ISMAIL NEGABI | Embedded Cryptographic Systems and Artificial Intelligence | Best Researcher Award

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Assist. Prof. Dr ISMAIL NEGABI | Embedded Cryptographic Systems and Artificial Intelligence | Best Researcher Award

Lecturer, Abdelmalek Essaadi University, Morocco

Ismail Negabi is a dedicated researcher and educator specializing in Embedded Cryptographic Systems and Artificial Intelligence. He holds a Doctorate from Université Abdelmalek Essaâdi, where he focused on enhancing cryptographic system security against side-channel attacks using deep learning. With a strong academic background, including a Master’s in Signal Processing and Automatic Learning and a Bachelor’s in Physical Sciences, Ismail has consistently demonstrated excellence in his field. He is currently a primary school teacher and a reviewer for the International Journal of Computer Systems and Digital Systems. Ismail is passionate about leveraging AI and cryptography to address real-world security challenges.

Professional Profile

Google Scholar

Orcid

Scopus

Education 🎓

Ismail Negabi earned his Doctorate in 2023 from Université Abdelmalek Essaâdi, specializing in Embedded Cryptographic Systems and Artificial Intelligence. He completed his Master’s in Signal Processing and Automatic Learning in 2019 and his Bachelor’s in Physical Sciences in 2017, both from Moroccan universities. His academic journey began with a Baccalaureate in Physical and Chemical Sciences in 2011. Throughout his education, Ismail has consistently achieved high honors, including a “Très Honorable” distinction for his doctoral thesis.

Experience 💼

Ismail has a diverse professional background, including roles as a primary school teacher since 2020 and a reviewer for the International Journal of Computer Systems and Digital Systems. He has also worked as a trainer for the General Population and Housing Census in Morocco and completed internships in algorithm development and FPGA-based cryptographic systems. His experience spans teaching, research, and practical applications of AI and cryptography.

Awards and Honors 🏆

Ismail Negabi has received numerous accolades, including the “Très Honorable avec Félicitations” distinction for his doctoral thesis. His research has been published in prestigious journals indexed in Scopus, and he has presented at international conferences. Ismail’s contributions to AI and cryptography have earned him recognition as a promising researcher in his field.

Research Focus 🔍

Ismail’s research focuses on enhancing the security of cryptographic systems using deep learning techniques, particularly against side-channel attacks. He explores the integration of AI with encryption methods like AES to improve embedded system security. His work also extends to applications of deep learning in remote sensing, such as building extraction from satellite images, and anomaly detection for connected objects.

Publication Top Notes 📚

  1. “Building extraction from remote sensing imagery: advanced squeeze-and-excitation residual network based methodology”
  2. “Deep Learning-based Power Analysis Attack for Extracting Advanced Encryption Standard Keys on Microcontroller”
  3. “Convolutional neural network based key generation for security of data through encryption with AES”
  4. “Enhancing Building Extraction from Remote Sensing Images through UNet and Transfer Learning”
  5. “A Modular System based on U-Net for Automatic Building Extraction from very high-resolution satellite images”
  6. “Enhancing Cryptosystem Security with a CNN-based Countermeasure against Power Analysis Attacks”
  7. “Beyond Encryption: How DL Can Break Microcontroller Security Through Power Analysis”
  8. “Encryption of Sensitive Data by Intelligent Cryptosystem based on AES and CNN for Embedded Systems Security”
  9. “Combining Convolutional Neural Network with Feature Extraction for Automatic Building Extraction”
  10. “Towards an Intelligent Cryptosystem Design: Deep Learning Cryptography for Embedded Systems Security”

Conclusion 🌟

Ismail Negabi is a highly accomplished researcher and educator with a passion for advancing the fields of AI and cryptography. His innovative work on deep learning-based cryptographic security and remote sensing applications has made significant contributions to the academic and professional communities. With a strong foundation in education, diverse professional experience, and a commitment to excellence, Ismail continues to inspire and lead in his field.

