This course consists of a sustained study of ethical and legal issues that arise in relation to employment in the public and private sectors, including allocation of resources, corporate and social responsibility, relationships, and discrimination. A main focus of this course will be on the ethical and legal standards governing information technology. New technology creates ethical challenges for individuals around the globe and applies to most persons regardless of whether they are employed in the information technology field or a more traditional occupation. The study of Cyber Ethics provides a framework for making ethical decisions that professionals are likely to encounter in the workplace. This course will not only focus on ethics but on the legal, economic, social, cultural and global impacts of decisions that are made in the context of professional occupations.
Course Catalogue
The overview of Principles of Forensics and IR, Data Collection Techniques, Forensic Hardware, Chain of Custody, Basic Incident Response Process, Pre-Incident Preparation, Documentation Requirements, Common Approaches, Containment and Remediation Strategies, Malware Footprints, Data Volatility, Installed Software and Hotfixes, Persistence Mechanisms, Windows Audit Policies, Malware Analysis, Prefetch Analysis, The Windows Registry, Windows Event Log Analysis, File Carving, Email Header Analysis, Determining File Headers, Extraction of Attachments, Extracting Specific File Types, Deleted Files and Recovery, Use of Hash Sets, Adding Hash Sets, Advantages of Timeline, Timeline Creation, Sources of Network Data, PCAP Analysis with Wireshark, Network Footprint Basics of Memory Acquisition and Analysis, Highlight Power of Memory, Live Response Best Practices and Order of Volatility, Following the Process Tree and Unix/Linux File Permissions.
As necessary.
Background, history, classifications, programming languages for embedded systems. Combinational logic and transistors, RT-level combinational and sequential components, customized single purpose processor design. Structure of microcontrollers, CPU, memory and I/O structure, various microcontrollers, ARM. I/O and memory mapping, addressing modes, interrupts and traps, bus protocols, DMA, system bus configurations, RAM, ROM, SDRAM, flash, basic I/O interfaces. Parallel ports, LEDs, pushbutton, keypad, 7-segment display, LCD display, touchscreen, timers and counters, serial Interface, networked embedded systems. C-language primer, state machines, streams, circular buffers. Development environment, hardware/software debugging techniques, performance analysis, use of hardware debugging modules. CPU and hardware acceleration, multiprocessor performance analysis. Design methodologies and flows, requirement analysis, specifications description, system analysis and architecture design, quality assurance.
Lab works based CSE 4441.
This course covers general introductory concepts in the design and implementation of distributed systems, covering all the major branches such as Cloud Computing, Grid Computing, Cluster Computing, Supercomputing, and Many-core Computing. The specific topics that this course will cover are: scheduling in multiprocessors, memory hierarchies, synchronization, concurrency control, fault tolerance, data parallel programming models, scalability studies, distributed memory message passing systems, shared memory programming models, tasks, dependence graphs and program transformations, parallel I/O, applications, tools (Cuda, Swift, Globus, Condor, Amazon AWS, OpenStack, Cilk, gdb, threads, MPICH, OpenMP, Hadoop, FUSE), SIMD, MIMD, fundamental parallel algorithms, parallel programming exercises, parallel algorithm design techniques, interconnection topologies, heterogeneity, load balancing, memory consistency model, asynchronous computation, partitioning, determinacy, Amdahl's Law, scalability and performance studies, vectorization and parallelization, parallel programming languages, and power.
System Models- Entities, Attributes, States, Activities, Types of Models, Static & Dynamic Models, Deterministic & Stochastic Activities. Principles used in Modeling. System Simulation Continuous & Discrete event simulation Languages- GPSS, SIMULA, CSMP, DYNAMO. Probability concepts in Simulation- Random number, stochastic processes, Birth-Death process. Parameter estimation & input/output validation. Statistical Hypothesis Testing. Queuing Systems, M/M/I & M/M./m queues, Bulk arrival & Bulk service systems. Queuing networks. Computational algorithms & approximation techniques. Workload characterization & performance evaluation of computer systems. Evaluation of program performance. Case studies.
Lab works based CSE 4445.
Basics of Robotics and Linear Algebra, Representing positions and rotations, Rotational transformations and parameterizations of rotations, Homogeneous transformations, kinematic chains and Denavit–Hartenberg (DH) convention, DH convention and forward kinematics, Inverse kinematics and angular velocity, Jacobian, Trajectory design and configuration space, Configuration space with examples and motion planning introduction, Motion planning: potential field and Probabilistic Roadmaps (PRM).
Cloud Computing has transformed the IT industry by opening the possibility for infinite or at least highly elastic scalability in the delivery of enterprise applications and software as a service (SaaS). Amazon Elastic Cloud, Microsoft’s Azure, Google App Engine, and many other Cloud offerings give mature software vendors and new start-ups the option to deploy their applications to systems of infinite computational power with practically no initial capital investment and with modest operating costs proportional to the actual use. The course examines the most important APIs used in the Amazon and Microsoft Cloud, including the techniques for building, deploying, and maintaining machine images and applications. We will learn how to use Cloud as the infrastructure for existing and new services. We will use open source implementations of highly available clustering computational environments, as well as RESTful Web services, to build very powerful and efficient applications. We also learn how to deal with not trivial issues in the Cloud, such as load balancing, caching, distributed transactions, and identity and authorization management.