500

Introduction to Computer Networks will be provided. Activities involved in deploying, configuring, administering, operating and managing networks will be a part of this course. Topics such as Fault Management, Configuration Management, Performance Management, Security Management and Account Management will be discussed in addition to System Administration. The course will include study of protocols involved and hands-on lab exercises to understanding working of the protocols and other concepts related to Network Management and System Administration. An introduction to Software Defined Networks will be a part of this course including hands-on exercises.

Security control types, Need to know and least privilege, Access control models, Identification and authentication, User account provisioning, Access control methods, Biometrics, Multi-factor techniques, SSO technologies, Security operations, Change and configuration management, Privilege management, Incident response and investigation, Backup and Recovery operations, Application Security testing, client-server app vulnerabilities, secure SDLC, Database security.

Introduction to Network Security. Network attacks. Secure network architecture. VLANs. NAT. VPNs. Firewalls. Packet inspection. Ingress/Egress filtering. Intrusion detection. Intrusion prevention. Network encryption.

Probability theory, Symmetric and asymmetric cryptography, Common cryptographic algorithms, Steganography, Hashing and Message Digests, Key Management, Public Key Infrastructure and certificate management, Cryptanalysis and Cryptographic attacks, Standard cryptographic tools.

Quality Assurance, Maturity models, Change management, Asset management, Security policies, Security management, Threat profiling and risk analysis, Risk management techniques, Business continuity planning, Disaster recovery, Regulatory compliance, HIPAA and PCI requirements, legal issues, Computer crime and criminal investigations, Privacy and Ethics.

Introduction to penetration testing, Penetration testing methodology, reconnaissance, Google hacking, email harvesting, Open source intelligence and social media, enumeration, DNS enumeration, Port scanning, Vulnerability assessments, exploits and exploit development, bypassing antivirus, Post-exploitation techniques, Privilege escalation, Password retrieval and cracking, Pivoting, Web application hacking, SQL Injection, Cross-site scripting, Cross-site request forgery, Local and remote file inclusion.

Designing client-server application with sockets; traffic analysis; building concurrent and multi-service servers; designing network protocols; measuring and analyzing performance of protocols. Students will complete a number of programming and network analysis experiments during the semester. Background assumed: Data Communication and Networks II or equivalent.

Review of contemporary operating systems (OS), OS design principles and strategies; examination of communication and synchronization protocols; concurrent processes and process scheduling including their statistical analysis; distributed operating systems; client-server computing model; distributed resource management; multiprocessor OS; failure, recovery and fault tolerance; data security; applications. Background assumed: Introduction to Operating Systems or equivalent.

Topics include: time and space complexity; verification of correctness; advanced algorithm design strategies (iterative, divide-and-conquer, greedy methods, dynamic programming, branch-and-bound, etc., with specific examples drawn from sorting, searching, graph theory, matrix and polynomial arithmetic, and cryptography); hard problems and approximation algorithms, with examples such as napsack, bin-packing, and graph coloring problems; introduction to parallel algorithms as time permits. Background assumed: Mathematical Structures and Proof and Data Structures.

Typical topics include: Red-Black trees; AVL trees; B trees; B+ trees; B* trees; tries; splay trees; spatial data structures; self-organizing lists; summation techniques; recurrence relations, including establishing bounds and expanding recurrences; hashing and other complex indices; complexity of searching on various structures. Background assumed: Data Structures.

The course exposes students to a wide range of state-of-the-art research and techniques in the field of computational biology. This is a modern discipline dealing with the discovery and implementation of algorithms facilitating the understanding of biological processes. Various statistical, heuristic, and machine learning methods are used for this purpose, as well as graphical tools to visualize the objects. The course is intended to present some biological problems related to the human genome and the computational methods to resolve them. It will cover an introduction to computational biology, the use of computational methods to search for, classify, analyze, and model protein sequences, i.e. to convert the masses of information from biochemical experiments into useful information.

A variable topics course in computer science. Topics normally not covered in Computer Science or Computer Information Systems undergraduate degree programs but suitable to explore at length at graduate and senior level. Project and a formal presentation are required. Prerequisite: CSIT 341 or equivalent background knowledge and permission of instructor.