جستجوی استاد راهنمای دانشگاهی

Jia Jiaمشاهده پروفایل

مدرس

• Cybersecurity
• Cryptography
• Blockchain Technology
• +۵ مورد دیگر

Dr. Jia Jia is a Lecturer in International Business and Strategy at Plymouth Business School (Faculty of Arts, Humanities and Business), University of Plymouth. Her research focuses on cybersecurity, cryptography, blockchain technology, and federated learning. She has held previous academic roles at UCL School of Management and Royal Holloway University of London. Her work bridges business strategy with technological advancements, particularly in secure digital systems and AI-driven cybersecurity solutions. Teaching Responsibilities include courses such as International Business Strategy, Asia-Pacific Business Management, and Capstone/Honours Project supervision. She actively contributes to research in e-voting security, identity-based identification systems, and distributed PKI frameworks. Recent publications address challenges in Byzantine-robust federated learning, blockchain-based e-auctions, and post-quantum cryptographic systems. Research interests span interdisciplinary areas including: Cybersecurity in pervasive computing environments Blockchain and smart contract applications Secure data transfer protocols in cloud computing Adaptive adversary resistance in distributed systems Her articles highlight contributions to e-voting security, federated learning resilience, and AI-driven hazard simulation for driver education. Current doctoral supervision includes Tonari Arikekpar’s work on Nigerian international students’ experiences. No academic awards are listed.

• Cryptography
• Security Protocols
• Side-Channel Attacks
• +۳ مورد دیگر

Olivier Markowitch is a Professor at the Computer Sciences Department of the Faculty of Sciences at Université Libre de Bruxelles (Free University of Brussels). He currently serves as Dean of the Faculty of Sciences and is the university's information security advisor. Previously, he was Head of the Computer Sciences Department and co-president of the university's ethics committee. He co-founded the inter-university Master in Cybersecurity program and co-organized the Cybersecurity Research Center at ULB. His research focuses on: Design and analysis of cryptographic protocols Communication protocol security Side-channel attack methodologies Blockchain applications Hardware security (Network-on-Chip) Secure computation outsourcing Analysis of his 100+ publications reveals consistent focus on applied cryptography, with recent work emphasizing blockchain-based auction systems, hardware security for multi-core architectures, lightweight encryption for IoT devices, and theoretical advances in cryptographic protocols. His publications frequently address both theoretical foundations and practical implementations. Markowitch has supervised doctoral candidates in areas including lattice-based cryptography and secure Network-on-Chip protocols. He leads institutional cybersecurity initiatives and teaches courses in algorithms, cryptography, and computer security.

• Cryptography
• Information Security
• Secret Sharing
• +۵ مورد دیگر

Keiichi Iwamura is a Professor in the Department of Information and Computer Technology at Tokyo University of Science's School of Engineering, specializing in cryptographic protocols and information security. With over 113 publications spanning from 1992 to projected 2025, his research demonstrates sustained academic productivity and leadership in the field of information security. Professor Iwamura's primary research interests center around secret sharing schemes, secure multi-party computation, privacy-preserving technologies, and digital watermarking. His work bridges theoretical cryptography with practical implementations, particularly focusing on communication efficiency and real-world applicability of cryptographic protocols. He has made significant contributions to threshold secret sharing techniques, verifiable secret sharing, and secure computation frameworks that maintain privacy while enabling collaborative data processing. His recent publications (2020-2025) reveal a strong focus on optimizing secret sharing protocols for practical applications, with particular attention to reducing communication overhead while maintaining security guarantees. The research trends show increasing integration of machine learning techniques with traditional cryptographic methods, especially in watermarking and privacy-preserving computation domains. Professor Iwamura maintains extensive research collaborations, most notably with Ahmad Akmal Aminuddin Mohd Kamal (22 joint publications), Isao Echizen (21 publications), and Kitahiro Kaneda (20 publications), indicating a well-established research network focused on information security challenges. His research has been published in high-impact venues including IEEE Access, Journal of Information Security and Applications, and major conferences such as CCNC, GCCE, and ICISSP, demonstrating recognition of his work within the international security research community.

• Cloud Computing
• Blockchain Technology
• Data Security
• +۵ مورد دیگر

Xiaojun Zhang is a Professor actively contributing to cloud computing, blockchain technology, data security, and educational technology. His work spans cybersecurity, signal processing, and wireless systems. Key Research Areas: Privacy-preserving data aggregation, machine learning for biomedical imaging, blockchain-based integrity auditing, and educational metacognition studies. Recent Article Trends (2022–2025): Focus on secure federated learning, data denoising algorithms, and blockchain applications in smart grids, healthcare, and education. Collaborations include institutions in China and international researchers.

