Personal profile
Research and Innovation interests
Sadegh is a cybersecurity researcher and software security specialist with expertise in AI-driven fuzzing, cyptography, automated vulnerability detection, and secure software development. He leverages the intersection of cybersecurity and machine learning to design innovative solutions that identify and mitigate software vulnerabilities before they can be exploited.
With a background in data analytics, cyberecurity operations and IT management, Sadegh brings a data-driven approach to security research, exploring the convergence of AI and emerging smart and green technologies—where cutting-edge security and intelligence meet real-world challenges.
He thrives at the nexus of research, innovation, and practical implementation, working to create secure, resilient, and intelligent systems at the intersection of software, hardware, and emerging domains—from digital technologies to quantum computing and beyond!
Education/Academic qualification
IT management - Data Analytics, Master of Science, Golden Gate University
Electrical Engineering - Telecommunication, Bachelor of Science, University of Tabriz
Cybersecurity and Software Testing, Doctor of Philosophy, University of the West of England
Keywords
- QA76 Computer software
- Fuzzing
- Software Testing
- Vulnerability Assessment
- Random Testing
- Antifuzzing
- Quality Assessment
- Stress Testing
- Machine learning algorithms
- QA75 Electronic computers. Computer science
- Cybersecurity Analytics
- Cybersecurity Operations
- Applied Operating System
- HD28 Management. Industrial Management
- Managing IT in business enterprise
- Infrastructure & hosted service
- Database and data management
- Business Intelligence and risk assessment
- Cryptography Compliance Specialist
- FIPS 197, 202, 180-4, 140-3
- NIST SP 800-38A, 800-22, 800-90A
- ISO/IEC 18033
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- 1 Similar Profiles
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Leveraging activation and optimisation layers as dynamic strategies in the multi-task fuzzing scheme
Bamohabbat Chafjiri, S. (Corresponding / Lead Author), Legg, P., Tsompanas, M.-A. & Hong, J., 15 Apr 2025, In: Computer Standards and Interfaces. 94, 104011.Research output: Contribution to journal › Article › peer-review
Open Access -
Improving search space analysis of fuzzing mutators using cryptographic structures
Bamohabbat Chafjiri, S., Legg, P., Tsompanas, M.-A. & Hong, J., 18 Sept 2024, AI Applications in Cyber Security and Communication Networks: Proceedings of Ninth International Conference on Cyber Security, Privacy in Communication Networks (ICCS 2023). Hewage, C., Nawaf, L. & Kesswani, N. (eds.). 1st ed. Singapore: Springer Nature, Vol. 1032. p. 153-172 (Lecture Notes in Networks and Systems).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
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Vulnerability detection through machine learning-based fuzzing: A systematic review
Bamohabbat Chafjiri, S. (Corresponding / Lead Author), Legg, P., Hong, J. & Tsompanas, M.-A., 29 May 2024, In: Computers and Security. 143, 103903.Research output: Contribution to journal › Literature review › peer-review
Open Access -
Stop at the red-light is no longer boring
Bamohabbat Chafjiri, S., Chamforoush, S., Mirmousavi, S. F. & Ahaki Lakeh, H., 8 Jun 2022.Research output: Contribution to conference › Poster › peer-review
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Related-key impossible differential cryptanalysis of full-round HIGHT
Bamohabbat Chafjiri, S., Rostami, S. & Tabatabaei, S. A. H., 27 Aug 2015, 2013 International Conference on Security and Cryptography (SECRYPT, Reykjavik, Iceland). First edition ed. Lisbon, Portugal: SciTePress, p. 537–542 6 p.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
Thesis
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Advancing software fuzzing techniques through the exploration of cryptographic concepts and machine learning
Bamohabbat Chafjiri, S. (Author), Legg, P. (Director of Studies), Hong, J. (Second Supervisor 1) & Tsompanas, M.-A. (Second Supervisor 2), 23 Aug 2025Student thesis: PhD Thesis
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