About memy stats
Information About me
I hold a PhD degree in cryptography and security from Sorbonne Doctoral School. I also hold a diploma of engineering from Telecom ParisTech in CyberSecurity. Currently, I work for NXP Semiconductors as a crypto developer for embedded devices. I develop C libraries for NXP microcontrollers targeting the highest levels of security. As a daily routine, I write embedded C and assembly code and interface with IP specific hardwares.
Previously, I worked in R&D of Thales researching novel cryptography and network security protocols. I also worked on malware Research and vulnerability analysis. In my extra time, I offer penetration testing services for websites and mobile applications for private clients.
Away from my desk, I enjoy playing chess and doing sport. My favorite sports are swimming and hiking.
Years of experience
Embedded C, Python, C++, ARM ASM, RISC V ASM
Web (OWASP), Android (ADB, MobSF, ...)
Machine Learning and AI
CNN, DNN, Transformers, Federated Learning
Theoretical and Applied Cryptography
NIST Standards, AES, DES, ECC, RSA, PQC, ZKP, ...
Version Control, Server Integration, Containers, ...
Unix System Administration
Servers, Database, Web
Research and Writing
Academic Articles, Patents, Blogs
Debugging and Dynamic Code Analysis
Intel PIN, GDB, Keil, OpenCRT, Frida
Reverse Engineering and Static Analysis
IDA Pro, Radare2
Crypto Developer - NXP Semiconductors (Toulouse, France)
Developing cryptography C libraries for embedded devices.
Research Engineer - THALES SIX GTS (Paris, France)
Designing and developing cutting-edge network security solutions.
Research Internship - Stevens Institute of Technology (Hoboken, USA)
Reducing the attack surface of user programs by removing unwanted features from programs using dynamic and static binary analysis.
Research Internship - EURECOM (Sophia Antipolis, France)
Designing a privacy-preserving neural networks using multi-party computation.
Penetration Tester - NetRom Consultants (Jounieh, Lebanon)
Black box and white box website penetration testing and on-site network pentesting.
Ph.D. - University of Sorbonne
Philosophy Degree in IoT Security (Bac+7).
Diploma in Engineering - Telecom ParisTech (EURECOM)
Diploma in cybersecurity engineering. Equivalent to a masters degree (Bac+5)
Diploma in Engineering - Lebanese University
Diploma in telecomunication engineering. Equivalent to a masters degree (Bac+5)
My ProjectsMy Work
Here is a selection of my work in several programming languages. The source code of all these projects is accessible on Github
This is an implementation of the protocol presented here . The protocol aims to preserve the privacy of federated learning clients by encrypting their model updates. The encryption is additively homomorphic such that the federated learning average can be computed on the encrypted inputs.
A framework for training machine learning models for anomaly detection using realtime IoT network traffic. The frameworks enables training multiple models for different types of IoT devices. It can also collect traffic generated in several networks and train in real time.
This is a simulation of the protocol proposed here. FADIA is a collaborative remote attestation protocol designed to verify the software integrity of millions of devices on the network in a scalable way.
Radare2 is an open-source reverse engineering tool. This project implements a plugin for Radare2 which serves as a clients for FIRST server. The Function Identification and Recover Signature Tool (FIRST) developed by Talos, is a framework to help reverse engineers. It makes finding similar functions easier by searching function metadata.
This project aims to evaluate existing function similarity techniques. It contains a database of programs, compiled for different architectures, using different compilers and several compiler flags. Using the database we benchmark the state-of-the art diffing tools.
Conan is a network traffic analyzer that investigates pcap file, it reads the packets, reassembles all the TCP connections in the network trace, and for each connection it looks for any ambiguities.
Mohamad Mansouri . Performance and Verifiability of IoT Security Protocols (2023). Cryptography and Security. Sorbonne Université, 2023.
Mohamad Mansouri , Melek Önen, Wafa Ben Jaballah, and Mauro Conti. Sok: Secure aggregation based on cryptographic scheme for federated learning (2023). To appear in PETS'23
Mohamad Mansouri , Jun Xu, and Georgios Portokalidis. Disabling unwanted functionalities in binary programs. (2023). To appear in AsiaCSS'23
Mohamad Mansouri , Melek Önen, and Wafa Ben Jaballah. Learning from failures: Secure and fault-tolerant secure aggregation for federated learning (2023). Proceedings of the 38th Annual Computer Security Applications Conference (ACSAC '22)
Andrea Marcelli, Mariano Graziano, Xabier Ugarte-Pedrero, Yannick Fratantonio, Mohamad Mansouri , and Davide Balzarotti. How machine learning is solving the binary function similarity problem (2022). 31st usenix security symposium, 10-12 august 2022, Boston, MA, USA (Usenix 2022).
Mohamad Mansouri , Wafa Ben Jaballah, Melek Önen, Md Masoom Rabbani, and Mauro Conti. FADIA: fairness-driven collaborative remote attestation (2021). Proceedings of the 14th ACM Conference on Security and Privacy in Wireless and Mobile Networks (WiSec '21).
Mohamad Mansouri , Beyza Bozdemir, Melek Önen, and Orhan Ermis. PAC: Privacy-Preserving Arrhythmia Classification with Neural Networks (2020). Foundations and practice of security (FPS '19).
Contact me here
Do you have a nice project?! I'm very interested in helping. Please don't hesitate to contact me.
mohamad_mansouri (at) outlook.com
+33 6 25 O8 O8 25