in consultation with the student's research advisor, if applicable.
The required core courses provide students with a theoretical foundation in the field of cybersecurity and a framework to guide the application of knowledge gained in technical electives to the practice of cybersecurity.
|INFO 517||Principles of Cybersecurity||3.0|
|INFO 725||Information Policy and Ethics||3.0|
|SE 578||Security Engineering *||3.0|
|or INFO 712||Information Assurance|
|Cybersecurity Track-Specific Technical Electives||27.0|
Choose from lists below depending on track
|Cybersecurity Non-Track Technical Electives **||9.0|
Students in the Information Systems Track must take INFO 712.
Students in the Computer Science Track and Electrical & Computer Engineering must take SE 578.
If enrolled in the Computer Science Track, choose 3 courses (9.0 credits) from either Electrical & Computer Engineering Track or Information Systems Track Technical Electives list.
If enrolled in the Information Systems Track, choose 3 courses (9.0 credits) from either the Computer Science or Electrical & Computer Engineering Tracks.
If enrolled in the Electrical & Computer Engineering Track, choose 3 courses (9.0 credits) from either the Computer Science or Information Systems Tracks,
Computer Science Track Electives
|CS 500||Fundamentals of Databases||3.0|
|CS 501||Introduction to Programming||3.0|
|CS 502||Data Structures and Algorithms||3.0|
|CS 503||Systems Basics||3.0|
|CS 510||Introduction to Artificial Intelligence||3.0|
|CS 521||Data Structures and Algorithms I||3.0|
|CS 522||Data Structures and Algorithms II||3.0|
|CS 540||High Performance Computing||3.0|
|CS 543||Operating Systems||3.0|
|CS 544||Computer Networks||3.0|
|CS 550||Programming Languages||3.0|
|CS 551||Compiler Construction||3.0|
|CS 610||Advanced Artificial Intelligence||3.0|
|CS 612||Knowledge-based Agents||3.0|
|CS 613||Machine Learning||3.0|
|CS 621||Approximation Algorithms||3.0|
|CS 630||Cognitive Systems||3.0|
|CS 643||Advanced Operating Systems||3.0|
|CS 645||Network Security||3.0|
|CS 647||Distributed Systems Software||3.0|
|CS 650||Program Generation and Optimization||3.0|
|CS 695||Research Rotations in Cybersecurity||1.0-12.0|
|CS 741||Computer Networks II||3.0|
|CS 751||Database Theory||3.0|
|CS 759||Complexity Theory||3.0|
|CS 770||Topics in Artificial Intelligence||3.0|
|SE 575||Software Design||3.0|
|SE 576||Software Reliability and Testing||3.0|
|SE T680||Special Topics in Software Engineering||3.0|
Electrical & Computer Engineering Track Electives
|ECE 610||Machine Learning & Artificial Intelligence||3.0|
|ECE 687||Pattern Recognition||3.0|
|ECEC 500||Fundamentals Of Computer Hardware||3.0|
|ECEC 501||Computational Principles of Representation and Reasoning||3.0|
|ECEC 502||Principles of Data Analysis||3.0|
|ECEC 503||Principles of Decision Making||3.0|
|ECEC 511||Combinational Circuit Design||3.0|
|ECEC 512||Sequential Circuit Design||3.0|
|ECEC 513||Design for Testability||3.0|
|ECEC 520||Dependable Computing||3.0|
|ECEC 531||Principles of Computer Networking||3.0|
|ECEC 600||Fundamentals of Computer Networks||3.0|
|ECEC 621||High Performance Computer Architecture||3.0|
|ECEC 622||Parallel Programming||3.0|
|ECEC 623||Advanced Topics in Computer Architecture||3.0|
|ECEC 632||Performance Analysis of Computer Networks||3.0|
|ECEC 633||Advanced Topics in Computer Networking||3.0|
|ECEC 641||Web Security I||3.0|
|ECEC 642||Web Security II||3.0|
|ECEC 643||Web Security III||3.0|
|ECEC 661||Digital Systems Design||3.0|
|ECES 511||Fundamentals of Systems I||3.0|
|ECES 512||Fundamentals of Systems II||3.0|
|ECES 513||Fundamentals of Systems III||3.0|
|ECES 521||Probability & Random Variables||3.0|
|ECES 522||Random Process & Spectral Analysis||3.0|
|ECES 523||Detection & Estimation Theory||3.0|
|ECES 558||Digital Signal Processing for Sound & Hearing||3.0|
|ECES 559||Processing of the Human Voice||3.0|
|ECES 604||Optimal Estimation & Stochastic Control||3.0|
|ECES 607||Estimation Theory||3.0|
|ECES 620||Multimedia Forensics and Security||3.0|
|ECES 621||Communications I||3.0|
|ECES 622||Communications II||3.0|
|ECES 623||Communications III||3.0|
|ECES 631||Fundamentals of Deterministic Digital Signal Processing||3.0|