 

Ali Abdullah S. AlQahtani | Cybersecurity | Best Researcher Award

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Dr Ali Abdullah S. AlQahtani | Cybersecurity | Best Researcher Award 

Assistant Professor, Prince Sultan University, Saudi Arabia

Dr. Ali Abdullah S. AlQahtani is an esteemed cybersecurity researcher and academic affiliated with Prince Sultan University. His expertise spans digital authentication, cybersecurity, IoT applications, and machine learning. He has contributed significantly to authentication systems, including zero-effort two-factor authentication and continuous authentication mechanisms. Dr. AlQahtani has authored numerous high-impact publications and has been cited widely for his research in secure digital identification and privacy protection. His contributions extend to academia and industry, where he has collaborated on innovative security solutions.

PROFESSIONAL PROFILE

Google Scholar

STRENGTHS FOR THE AWARD

  1. Strong Academic Background – Dr. AlQahtani holds a Ph.D. in Engineering (Cyberspace Engineering) from Louisiana Tech University, along with master’s degrees in Electrical Engineering and Computer & Information Science (Cybersecurity & Privacy). His education is well-aligned with cutting-edge cybersecurity research.
  2. High Citation and Research Impact – He has multiple peer-reviewed publications, including papers in IEEE Access and leading cybersecurity conferences. His work on machine learning, cybersecurity, digital authentication, and IoT security has received substantial citations, indicating strong influence in the field.
  3. Innovative Research Contributions – His work on Zero Effort Two-Factor Authentication (0E2FA) and Beacon Frame Two-Factor Authentication (BF2FA) demonstrates significant contributions to authentication mechanisms, enhancing security with minimal user interaction.
  4. Focus on Emerging Topics – Dr. AlQahtani’s research spans biometric authentication, IoT security, AI-driven cybersecurity, and location-based authentication systems, aligning with global challenges in cybersecurity.
  5. Diverse Research Collaborations – He has worked with multiple researchers across different institutions and has interdisciplinary collaborations in cybersecurity, AI, and IoT security, enhancing the practical applicability of his research.

AREAS FOR IMPROVEMENT

  1. Industry Collaboration & Patents – While his research is strong, expanding collaboration with industry leaders in cybersecurity and obtaining patents on his authentication systems could enhance the practical impact of his work.
  2. Government & Policy Influence – Given the increasing importance of cybersecurity policies, contributing to government regulations or cybersecurity frameworks could further solidify his global recognition.
  3. Large-Scale Real-World Implementation – While his research on user authentication and IoT security is promising, implementing his solutions at scale (e.g., national security, enterprise cybersecurity, or smart cities) would further validate his innovations.

EDUCATION

🎓 Doctor of Philosophy in Engineering (Cyberspace Engineering) – Louisiana Tech University, USA (2017-2020)
📝 Dissertation: “0E2FA: Zero Effort Two Factor Authentication”
📊 GPA: 3.667/4.00

🎓 Master of Engineering in Electrical Engineering – Louisiana Tech University, USA (2017-2019)
📊 GPA: 3.667/4.00

🎓 Master of Science in Computer and Information Science – Southern Arkansas University, USA (2016-2017)
🔬 Concentration: Cybersecurity and Privacy
📊 GPA: 3.90/4.00

🎓 Bachelor of Science in Computer Science – Grambling State University, USA (2013-2016)
📊 Major & Math GPA: 4.00/4.00 | Overall GPA: 3.90/4.00

EXPERIENCE

With a diverse background in academia, research, industry, and military service, I have gained extensive expertise in cybersecurity, computer science, and leadership roles. As an Assistant Professor of Cybersecurity at Prince Sultan University and previously at North Carolina A&T State University, I have taught graduate and undergraduate courses, mentored students, and led research initiatives. My research spans cybersecurity, authentication systems, and artificial intelligence, securing over $1.9M in funding. I also held leadership roles as Projects Director at King Saud University and Founding Director of CyberNex Lab, spearheading cybersecurity initiatives. My industry experience includes working as a Software Engineer Intern at CenturyLink, developing innovative mobile applications. Additionally, I served in the Royal Saudi Air Force (2004-2011), gaining expertise in technical operations and leadership. My multidisciplinary experience enables me to contribute effectively to academia, research, and industry collaborations.

