Sarra Senouci at University of Electronic Science and Technology of China, Algeria
Sarra Senouci is an emerging researcher in the field of mechanical and electrical systems with a strong foundation in cryptography, network security, and embedded systems. She is currently pursuing her Ph.D. at the University of Electronic Science and Technology of China, where she is contributing to the advancement of secure communication systems using chaos theory and deep learning. Fluent in Arabic, English, French, and Chinese, Sarra brings multicultural and multidisciplinary strengths to her academic and professional engagements.
🔹Professional Profile:
Scopus Profile
Orcid Profile
Google Scholar Profile
🎓Education Background
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Ph.D. in Mechanical & Electrical Engineering, University of Electronic Science and Technology of China, P.R. China (Expected 2025)
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Master’s in Instrumentation, University of Sciences and Technology Houari Boumediene, Algiers, Algeria (2021)
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Bachelor’s in Electronics, University of Sciences and Technology Houari Boumediene, Algiers, Algeria (2017)
💼 Professional Development
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2023 – Present | China
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2022 | Algeria
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2021 | Algeria
🔬Research Focus
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Cryptographically Secure PRNGs
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Chaos Theory in Communication Systems
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Deep Learning for Cybersecurity (DDoS Detection)
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Software-Defined Networking (SDN)
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Secure and Autonomous Sensor Networks
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Embedded Systems and FPGA Design
📈Author Metrics:
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Publications in IEEE and Elsevier-indexed journals and conferences, including Chaos, Solitons & Fractals
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Co-author of 4+ peer-reviewed research papers
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Topics span chaotic systems, PRNG, SDN security, ensemble learning, and deep convolutional neural networks
🏆Awards and Honors:
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Excellent Performance Award, Chengdu, China (2024, 2025)
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Academic Achievement Award, Chengdu, China (2024, 2025)
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Certificate of Presentation, ICCWAMTIP 2024, Chengdu, China
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Invitation to Participate, ICCWAMTIP 2024 Conference
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English Language Proficiency Certification, USTHB, Algeria (2021)
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Visiting Scholar Certificate, Beijing University of Posts and Telecommunications (2024)
📝Publication Top Notes
1. A Novel PRNG for Fiber Optic Transmission
Authors: S. Senouci, S.A. Madoune, M.R. Senouci, A. Senouci, Z. Tang
Journal: Chaos, Solitons & Fractals, Volume 192, Article 116038
Publisher: Elsevier
Year: 2025
DOI: [Available upon publication]
Summary:
This research proposes a novel Pseudo Random Number Generator (PRNG) leveraging chaotic dynamics, optimized for secure fiber optic communication systems. The model enhances entropy and unpredictability, crucial for encryption protocols in high-speed optical transmission networks. The study includes performance comparisons, security analyses, and hardware feasibility discussions.
2. Deep Convolutional Neural Network-Based High-Precision and Speed DDoS Detection in SDN Environments
Authors: S.A. Madoune, S. Senouci, J. Dingde, A. Senouci
Conference: 2024 21st International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP)
Pages: 1–6
DOI: 10.1109/iccwamtip64812.2024.10873789
Summary:
This paper introduces a deep CNN architecture designed to detect Distributed Denial of Service (DDoS) attacks in Software Defined Networking (SDN) frameworks. The model outperforms conventional detection systems in both accuracy and detection speed, addressing critical latency and scalability issues. A real-world SDN testbed is used for validation.
3. Toward Robust DDoS Detection in SDN: Leveraging Feature Engineering and Ensemble Learning
Authors: S.A. Madoune, S. Senouci, M.A. Setitra, J. Dingde
Conference: 2024 21st International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP)
Pages: 1–7
DOI: 10.1109/iccwamtip64812.2024.10873648
Summary:
Focusing on robustness in DDoS detection, this paper explores feature engineering techniques combined with ensemble learning models (like Random Forest and Gradient Boosting) to counter adversarial attacks in SDN networks. Experimental results highlight a significant increase in detection robustness and generalization across different traffic datasets.
4. A New Chaotic Based Cryptographically Secure Pseudo Random Number Generator
Authors: S. Senouci, S.A. Madoune, M.R. Senouci, A. Senouci, T. Zhangchuan
Conference: 2024 21st International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP)
Pages: 1–5
DOI: 10.1109/iccwamtip64812.2024.10873703
Summary:
This paper presents a cryptographically secure PRNG grounded in chaotic system dynamics with a focus on hardware and software compatibility for secure communication systems. The proposed PRNG is tested against NIST and DIEHARD standards and shows improved resistance to cryptanalytic attacks compared to classical chaotic PRNGs.
.Conclusion:
Mrs. Sarra Senouci is a highly promising and deserving candidate for the Best Researcher Award. Her profile shows significant research maturity, innovation, and interdisciplinary depth for someone in the final stages of her Ph.D. With a track record of quality publications, multilingualism, global engagement, and award recognition, she reflects the profile of a next-generation researcher contributing to secure, intelligent communication systems.
🔖 Recommendation: Highly Recommended for Best Researcher Award (Early Career Category or Emerging Researcher Track).