|ECES 632||Fundamentals of Statistical Digital Signal Processing||3.0|
|ECES 642||Optimal Control||3.0|
|ECES 643||Digital Control Systems Analysis & Design||3.0|
|ECES 644||Computer Control Systems||3.0|
|ECES 651||Intelligent Control||3.0|
|ECES 682||Fundamentals of Image Processing||3.0|
|ECES 685||Image Reconstruction Algorithms||3.0|
|ECES 811||Optimization Methods for Engineering Design||3.0|
|ECES 812||Mathematical Program Engineering Design||3.0|
|ECES 813||Computer-Aided Network Design||3.0|
|ECES 818||Machine Learning & Adaptive Control||3.0|
|ECES 821||Reliable Communications & Coding I||3.0|
|ECES 822||Reliable Communications & Coding II||3.0|
|ECES 823||Reliable Communications & Coding III||3.0|
|ECET 501||Fundamentals of Communications Engineering||3.0|
|ECET 511||Physical Foundations of Telecommunications Networks||3.0|
|ECET 512||Wireless Systems||3.0|
|ECET 513||Wireless Networks||3.0|
|ECET 602||Information Theory and Coding||3.0|
|ECET 603||Optical Communications and Networks||3.0|
|ECET 604||Internet Laboratory||3.0|
Information Systems Track Electives
|INFO 532||Software Development||3.0|
|INFO 540||Perspectives on Information Systems||3.0|
|INFO 590||Foundations of Data and Information||3.0|
|INFO 605||Database Management Systems||3.0|
|INFO 606||Advanced Database Management||3.0|
|INFO 607||Applied Database Technologies||3.0|
|INFO 624||Information Retrieval Systems||3.0|
|INFO 629||Applied Artificial Intelligence||3.0|
|INFO 633||Information Visualization||3.0|
|INFO 634||Data Mining||3.0|
|INFO 646||Information Systems Management||3.0|
|INFO 655||Intro to Web Programming||3.0|
|INFO 659||Introduction to Data Analytics||3.0|
|INFO 662||Metadata and Resource Description||3.0|
|INFO 670||Cross-platform Mobile Development||3.0|
|INFO 680||US Government Information||3.0|
|INFO 710||Information Forensics||3.0|
|INFO 712||Information Assurance *||3.0|
INFO 712 may not be used toward both track specific technical elective and core requirement.
Cybersecurity technical electives are used to build a deep understanding of one or more areas of technical expertise within the field of cybersecurity. All students are required to take a minimum of 18.0 credits of cybersecurity technical electives from the graduate course offerings of the Department of Computer Science, the Department of Computing and Security Technology, and the Department of Electrical and Computer Engineering [ECE]. A list of pre-approved technical electives can be found on the ECE Department website.
General electives are the remaining courses needed to reach the minimum credit hour requirement for the degree program. General electives can be chosen from among the graduate course offerings of the College of Computing & Informatics; the Department of Computer Science; the Department of Computing and Security Technology; the Department of Electrical and Computer Engineering, and the Department of Mathematics. In order to have courses outside of these departments and schools count towards degree completion, they must be approved by the departmental graduate advisors prior to registration for said courses.
Sample Plan of Study
|INFO 517||3.0||SE 578 or INFO 712*||3.0||INFO 725||3.0||VACATION|
|Track Elective||3.0||Track Electives||6.0||Track Elective||3.0|
|Non-Track Elective||3.0||Non-Track Elective||3.0|
|Track Electives||9.0||Track Electives||6.0|
|Total Credits 45|
Graduate Co-op/Career Opportunities
Students may choose to participate in the Graduate Co-op Program, working on curriculum related projects. Graduate Co-op enables graduate students to alternate class terms with a six-month period of hands-on experience, gaining access to employers in their chosen industries. Whether co-op takes students throughout the United States or abroad, they are expanding their professional networks, enhancing their resumes, and bringing that experience back to the classroom and their peers.
The program was deliberately designed to address needs of the Federal Cyber Service, the Department of Defense, and the National Security Agency. The program strengthens ties between these agencies and Drexel University and will provide professional opportunities for students pursuing this degree.
