This Course Is Designed to Allow Students to Develop Projects On Multidisciplinary Topics That Link Between Advanced Topics In Computer Structure (with Emphasis On Riscv), Open Accelerators For Machine Learning and Use of Deep Learning to Solve System Security Issues . As The Course Covers Topics and Skills From Different Fields, at The Beginning of The Course, We Will Meet With Each Team Separately and Go Over The Materials That Form The Basis For The Project. Then We Will Move to The Second Stage Where Each Team Of Students Will Develop The Project They Have Chosen. at The End of The Course, Each Team Will Present Their Project to The Rest of The Class And Each Team Will Deliver a Project Book . Learning Outcomes# By The End of The Course The Students Will Be Able To# 1. Have a Deep Understanding of The Fundamental Materials On Which The Project Is Based, Such As Riscv Processor Structure, Algorithms Based On Deep Learning. 2. Use Advanced Developing Tools Such As Development of an Fpga-based Systems. 3. Use Software and Hardware Tools to Perform Security Attacks. 4. Develop Machine Learning Based Algorithms For Reverse Engineering Implementation. 5. Develop Machine Learning Based Algorithms to Find Security Vulnerabilities. 6. Conduct Scientific Experiments. 7. Prove By Statistical Methods Whether a Claim Is Valid Or Refuted. 8. Build a Model Or S Prototype at The End of The Project. 9. Write a Short Article (or a Full Article If The Results Justify It, And Submit It For Publication ).

Faculty: Computer Science
|Undergraduate Studies |Graduate Studies
Pre-required courses

(44252 - Digital Systems and Computer Structure and 46267 - Computer Architecture and 236267 - Computer Architecture)

Course with no extra credit

236008 - Topics in Al For Hardware Security