Refik Molvaمشاهده پروفایل

استاد بازنشسته

• Cybersecurity
• Cryptographic Protocols
• Cloud Computing Security
• +۳ مورد دیگر

Refik Molva is an Emeritus Professor at EURECOM's Digital Security department. He holds a Ph.D. in Computer Science (1986) from Paul Sabatier University, Toulouse, and a B.Sc. in Computer Science (1981) from Joseph Fourier University, Grenoble. Prior to EURECOM, he worked at IBM's Zurich Research Laboratory (1987–1992) as a Research Staff Member, contributing to network and system security research, including the KryptoKnight security system. He later served as a consultant in IBM's Consulting Group (1997). His research focuses on security mechanisms, cryptographic protocols, cloud computing security, and privacy-preserving technologies. Key areas include confidentiality in cloud environments, privacy in data management, and secure authentication in IoT systems. He has published over 222 papers and received notable awards, including Best Paper Awards at SENSORCOMM 2011 and IFIP SEC 2009, alongside IBM's Outstanding Technical Achievement Award (1989) and Research Division Award (1988). Notable contributions include PORTOS (data reliability proofs), StealthGuard (hidden watchdogs for retrievability), and frameworks for searchable encryption. His work emphasizes practical solutions for modern security challenges in distributed systems, privacy preservation, and resilient network protocols. Education: Ph.D., Computer Science, Paul Sabatier University (1986) B.Sc., Computer Science, Joseph Fourier University (1981) Awards: Best Paper Award, SENSORCOMM 2011 Best Student Paper Award, IFIP SEC 2009 IBM Outstanding Technical Achievement Award (1989) Grants & Collaborations: IBM Zurich Research Lab (1987–1992) Consulting engagements in network security His research spans theoretical and applied cybersecurity, with an emphasis on real-world deployment and privacy-by-design principles in emerging technologies like IoT and cloud systems.

• Cybersecurity
• Privacy-Preserving Machine Learning
• Cryptography
• +۵ مورد دیگر

Dr. Maggie Liu is a Lecturer in Cybersecurity and Software Systems at RMIT University's School of Computing Technologies. Her research focuses on secure multi-party computation and its applications in privacy-preserving machine learning (PPML), with specific emphasis on practical deployments for medical diagnostics and mobile image classification. Key research areas include: Designing lightweight cryptographic protocols Secure computation techniques Machine learning systems security Interdisciplinary privacy-preserving solutions Her recent work involves PPML for medical services, mobile-edge computing, and collaborative learning systems. Notable projects include MediSC, CryptMed, OblivGNN, Sonic, EncSIM, and Leia. Maggie Liu earned her Ph.D. in Computer Science from RMIT University.

• Internet of Things Security
• Cryptography
• Attribute-Based Encryption
• +۳ مورد دیگر

Chong Guo and Bei Gong are collaborative researchers at Edith Cowan University's School of Engineering specializing in security solutions for Internet of Things ecosystems. Their work addresses critical challenges in cryptographic efficiency for resource-constrained devices. Research interests include: Lightweight cryptographic protocols eliminating pairing operations Multi-authority attribute-based encryption/signcryption frameworks Privacy-preserving keyword search for cloud IoT systems Cross-domain authentication using threshold signatures Verifiable outsourced decryption mechanisms Recent publications demonstrate a cohesive research trajectory focused on optimizing security protocols for IoT environments, with particular emphasis on reducing computational overhead while maintaining robust security properties. Their work bridges theoretical cryptography with practical implementation considerations for real-world deployment. Research is supported by significant funding including Major Science and Technology Projects in Yunnan Province (202202AD080013), National Key Research and Development Project of China (2019YFB2102303), National Natural Science Foundation of China (61971014), and King Khalid University (RGP.2/373/45), indicating strong institutional backing and international collaboration. As active researchers, they maintain productive partnerships across multiple institutions, with publications appearing in reputable venues like Sensors, demonstrating consistent contribution to advancing IoT security frameworks.

