Cybersecurity MS

Major: Cybersecurity
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 visit COE Graduate Co-op, and the Steinbright Career Development Center's website.

Additional Information

For more information about this program, please visit the ECE Department's Cybersecurity degree page.

Admission Requirements

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.

Additional Information

For more information on how to apply, visit Drexel's Admissions page for Cybersecurity.

Degree Requirements

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.

Core Courses
INFO 517Principles of Cybersecurity3.0
INFO 725Information Policy and Ethics3.0
SE 578Security Engineering *3.0
or INFO 712 Information Assurance
Cybersecurity Track-Specific Technical Electives27.0
Choose from lists below depending on track
Cybersecurity Non-Track Technical Electives **9.0
Optional Co-op Experience ***0-1
Career Management and Professional Development for Master's Degree Students
Total Credits45.0-46.0
*

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,

***

Co-op is an option for this degree for full-time on-campus students. To prepare for the 6-month co-op experience, students will complete: COOP 500. The total credits required for this degree with the co-op experience is 46.0

Students not participating in the co-op experience will need 45.0 credits to graduate.

Computer Science Track Electives

CS 500Fundamentals of Databases3.0
CS 501Introduction to Programming3.0
CS 502Data Structures and Algorithms3.0
CS 503Systems Basics3.0
CS 504Introduction to Software Design3.0
CS 510Introduction to Artificial Intelligence3.0
CS 521Data Structures and Algorithms I3.0
CS 522Data Structures and Algorithms II3.0
CS 523Cryptography3.0
CS 540High Performance Computing3.0
CS 543Operating Systems3.0
CS 544Computer Networks3.0
CS 550Programming Languages3.0
CS 551Compiler Construction3.0
CS 590Privacy3.0
CS 610Advanced Artificial Intelligence3.0
CS 612Knowledge-based Agents3.0
CS 613Machine Learning3.0
CS 621Approximation Algorithms3.0
CS 630Cognitive Systems3.0
CS 643Advanced Operating Systems3.0
CS 645Network Security3.0
CS 647Distributed Systems Software3.0
CS 650Program Generation and Optimization3.0
CS 741Computer Networks II3.0
CS 751Database Theory3.0
CS 759Complexity Theory3.0
CS 770Topics in Artificial Intelligence3.0
SE 575Software Design3.0
SE 576Software Reliability and Testing3.0
SE T680Special Topics in Software Engineering3.0