AWARDS AND HONORS

🏆 Best Research Paper Award – Multiple conferences on cybersecurity and authentication
🏆 Outstanding Research Contribution – Recognized for innovations in digital authentication
🏆 Cybersecurity Excellence Award – Honored for advancements in secure IoT applications
🏆 Best Academic Performance – Awarded for excellence in computer science education

RESEARCH FOCUS

🔐 Cybersecurity – Enhancing digital security frameworks
🆔 Digital Authentication – Developing zero-effort and two-factor authentication models
📡 IoT Applications – Securing IoT networks and devices
🤖 Machine Learning in Security – Applying ML for authentication and threat detection

PUBLICATION TOP NOTES📚

📝 Distinguishing Human-Written and ChatGPT-Generated Text Using Machine Learning
📝 0EISUA: Zero Effort Indoor Secure User Authentication
📝 A Survey on User Authentication Factors
📝 Zero-Effort Indoor Continuous Social Distancing Monitoring System
📝 COVID-19 Zero-Interaction School Attendance System
📝 TS2FA: Trilateration System Two Factor Authentication
📝 BF2FA: Beacon Frame Two-Factor Authentication
📝 A Cheat-Proof System to Validate GPS Location Data
📝 Comprehensive Survey: Biometric User Authentication Application, Evaluation, and Discussion
📝 IoT Devices Proximity Authentication in Ad Hoc Network Environment
📝 Analysis of the Design Requirements for Remote Internet-Based E-Voting Systems
📝 0EI2FA: Zero Effort Indoor Two Factor Authentication
📝 CI2FA: Continuous Indoor Two-Factor Authentication Based On Trilateration System
📝 Architecture for Continuous Authentication in Location-Based Services
📝 A Weighting System for Building RSS Maps by Crowdsourcing Data from Smartphones
📝 Leveraging Machine Learning for Wi-Fi-Based Environmental Continuous Two-Factor Authentication
📝 Navigating Cybersecurity Training: A Comprehensive Review
📝 Comparative Analysis of Underwater Positioning and Navigation Systems
📝 Two Methods for Authentication Using Variable Transmission Power Patterns
📝 Securing IoT-Based Healthcare Systems Against Malicious and Benign Congestion

CONCLUSION

Dr. Ali Abdullah S. AlQahtani is a highly qualified candidate for the Best Researcher Award in cybersecurity and authentication technologies. His pioneering work in two-factor authentication, machine learning applications in cybersecurity, and IoT security positions him among top researchers in the field. Strengthening industry partnerships, real-world applications, and policy influence would further enhance his contributions and solidify his status as a leading expert.

Salim Chehida – Smart grid security – Best Researcher Award

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Salim Chehida - Smart grid security - Best Researcher Award

VERIMAG - Université Grenoble alpes - France

AUTHOR PROFILE

Scopus

EARLY ACADEMIC PURSUITS

Salim Chehida's academic journey commenced with an Engineer Degree in Computer Science from the University of Mostaganem, Algeria. He furthered his studies with a Magister Degree in Information Systems Engineering and eventually pursued a Ph.D. in Computer Science specializing in Software Engineering and Systems Security from the University of Oran 1 in Algeria in collaboration with the University of Grenoble Alpes in France.

PROFESSIONAL ENDEAVORS

Dr. Salim Chehida has had a diverse professional career, starting as a Software Engineer at the Finance Direction in Algeria and later transitioning to roles as a Scientific Researcher and Assistant Professor at the University of Mostaganem, Algeria. Currently, he serves as a Research and Development Expert at the University of Grenoble Alpes in France, contributing significantly to the fields of Software Engineering and Deep Learning.

CONTRIBUTIONS AND RESEARCH FOCUS

Dr. Chehida's expertise lies in Software Engineering, particularly in the design, development, security, verification, and validation of software systems. He has made notable contributions to various innovative projects, including those related to cyber-physical systems (CPS) and Internet of Things (IoT) systems. His research focuses on deep learning applications, including image classification, segmentation, and object detection, as well as smart grid security.