Students in the MS in Cybersecurity program have opportunities to perform research-oriented coursework for academic credit. Research-oriented coursework can be divided into three categories: research rotations, master’s thesis, and independent research.
A total of 9.0 credits of research-oriented coursework may be counted towards the minimum credit hour requirement of the degree program. These credits are considered general electives.
Drexel University and the Electrical and Computer Engineering Department are nationally recognized for a strong history of developing innovative research. Research programs in the ECE Department prepare students for careers in research and development, and aim to endow graduates with the ability to identify, analyze, and address new technical and scientific challenges. The ECE Department is well equipped with state-of-the-art facilities in each of the following ECE Research laboratories:
Research Laboratories at the ECE Department
Adaptive Signal Processing and Information Theory Research Group
The Adaptive Signal Processing and Information Theory Research Group conducts research in the area of signal processing and information theory. Our main interests are belief/expectation propagation, turbo decoding and composite adaptive system theory. We are currently doing projects on the following topics:
i) Delay mitigating codes for network coded systems,
ii) Distributed estimation in sensor networks via expectation propagation,
iii) Turbo speaker identification,
iv) Performance and convergence of expectation propagation,
v) Investigating bounds for SINR performance of autocorrelation based channel shorteners.
Applied Networking Research Lab
Applied Networking Research Lab (ANRL) projects focus on modeling and simulation as well as experimentation in wired, wireless and sensor networks. ANRL is the home of MuTANT, a Multi-Protocol Label Switched Traffic Engineering and Analysis Testbed composed of 10 high-end Cisco routers and several PC-routers, also used to study other protocols in data networks as well as automated network configuration and management. The lab also houses a sensor network testbed.
Uses computer gaming hardware for enhanced and affordable 3-D visualization, along with techniques from information theory and machine learning to combine the exquisite capabilities of the human visual system with computational sensing techniques for analyzing vast quantities of image sequence data.
Data Fusion Laboratory
The Data Fusion Laboratory investigates problems in multisensory detection and estimation, with applications in robotics, digital communications, radar, and target tracking. Among the projects in progress: computationally efficient parallel distributed detection architectures, data fusion for robot navigation, modulation recognition and RF scene analysis in time-varying environments, pattern recognition in biological data sequences and large arrays, and hardware realizations of data fusion architectures for target detection and target tracking.
Drexel Network Modeling Laboratory
The Drexel Network Modeling Laboratory investigates problems in the mathematical modeling of communication networks, with specific focus on wireless ad hoc networks, wireless sensor networks, and supporting guaranteed delivery service models on best effort and multipath routed networks. Typical methodologies employed in our research include mathematical modeling, computer simulation, and performance optimization, often with the end goal of obtaining meaningful insights into network design principles and fundamental performance tradeoffs.
Drexel Power-Aware Computing Laboratory
The Power-Aware Computing Lab investigates methods to increase energy efficiency across the boundaries of circuits, architecture, and systems. Our recent accomplishments include the Sigil profiling tool, scalable modeling infrastructure for accelerator implementations, microarchitecture-aware VDD gating algorithms, an accelerator architecture for ultrasound imaging, evaluation of hardware reference counting, hardware and operating system support for power-agile computing, and memory systems for accelerator-based architectures.
Drexel University Nuclear Engineering Education Laboratory
The field of nuclear engineering encompasses a wide spectrum of occupations, including nuclear reactor design, medical imaging, homeland security, and oil exploration. The Drexel University Nuclear Engineering Education Laboratory (DUNEEL) provides fundamental hands on understanding for power plant design and radiation detection and analysis. Software based study for power plant design, as well as physical laboratory equipment for radiation detection, strengthen the underlying concepts used in nuclear engineering such that the student will comprehend and appreciate the basic concepts and terminology used in various nuclear engineering professions. Additionally, students use the laboratory to develop methods for delivering remote, live time radiation detection and analysis. The goal of DUNEEL is to prepare students for potential employment in the nuclear engineering arena.
Drexel VLSI Laboratory
The Drexel VLSI Laboratory investigates problems in the design, analysis, optimization and manufacturing of high performance (low power, high throughput) integrated circuits in contemporary CMOS and emerging technologies. Suited with industrial design tools for integrated circuits, simulation tools and measurement beds, the VLSI group is involved with digital and mixed-signal circuit design to verify the functionality of the discovered novel circuit and physical design principles. The Drexel VLSI laboratory develops design methodologies and automation tools in these areas, particularly in novel clocking techniques, featuring resonant clocking, and interconnects, featuring wireless interconnects.