Electrical & Computer Engineering Track Electives

ECE 610Machine Learning & Artificial Intelligence3.0
ECE 612Applied Machine Learning Engineering3.0
ECE 613Neuromorphic Computing3.0
ECE 506Hands on Computer Networks3.0
ECE 687Pattern Recognition3.0
ECEC 500Fundamentals Of Computer Hardware3.0
ECE T580Special Topics in ECE0.0-12.0
ECE 630Software Defined Radio Laboratory3.0
ECEC 571Introduction to VLSI Design3.0
ECEC 576Hardware Security & Trust3.0
ECEC T580Special Topics in ECEC0.0-12.0
ECES 681Fundamentals of Computer Vision3.0
ECEC 501Computational Principles of Representation and Reasoning3.0
ECEC 502Principles of Data Analysis3.0
ECEC 503Principles of Decision Making3.0
ECEC 511Combinational Circuit Design3.0
ECEC 512Sequential Circuit Design3.0
ECEC 513Design for Testability3.0
ECEC 520Dependable Computing3.0
ECEC 531Principles of Computer Networking3.0
ECEC 600Fundamentals of Computer Networks3.0
ECEC 621High Performance Computer Architecture3.0
ECEC 622Parallel Programming3.0
ECEC 623Advanced Topics in Computer Architecture3.0
ECEC 632Performance Analysis of Computer Networks3.0
ECEC 633Advanced Topics in Computer Networking3.0
ECEC 641Web Security I3.0
ECEC 642Web Security II3.0
ECEC 643Web Security III3.0
ECEC 661Digital Systems Design3.0
ECES 511Fundamentals of Systems I3.0
ECES 512Fundamentals of Systems II3.0
ECES 513Fundamentals of Systems III3.0
ECES 521Probability & Random Variables3.0
ECES 522Random Process & Spectral Analysis3.0
ECES 523Detection & Estimation Theory3.0
ECES 558Digital Signal Processing for Sound & Hearing3.0
ECES 559Processing of the Human Voice3.0
ECES 604Optimal Estimation & Stochastic Control3.0
ECES 607Estimation Theory3.0
ECES 620Multimedia Forensics and Security3.0
ECES 621Communications I3.0
ECES 622Communications II3.0
ECES 623Communications III3.0
ECES 631Fundamentals of Deterministic Digital Signal Processing3.0
ECES 632Fundamentals of Statistical Digital Signal Processing3.0
ECES 641Bioinformatics3.0
ECES 642Optimal Control3.0
ECES 643Digital Control Systems Analysis & Design3.0
ECES 644Computer Control Systems3.0
ECES 651Intelligent Control3.0
ECES 682Fundamentals of Image Processing3.0
ECES 685Image Reconstruction Algorithms3.0
ECES 811Optimization Methods for Engineering Design3.0
ECES 812Mathematical Program Engineering Design3.0
ECES 813Computer-Aided Network Design3.0
ECES 818Machine Learning & Adaptive Control3.0
ECES 821Reliable Communications & Coding I3.0
ECES 822Reliable Communications & Coding II3.0
ECES 823Reliable Communications & Coding III3.0
ECET 501Fundamentals of Communications Engineering3.0
ECET 511Physical Foundations of Telecommunications Networks3.0
ECET 512Wireless Systems3.0
ECET 513Wireless Networks3.0
ECET 602Information Theory and Coding3.0
ECET 603Optical Communications and Networks3.0
ECET 604Internet Laboratory3.0

Information Systems Track Electives

CS 501Introduction to Programming3.0
CS 502Data Structures and Algorithms3.0
CS 503Systems Basics3.0
CS 504Introduction to Software Design3.0
CS 570Programming Foundations3.0
CT 500Introduction to the Digital Environment3.0
CT 600Cloud Technology3.0
CT 605Cloud Security and Virtual Environments3.0
CT 610Disaster Recovery, Continuity Planning and Digital Risk Assessment3.0
CT 620Security, Policy and Governance3.0
DSCI 501Quantitative Foundations of Data Science3.0
DSCI 511Data Acquisition and Pre-Processing3.0
DSCI 521Data Analysis and Interpretation3.0
DSCI 632Applied Cloud Computing3.0
INFO 508Information Innovation through Design Thinking3.0
INFO 532Software Development3.0
INFO 540Perspectives on Information Systems3.0
INFO 590Foundations of Data and Information3.0
INFO 600Web Systems & Architecture3.0
INFO 605Database Management Systems3.0
INFO 606Advanced Database Management3.0
INFO 607Applied Database Technologies3.0
INFO 608Human-Computer Interaction3.0
INFO 615Designing with Data3.0
INFO 616Social and Collaborative Computing3.0
INFO 620Information Systems Analysis and Design3.0
INFO 623Social Network Analytics3.0
INFO 624Information Retrieval Systems3.0
INFO 629Applied Artificial Intelligence3.0
INFO 633Information Visualization3.0
INFO 634Data Mining3.0
INFO 646Information Systems Management3.0
INFO 648Healthcare Informatics3.0
INFO 655Intro to Web Programming3.0
INFO 659Introduction to Data Analytics3.0
INFO 662Metadata and Resource Description3.0
INFO 670Cross-platform Mobile Development3.0
INFO 680US Government Information3.0
INFO 690Understanding Users: User Experience Research Methods3.0
INFO 691Prototyping the User Experience3.0
INFO 692Explainable Artificial Intelligence3.0
INFO 710Information Forensics3.0
INFO 712Information 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