IMPACT AND INFLUENCE

Dr. Chehida's research and development work have had a significant impact on academia and industry, particularly in the domains of software engineering and deep learning. His involvement in numerous projects, collaborations with companies and institutions worldwide, and contributions to conferences and publications have established him as a respected expert in his field.

ACADEMIC CITES

Dr. Chehida's publications and technical reports have been widely cited, reflecting the importance and relevance of his research contributions. His work in smart grid security and deep learning applications has garnered attention from researchers and professionals in academia, industry, and government organizations.

LEGACY AND FUTURE CONTRIBUTIONS

As Dr. Chehida continues to advance his research and development endeavors, his legacy in the fields of software engineering and deep learning is assured. His future contributions are expected to further enhance our understanding and application of smart grid security measures and deep learning techniques, addressing critical challenges in cybersecurity and artificial intelligence for years to come.

NOTABLE PUBLICATION

Model-based Self-adaptive Management in a Smart Grid Substation 2023 (2)

Generation and verification of learned stochastic automata using k-NN and statistical model checking 2022 (1)

Learning and analysis of sensors behavior in IoT systems using statistical model checking 2022 (5)

BRAIN-IoT Architecture and Platform for Building IoT Systems 2022 (2)

Sareer Ul Amin – Computer Science and Engineering – Excellence in Research

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Sareer Ul Amin - Computer Science and Engineering - Excellence in Research

Chung Ang University - South Korea

AUTHOR PROFILE

Scopus

EARLY ACADEMIC PURSUITS

Sareer Ul Amin embarked on his academic journey at Islamia College Peshawar (ICP), Pakistan, where he pursued a Bachelor of Science in Computer Science, graduating with distinction. His academic excellence continued as he pursued a Master's degree at Chung-Ang University (CAU) in Seoul, Republic of Korea, achieving an outstanding CGPA of 4.18/4.5.

PROFESSIONAL ENDEAVORS

Sareer Ul Amin's professional journey is marked by significant contributions to the field of Computer Science and Engineering. He served as a Research Assistant at the Graphics Realization Lab, CAU, contributing to various industrial and research projects. Prior to this, he held the role of Lab Coordinator at the Digital Image Processing Lab, ICP, where he effectively managed projects and mentored students.

CONTRIBUTIONS AND RESEARCH FOCUS

Sareer Ul Amin's research focus lies in AI & Computer Vision, with a specialization in Advanced Machine Learning, Deep Learning, and Anomaly Detection in Surveillance Video. His research contributions include the development of efficient strategies for anomaly detection, active learning techniques for data annotation, and robust hand gesture recognition systems. His work has been published in esteemed journals and conferences, showcasing his expertise in the field.

IMPACT AND INFLUENCE

Sareer Ul Amin's research findings have had a significant impact on the field of Computer Science and Engineering, particularly in the areas of anomaly detection, image analysis, and machine learning. His publications have garnered citations and recognition, highlighting the relevance and influence of his research contributions in academia and industry.

ACADEMIC CITES

Sareer Ul Amin's research publications have been well-received in the academic community, with his work cited in reputable journals and conferences. His contributions to the development of efficient deep learning models and active learning techniques have advanced the state-of-the-art in computer vision and machine learning.

LEGACY AND FUTURE CONTRIBUTIONS

Sareer Ul Amin's legacy in the field of Computer Science and Engineering is characterized by his dedication to research excellence and innovation. His future contributions are poised to further advance the frontier of AI and Computer Vision, with a focus on addressing complex challenges and developing practical solutions for real-world applications.

NOTABLE PUBLICATION

An Efficient and Robust Hand Gesture Recognition System of Sign Language Employing Finetuned Inception-V3 and Efficientnet-B0 Network.  2023 (6)

Harnessing synthetic data for enhanced detection of Pine Wilt Disease: An image classification approach.  2024