ece 7970 machine learning in cyber security
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ECE 7970 Machine Learning in Cyber Security Chapter 0: Important - PowerPoint PPT Presentation

ECE 7970 Machine Learning in Cyber Security Chapter 0: Important information Dr. Mohamed Mahmoud Dr. Mostafa Fouda 1 - Course I nform ation I nstructors : Dr. Mohamed M. E. A. Mahmoud Office: Brown Hall - 332 E-mail:


  1. ECE 7970 – Machine Learning in Cyber Security Chapter 0: Important information Dr. Mohamed Mahmoud Dr. Mostafa Fouda

  2. 1 - Course I nform ation I nstructors : Dr. Mohamed M. E. A. Mahmoud Office: Brown Hall - 332 E-mail: mmahmoud@tntech.edu Homepage: http: / / www.cae.tntech.edu/ ~ mmahmoud/ Dr. Mostafa M. Fouda Office: Brown Hall - 331 E-mail: mfouda@tntech.edu Lectures : Mondays and Wednesdays, 4: 30 to 5: 50 in Brown 314 Course w ebsite https://www.cae.tntech.edu/~mmahmoud/teaching_files/grad/MLCybersecurity/MLCy bersecurity.html 0 - 1

  3. 2 - Feedback We strongly welcome feedback on how to improve teaching this course. Feel free to talk to me or email me. Do not hesitate to contact us if you have any question or problem 0 - 2

  4. 3 - Course Description Prerequisites: 1. Knowledge of linear algebra, probability, statistics and calculus. 2. Knowledge of basic programming skills. 3. Knowledge of machine learning concepts. 4. Knowledge of basic security concepts and cryptography primitives. #3 was covered in CSC 6230: Machine Learning. We will make a revision on the parts of machine learning we need . #4 was covered in ECE 6900: Security and privacy preservation for wireless networks. We will make a revision on the parts of ECE 6900 we need . 0 - 3

  5. Course Description: - Advanced topics in securing machine learning models and their applications to solve security/privacy threats. Course Topics: 1. Review to basic security concepts and cryptography primitives. 10% 2. Review to basic machine learning concepts. 15% 3.Attacks on machine learning models and countermeasures. 25% 4.Privacy-preserving evaluation of machine learning models. 15% 5.Using machine learning to launch attacks and counter security threats. 35% 0 - 4

  6. Course Textbook - No textbook is required. - The lecture materials will be derived from a number of background papers and textbooks. - Various reading material and research papers will be given. 0 - 5

  7. Course Evaluation 1 - Assignm ents, reports, answ ering questions, and presentations: 5 0 % of the final grade. To be done individually. 2 - Project: literature survey report. To be done individually. 2 0 % of the final grade. 3 - Tests : 1 0 % of the final grade. OPEN book, notes, laptops, etc. 4 - Final exam : The final examination will count for 2 0 % of the final grade. OPEN book, notes, laptops, etc. 0 - 6

  8. Expectations - The grade of the literature survey and reports is 7 0 % of the final grade but that does not m ean you w ill get m ost of this grade even if you do poor w ork. W rong assum ption. - Do the surveys and reports well and follow our guidelines. - Do not assume that you will get A without enough work because I’m your advisor. W rong assum ption. - Class participation: Your input is needed for good discussion. - Fully understand the slides, lectures, and assignments. - Be on time (if you are late enter the class quiet). - Focus in classes and take good notes. - Do not be shy to seek help from the instructor if you need. 0 - 7

  9. - Slides are protected by a password. - You do not need to type the password every time you open the files. - You can cancel the password protection after you download and open the files as follows 0 - 8

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  11. Questions Mohamed Mahmoud & Mostafa Fouda

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