Research Interests

• Hardware Security
• Post-Quantum Cryptography
• Side-Channel Analysis
• Privacy-Preserving Machine Learning
• Homomorphic Encryption

Education

North Carolina State University, Raleigh, NC Jan 2021 – Aug 2023

M.Sc. in Computer Engineering

• Advisors: Prof. Samira Mirbagher Ajorpaz, Prof. Aydin Aysu
• Thesis: Agent SCA: Advanced Physical Side Channel Analysis Agent with LLMs
• GPA: 3.55/4.00, Summa Cum Laude

Sabanci University, Istanbul, Turkey Sep 2014 – May 2020

B.Sc. in Computer Science and Engineering

B.Sc. in Electronics Engineering

Minor in Neuroscience

• Advisors: Prof. Erkay Savas, Prof. Albert Levi
• Thesis: Intrusion Detection Systems with Machine Learning for IoT Devices
• GPA: 3.62/4.00, Summa Cum Laude

Work Experiences

AMD

Hardware Security Researcher – Product Security Research Team (PSO RD), May 2022 – Present

• Conducted in-depth evaluations of Post-Quantum Cryptography (PQC) algorithms, ensuring optimal efficiency and robustness for next-generation cryptographic systems.
• Architected secure computation frameworks for machine learning (ML) and artificial intelligence (AI) on GPUs, including the design of a homomorphic encryption compiler to protect sensitive AI operations.
• Strengthened the security architecture of AMD’s Secure Encrypted Virtualization and Trusted Execution Environment, mitigating potential vulnerabilities and enhancing system integrity.
• Designed and implemented test environments to validate Secure Memory Encryption and cryptographic components for system-on-chip (SoC) platforms, contributing to FIPS certification readiness.
• Enhanced the resilience of cryptographic coprocessors against side-channel attacks (SCA) by developing advanced models using ChipWhisperer Python libraries and creating custom SCA models using Riscure Inspector, driving innovative approaches to secure cryptographic processors and mitigate emerging threats.

Accenture

Software Engineering Intern, Jun 2019 – Jul 2019

• Contributed to the development of a human resources automation system, streamlining routine HR tasks and enhancing operational efficiency.
• Designed and implemented RESTful APIs for backend services, enabling seamless data exchange and improving system functionality. Integrated event-driven and time-triggered serverless applications into a microservices architecture, leveraging Microsoft Azure to ensure scalability and reliability.

Vingd

AI Software Engineering Intern, Jan 2019 – Feb 2019

• Designed and implemented a rule-based security AI bot using Bayesian Networks in Java, and deployed the solution in a containerized environment using Docker for scalability and reliability.

Multinet inventiv

Software Engineer, Jul 2018 – Jan 2019

• Developed a Fraud Detection and Prevention System leveraging outlier detection machine learning models to identify anomalies in large-scale payment datasets using Weka.
• Designed and implemented database schemas using Java Hibernate and Spring Framework, enabling efficient data management and integration with backend services.
• Built and tested RESTful APIs for machine learning model deployment and system functionality, ensuring high reliability through JUnit-based validation.

Research Experiences

Hardware Cyber Threat Research Lab, NC State University

Advisor: Dr. Aydin Aysu, Jan 2021 – July 2022

• Conducted side-channel analysis (SCA) on deep learning accelerators for edge devices, leveraging the Python TensorFlow framework to uncover vulnerabilities.
• Designed and implemented attack vectors targeting Tensor Processing Units using Riscure Inspector, enhancing the understanding of potential security flaws.
• Optimized solvers for lattice-based cryptography problems, including NP-hard challenges like the Shortest Vector Problem (SVP) and Learning with Errors (LWE), contributing to advancements in PQC

Computer and Information Security Lab, Sabanci University

Advisors: Prof. Erkay Savas, Prof. Albert Levi, Sept 2019 – Jan 2021

• Optimized Homomorphic Encryption (HE) and Post-Quantum Cryptography schemes, contributing to advancements in secure computing.
• Developed Python simulations for prototyped FPGA designs, enhancing performance and efficiency.
• Built privacy-preserving machine learning applications using HE in a Python-based DNN framework.
• Implemented a secure inference system combining homomorphic encryption and machine learning, securing a top-5 finish in the IDASH’20 competition.
• Applied machine learning models to network traffic data for intrusion detection, improving security in IoT.