Full Time, No CO-OP

First Year
FallCreditsWinterCreditsSpringCreditsSummerCredits
INFO 5173.0SE 578 or INFO 712*3.0INFO 7253.0VACATION
Track Elective3.0Track Electives6.0Track Elective3.0 
Non-Track Elective3.0 Non-Track Elective3.0 
 9 9 9 0
Second Year
FallCreditsWinterCredits  
Track Electives9.0Track Electives6.0  
 Non-Track Elective3.0  
 9 9  
Total Credits 45
*

Students in the Information Systems Track must take INFO 712.

Students in the Computer Science Track and Electrical & Computer Engineering must take SE 578.

Full Time With CO-OP (Information Systems Track)

First Year
FallCreditsWinterCreditsSpringCreditsSummerCredits
COOP 5001.0INFO 7253.0Track Elective Courses6.0INFO 712 or SE 578*3.0
INFO 5173.0Track Elective Courses6.0Non-Track Elective Course3.0Track Elective Courses6.0
Track Elective Course3.0   
Non-Track Elective Course3.0   
 10 9 9 9
Second Year
FallCreditsWinterCreditsSpringCredits 
COOP EXPERIENCECOOP EXPERIENCETrack Elective Courses6.0 
  Non-Track Elective Course3.0 
 0 0 9 
Total Credits 46
*

Students in the Information Systems Track must take INFO 712.

Students in the Computer Science Track and Electrical & Computer Engineering must take SE 578.

Full Time With CO-OP (Computer Science & ECE Tracks)

First Year
FallCreditsWinterCreditsSpringCreditsSummerCredits
COOP 5001.0INFO 7253.0Track Elective Courses6.0Track Elective Courses9.0
INFO 5173.0SE 578 or INFO 712*3.0Non-Track Elective Course3.0 
Track Elective Course3.0Track Elective Course3.0  
Non-Track Elective Course3.0   
 10 9 9 9
Second Year
FallCreditsWinterCreditsSpringCredits 
COOP EXPERIENCECOOP EXPERIENCETrack Elective Courses6.0 
  Non-Track Elective Course3.0 
 0 0 9 
Total Credits 46
*

Students in the Information Systems Track must take INFO 712.

Students in the Computer Science Track and Electrical & Computer Engineering must take SE 578.

Graduate Co-op/Career Opportunities

Graduate Co-Op

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.

Further information on the Graduate Co-Op Program is available at the Drexel Steinbright Career Development Center.

Career Opportunities

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.

Research

Students in the MS in Cybersecurity program have opportunities to perform research-oriented coursework for academic credit. Research-oriented coursework can bdivided 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.

Facilities

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.

Bioimage Laboratory

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.

NanoPhotonics+ Lab

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.

Opto-Electro-Mechanical Laboratory

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.

Cybersecurity Faculty

Kapil Dandekar, PhD (University of Texas-Austin) Director of the Drexel Wireless Systems Laboratory (DWSL); Associate Dean of Research, College of Engineering. Professor. Cellular/mobile communications and wireless LAN; smart antenna/MIMO for wireless communications; applied computational electromagnetics; microwave antenna and receiver development; free space optical communication; ultrasonic communication; sensor networks for homeland security; ultrawideband communication.
Constantine Katsinis, PhD (University of Rhode Island). Teaching Professor. High-performance computer networks, parallel computer architectures with sustained teraflops performance, computer security, image processing.
Steven Weber, PhD (University of Texas-Austin) Department Head. Professor. Mathematical modeling of computer and communication networks, specifically streaming multimedia and ad hoc networks.
Christopher C. Yang, PhD (University of Arizona). Professor. Web search and mining, security informatics, knowledge management, social media analytics, cross-lingual information retrieval, text summarization, multimedia retrieval, information visualization, information sharing and privacy, artificial intelligence, digital library, and electronic commerce.