Drexel Wireless Systems Laboratory
The Drexel Wireless Systems Laboratory (DWSL) contains an extensive suite of equipment for constructing, debugging, and testing prototype wireless communications systems. Major equipment within DWSL includes:
- software defined radio network testbeds for rapidly prototyping new communications and network systems,
- electromagnetic anechoic chamber and reverberation chambers for testing new wireless technologies,
- experimental cell tower for field testing new wireless technologies.
The lab is also equipped with network analyzers, high speed signal generators, oscilloscopes, and spectrum analyzers as well as several Zigbee development platforms for rapidly prototyping sensor networks. The lab offers laboratory coursework in wireless network security, collaborative intelligent radio networks, and fundamental analog and digital communication systems.
Ecological and Evolutionary Signal-processing and Informatics Laboratory
The Ecological and Evolutionary Signal-processing and Informatics Laboratory (EESI) seeks to solve problems in high-throughput genomics and engineer better solutions for biochemical applications. The lab's primary thrust is to enhance the use of high-throughput DNA sequencing technologies with pattern recognition and signal processing techniques. Applications include assessing the organism content of an environmental sample, recognizing/classifying potential and functional genes, inferring environmental factors and inter-species relationships, and inferring microbial evolutionary relationships from short-read DNA/RNA fragments. The lab also investigates higher-level biological systems such as modeling and controlling chemotaxis, the movement of cells.
Electric Power Engineering Center
This newly established facility makes possible state-of-the-art research in a wide variety of areas, ranging from detailed theoretical model study to experimental investigation in its high voltage laboratories. The mission is to advance and apply scientific and engineering knowledge associated with the generation, transmission, distribution, use, and conservation of electric power. In pursuing these goals, this center works with electric utilities, state and federal agencies, private industries, nonprofit organizations and other universities on a wide spectrum of projects. Research efforts, both theoretical and experimental, focus on the solution of those problems currently faced by the electric power industry. Advanced concepts for electric power generation are also under investigation to ensure that electric power needs will be met at the present and in the future.
Electronic Design Automation Facility
Industrial-grade electronic design automation software suite and intergrated design environment for digital, analog and mixed-signal systems development. Field Programmable Gate Array (FPGA) development hardware. Most up-to-date FPGA/embedded system development hardware kits. Printed circuit board production facility. Also see Drexel VLSI Laboratory.
Microwave-Photonics Device Laboratories
The laboratory is equipped with test and measurement equipment for high-speed analog and digital electronics and fiber optic systems. The test equipment includes network analyzers from Agilent (100kHz- 1.3 GHz and 45 Mhz-40 GHz), and Anritsu (45 MHz-6 GHz); spectrum analyzers from Tektronix, HP, and Agilent with measurement capability of DC to 40 GHz and up to 90 GHz using external mixers; signal generators and communication channel modulators from HP, Rhode-Schwartz, Systron Donner, and Agilent; microwave power meter and sensor heads, assortment of passive and active microwave components up to 40 GHz ; data pattern generator and BER tester up to 3Gb/s; optical spectrum analyzer from Anritsu and power meters from HP; single and multimode fiber optic based optical transmitter and receiver boards covering ITU channels at data rates up to 10Gb/s; passive optical components such as isolator, filter, couplers, optical connectors and fusion splicer; LPKF milling machine for fabrication of printed circuit boards; wire-bonding and Cascade probe stations; Intercontinental test fixtures for testing of MMIC circuits and solid-state transistors; state-of-the-art microwave and electromagnetic CAD packages such as Agilent ADS, ANSYS HFSS, and COMSOL multi-physics module.
Multimedia & Information Security Laboratory
The Multimedia & Information Security Laboratory (MISL) conducts research that provides information verification and security in scenarios when an information source cannot be trusted.
The majority of MISL's research is in digital multimedia forensics. Digital multimedia forensics involves the developing mathematical techniques to identify multimedia forgeries such as falsified images and videos. This research is particularly important because widely available editing software enables multimedia forgers to create perceptually realistic forgeries. MISL performs research on anti-forensic operations designed to fool forensic techniques. By studying anti-forensics, researchers can identify and address weaknesses in existing forensic techniques as well as develop techniques capable of identifying the use of anti-forensics.