Maher Salemمشاهده پروفایل

مدرس ارشد

• Cybersecurity
• Blockchain Technology
• Machine Learning
• +۴ مورد دیگر

Dr. Maher Salem is a Senior Lecturer (Assistant Professor) in Cybersecurity at King's College London, affiliated with the Department of Informatics within the Faculty of Natural, Mathematical & Engineering Sciences. He holds a PhD in Security Engineering from Kassel University (2014) and is a HEA Fellow. His research focuses on intrusion detection systems, cyber threat intelligence, machine learning-based security solutions, and blockchain applications in cybersecurity and finance. He has 15+ years of industrial experience with firms like AUDI AG and E-Plus, and has secured funding from the German Federal Ministry of Education and Research (BMBF). Dr. Salem leads the Computing Education Research Centre (CERC) at King's, advancing cybersecurity education through pedagogical tools and PhD supervision. His work bridges academia and industry, addressing challenges in online learning equity, cloud security, and automotive/IoT security via blockchain. Notable contributions include frameworks for threat intelligence detection, privacy-preserving cloud search, and decentralized transportation authentication systems. Education: PhD in Security Engineering (Kassel University, 2014) Affiliations: Former roles at Higher Colleges of Technology (UAE) and Fulda University of Applied Sciences (Germany) Labs/Teams: Security Hub (King's College), CERC His awards include the Emirates Skills First Rank Award (2017) and HEA Fellowship (2019). Research outputs span 25+ peer-reviewed articles, focusing on AI-driven penetration testing, blockchain applications, and cybersecurity education innovations. He collaborates globally on projects like dynamic cloud congestion management and APT detection frameworks.

Yi-Fan Tsengمشاهده پروفایل

استادیار

• Cryptography
• Information Security
• Cloud Security
• +۴ مورد دیگر

Dr. Tseng Yi-Fan is an Assistant Professor in the Department of Management Information Systems at National Chengchi University (NCCU), Taiwan. He holds a Ph.D. in Computer Science from National Sun Yat-sen University (2014-2018) and has been with NCCU since February 2020. His research focuses on advanced cryptography and information security. Research Interests: Dr. Tseng specializes in post-quantum cryptography, cloud security frameworks, and encrypted data systems. His core innovations include: Quantum-resistant encryption schemes (lattice/isogeny-based) Secure data sharing in cloud/IIoT environments Identity-based cryptographic systems Efficient searchable encryption protocols Blockchain security applications Publication Trends: His 15 most recent articles demonstrate concentrated work in quantum-resistant cryptosystems (7 papers), enhanced encryption for cloud/IoT (6 papers), and advanced searchable encryption (5 papers), with consistent focus on practical cryptographic efficiency. Awards: Academic Research Excellence Award, NCCU (2022) Research Projects: Principal Investigator for NSTC grants including: Post-quantum blockchain security mechanisms (2024-2025) Cryptography for consortium blockchains (2022-2023) Co-investigator for multi-year FinTech security projects (2021-2025) focusing on digital currencies and privacy technologies. Lab Affiliations: Contributes to NCCU's Software Security Lab and IT Innovation Lab, focusing on cryptographic protocol design and security analysis for emerging technologies.

Vicente Alarcon-Aquinoمشاهده پروفایل

استاد

• Cybersecurity
• Network Monitoring
• Anomaly Detection
• +۷ مورد دیگر

Dr. Vicente Alarcon-Aquino is a Professor in the Department of Computing, Electronics, and Mechatronics at Universidad de las Americas Puebla (UDLAP), Mexico. He received his Ph.D. and D.I.C. degrees in Electrical and Electronic Engineering from Imperial College London in 2003. He previously served as department head from October 2012 to June 2018 and spent a research stay at King's College London in 2017. Dr. Alarcon-Aquino is a Senior Member of IEEE, a Level I member of the Mexican National System of Researchers (SNI), and a Fellow of the Mexican Academy of Sciences. His educational background includes: Ph.D. and D.I.C. in Electrical and Electronic Engineering, Imperial College London, UK (2003) Dr. Alarcon-Aquino's research focuses on cybersecurity, network monitoring, anomaly detection, wavelet analysis, and machine learning. His work spans theoretical foundations to practical applications in network security, with significant contributions to intrusion detection systems, cryptographic techniques, and machine learning approaches for security applications. He has developed innovative methods combining wavelet transforms with neural networks for various security and signal processing applications. His scholarly contributions include over 180 research articles in refereed journals and conference proceedings, a book on MPLS networks, and numerous citations. As an editor, he serves as Associate Editor for IEEE Access Journal and as Academic & Section Editor for PeerJ Computer Science, focusing on Security & Privacy. Notable professional recognitions include: Senior Member of IEEE Mexican National System of Researchers (SNI Level I) Member of the Mexican Academy of Sciences Dr. Alarcon-Aquino has supervised over 70 theses, including 8 Ph.D. dissertations, 15 Master's theses, and more than 37 Bachelor's theses. His supervision spans topics including network intrusion detection, information security, encryption algorithms, wavelet-based signal processing, neural networks, EEG signal processing, and biometric cryptosystems. He has hosted international research students from institutions including the Polytechnic University of Madrid and Kiel University of Applied Sciences. His research group at UDLAP focuses on developing advanced security solutions for modern network environments, with particular emphasis on applying machine learning techniques to cybersecurity challenges. Current projects include blockchain-based security solutions, federated learning approaches for intrusion detection, and advanced anomaly detection systems for IoT environments.