Courses | VD Academic Affairs

Three-dimensional transformations and perspective systems and techniques for displaying and shading solid areas, hidden-element removal, display device characteristics, device independent systems, and user interface design.

Introduction to the issues of privacy and data protection, information collection, cookies, profiling, traffic monitoring analysis, data mining, data matching, surveillance technology, censorship, encryption, identification, anonymity, codes and policies, law, privacy in workplace, and ethical issues.

This course concentrates on recent research in computing that affects future directions in science, engineering and technology, hence upon modern society. For example, studying standers (e.g., E- Commerce technologies, and software life cycle processes such as ISO/IEC 12207) have immense effect on industry and society. Students explore such topics through conducting research. The course introduces skills necessary for research including surveying, scrutinizing methods and outcomes, designing tools, and preparing technical manuscripts.

Introduction to Machine Learning

Introduction to AI. History of AI. Knowledge representation: First order logic, Predicate logic, and Semantic net. Blind search. Heuristic search. Machine planning. Machine learning. Agents. Natural language processing.

Advanced AI topics will be discussed in-depth. Student will survey recent research in topics such as, but not limited to, natural language processing, cognitive modeling techniques, machine learning techniques, evolutionary algorithms, fuzzy logic, expert systems, robotics, knowledge system engineering (knowledge-based software engineering), and neural network computing.

Database management systems architecture; conceptual database models; relational, semantic, object-oriented, and object-relational databases; implementation techniques for database systems; file organization and data placement techniques; query processing; concurrency control; rollback and recovery techniques; integrity and consistency; transaction processing.

Design and implementation of database management systems in support of advanced technologies and applications, such as: geographical information systems (GIS) temporal and spatial databases, multimedia databases data mining data warehousing, distributed database systems, or other advanced topics in the area of database and information systems. We will focus on current issues in database and information system design.

Fundamental and emerging technologies such as networking infrastructures, data management tools, application servers, design tools, security systems, personalization tools, and electronic payment systems; case studies dealing with the existing business models and business processes; design and implementation of a major E-Commerce project using the state of the art tools. Proficiency in an object-Oriented programming language (such as Java) is expected from all students.

Overview of data representation, hexadecimal representation and different file type representations. Review on assembly language and code reverse engineering. Digital Forensics lab requirements. Digital Forensic process: technical and legal aspects. Types of Digital evidences. Extracting evidences from different OS platforms. Overview of network, Email, database and mobile Forensics. Students will be exposed to reverse engineering and code analysis. Students will do exercises on several Forensics tools.

This course will study approaches, mechanisms, and tools used to make software systems more secure. We will motivate the study by discussing common software security vulnerabilities such as buffer overflows, cross-site scripting and injection attacks. Then we will look at architectural approaches to building secure software (e.g., confinement, virtual machines, trusted computing), secure design principles and patterns, software analysis, secure programming techniques, run-time enforcement of security policies, code reviews and security testing. The course will also cover topics such as the importance of usability to building secure software systems.

Overview of security management: assets, vulnerabilities, threats, attacks, security tools, models and procedures. Role of policy making in the context of information security. Common practices to risk management and analysis. Fundamentals of cryptology, secure networking and access control. Problems and potential solutions associated with designing and implementing operating system and application security. Frameworks commonly used for governance and compliance control. Incident and disaster response.

Reviews regular expressions and finite automata. studies turning machines and equivalent models of computation, the Chomsky hierarchy, context-free grammars, push-down automata, and computability. Machine models of effective computability; sub-recursive hierarchies; P and NP problems; effective and efficient reducibility; time, space, and abstract complexity.

Distributed system examples, implementation issues, parallel vs. distributed systems, review of communication and networking, distributed system models, message-passing vs. shared memory models, synchronous vs, asynchronous systems, guarded actions non-determinism, atomic operations, scheduling and fairness issues, program correctness, safety and liveness properties, distributed mutual exclusion, distributed snapshot, distributed reset, wave algorithms, termination detetction, distributed deadlock, randomized algorithms, synchronous message passing, Hoare's CSP, clients and servers, faults in distributed systems, classification of faults, fault masking vs. fault recovery, self-stabilizing and adaptive distributed systems, gracefully degradable systems, waitfree systems, distributed consensus, leader election, clock synchronization.

Computer Security