Music and Entertainment Technology Laboratory
The Music and Entertainment Technology Laboratory (MET-lab) is devoted to research in digital media technologies that will shape the future of entertainment, especially in the areas of sound and music. We employ digital signal processing and machine learning to pursue novel applications in music information retrieval, music production and processing technology, and new music interfaces. The MET-lab is also heavily involved in outreach programs for K-12 students and hosts the Summer Music Technology program, a one-week learning experience for high school students. Lab facilities include a sound isolation booth for audio and music recording, a digital audio workstation running ProTools, two large multi-touch display interfaces of our own design, and a small computing cluster for distributed processing.
Our research is primarily in the area of nanophotonics with a focus on the nanoscale interaction of light with matter. Interests include: liquid crystal/polymer composites for gratings, lenses and HOEs; liquid crystal interactions with surfaces and in confined nanospaces; alternative energy generation through novel photon interactions; ink-jet printed conducting materials for RF and photonic applications; and the creation and development of smart textiles technologies including soft interconnects, sensors, and wireless implementations.
This lab concentrates on the system integration on optics, electronics, and mechanical components and systems, for applications in imaging, communication, and biomedical research. Research areas include: Programmable Imaging with Optical Micro-electrical-mechanical systems (MEMS), in which microscopic mirrors are used to image light into a single photodetector; Pre-Cancerous Detection using White Light Spectroscopy, which performs a cellular size analysis of nuclei in tissue; Free-space Optical Communication using Space Time Coding, which consists of diffused light for computer-to-computer communications, and also tiny lasers and detectors for chip-to-chip communication; Magnetic Particle Locomotion, which showed that particles could swim in a uniform field; and Transparent Antennas using Polymer, which enables antennas to be printed through an ink-jet printer.
Plasma and Magnetics Laboratory
Research is focused on applications of electrical and magnetic technologies to biology and medicine. This includes the subjects of non-thermal atmospheric pressure plasma for medicine, magnetic manipulation of particles for drug delivery and bio-separation, development of miniature NMR sensors for cellular imaging and carbon nanotube cellular probes.
Power Electronics Research Laboratory
The Power Electronics Research Laboratory (PERL) is involved in circuit and design simulation, device modeling and simulation, and experimental testing and fabrication of power electronic circuits. The research and development activities include electrical terminations, power quality, solar photovoltaic systems, GTO modeling, protection and relay coordination, and solid-state circuit breakers. The analysis tools include EMPT, SPICE, and others, which have been modified to incorporate models of such controllable solid-state switches as SCRs, GTOs, and MOSFETs. These programs have a wide variety and range of modeling capabilities used to model electromagnetics and electromechanical transients ranging from microseconds to seconds in duration. The PERL is a fully equipped laboratory with 42 kVA AC and 70 kVA DC power sources and data acquisition systems, which have the ability to display and store data for detailed analysis. Some of the equipment available is a distribution and HV transformer and three phase rectifiers for power sources and digital oscilloscopes for data measuring and experimental analysis. Some of the recent studies performed by the PERL include static VAR compensators, power quality of motor controllers, solid-state circuit breakers, and power device modeling which have been supported by PECO, GE, Gould, and EPRI.
Privacy, Security and Automation Lab
Drexel University's Privacy, Security, and Automation Laboratory (PSAL) researches on topics at the intersection between artificial intelligence, privacy and security, and human-computer interaction.
RE Touch Lab
The RE Touch Lab is investigating the perceptual and mechanical basis of active touch perception, or haptics, and the development of new technologies for stimulating the sense of touch, allowing people to touch, feel, and interact with digital content as seamlessly as we do with objects in the real world. We study the scientific foundations of haptic perception and action, and the neuroscientific and biomechanical basis of touch, with a long-term goal of uncovering the fundamental perceptual and mechanical computations that enable haptic interaction. We also create new technologies for rendering artificial touch sensations that simulate those that are experienced when interacting with real objects, inspired by new findings on haptic perception.
Testbed for Power-Performance Management of Enterprise Computing Systems
This computing testbed is used to validate techniques and algorithms aimed at managing the performance and power consumption of enterprise computing systems. The testbed comprises a rack of Dell 2950 and Dell 1950 PowerEdge servers, as well as assorted desktop machines, networked via a gigabit switch. Virtualization of this cluster is enabled by VMWare's ESX Server running the Linux RedHat kernel. It also comprises of a rack of ten Apple Xserve machines networked via a gigabit switch. These servers run the OS X Leopard operating systems and have access to a RAID with TBs of total disk capacity.