Institute for Infocomm Research, A-STAR

Advisors: Dr. Chao Jin, Dr. Ahmad Al Badawi, July 2019 – Sept 2019

• Developed and implemented privacy-preserving protocols for Deep Learning models, enhancing data security and model performance.
• Leveraged expertise in Multiparty Computing Security (Homomorphic Encryption, Garbled Circuits) to optimize CNN models, reducing resource usage while maintaining efficiency and security.

Secure Systems Lab, Boston University

Advisors: Dr. Manuel Egele, July 2017 – Sept 2017

• Conducted research and analysis to identify and mitigate potential security vulnerabilities in digital platforms.
• Analyzed Twitter data for homoglyph character vulnerabilities using Python, identifying potential risks in user interactions. Developed a scalable web scraper system utilizing a 30-node cluster and RabbitMQ

Publications

1. Yaman, F., Mert, A.C., Ozturk, E., Savas E., “A Hardware Accelerator for Polynomial Multiplication Operation of CRYSTALS-KYBER PQC Scheme” Design, Automation & Test in Europe Conference & Exhibition (DATE’21)
2. Kurian, A., Dubey, A., Yaman, F., Aysu, A. “TPUXtract: An Exhaustive Hyperparameter Extraction Framework”. IACR Transactions on Cryptographic Hardware and Embedded Systems, (CHES 2025)
3. Magara, S.S., Yildirim, C., Yaman, F., Dilekoglu B., Tutas, F.R., Ozturk, E., Kaya, K., Taştan, O., and E Savas, E., “ML with HE: Privacy Preserving Machine Learning Inferences for Genome Studies”. ACM Computer and Communications Security, CCS’21, PPML Workshop
4. Calhoun, A., Ortega, E., Yaman, F., Dubey A., Aysu, A., “Hands-On Teaching of Hardware Security for Machine Learning” Proceedings of the Great Lakes Symposium on VLSI, (ACM GLS-VLSI 2022)
5. Mert, A.C., Yaman, F., Karabulut, E., Ozturk, E., Savas, E., Aysu, A., “A Survey of Software Implementations for the Number Theoretic Transform” SAMOS 2023 International Conference on Embedded Computer Systems

Skills

• Programming Languages: Python, C / C++, C#, Verilog, Assembly, MATLAB, Java, Unix, SQL
• Frameworks: TensorFlow, PyTorch, Keras, Spring, Hibernate, JUnit
• Development: Git, Docker, Perforce, ARM DS5, KVM
• Security & Analysis: Riscure SCA, ChipWhisperer, Lascar, eShard, Kali Tools
• CAD Tools: Xilinx ISE, Vivado Design Suite

Coursework

• North Carolina State University, Raleigh, NC
  • Cryptographic Eng. and Hardware Security, Operating Systems, Secure Microprocessor Architecture Design
• Sabanci University, Istanbul, Turkey
  • Cryptography, Computer Networks and Security, Machine Learning, Digital and Logic System Design

Teaching Experience

• North Carolina State University, Raleigh, NC

  • TA for Cryptographic Engineering and Hardware Security (ECE-592), Aug 2021 – Dec 2021
    • Instructor: Dr. Aydin Aysu
    • Designed and evaluated research projects, graded reports, presentations, homeworks, and held office hours.
  • TA for Computer Engineering (ECE-290), Jan 2021 – May 2022
    • Instructor: Prof. Greg Byrd
    • Held weekly office hours and helped students to overcome their problems on programming concepts.

• Sabanci University, Istanbul, Turkey

  • TA for Logic and Digital System Design (CS 303, EE 310), Sept 2018 – May 2020
    • Instructor: Prof. Erkay Savas, Prof. Ilker Hamzaoglu
    • Guided students in creating digital systems on FPGA boards and led labs on logic design and Verilog HDL.
  • TA for Advanced Programming with C++ (CS-201, CS204), Oct 2016 – Jun 2017
    • Instructor: Prof. Kamer Kaya, Prof. Albert Levi
    • Assisted students in developing C++ projects on topics like Classes, Linked Lists, Queues, Heaps, and Trees. Held office hours to support homework, exams, and problem-solving in Object-Oriented Programming (Inheritance, Encapsulation, Polymorphism)