Fietyata Yudha, Ph.D.
Assistant Professor, Department of Informatics, Universitas Islam Indonesia
KH. Mas Mansyur Bld
Universitas Islam Indonesia
Jl. Kaliurang KM. 14,5 Sleman
Yogyakarta 55584, Indonesia
Fietyata Yudha received the Ph.D. degree from the Electrical Engineering and Computer Science International Graduate Program, National Yang Ming Chiao Tung University (NYCU), Taiwan, in 2025, the M.S. degree in Digital Forensics from Universitas Islam Indonesia (UII), Indonesia, in 2013, and the B.S. degree in Computer Science from UII in 2011. He is currently an Assistant Professor with the Department of Informatics, Universitas Islam Indonesia, and a member of the Center for Digital Forensic Studies (CDFS), where he has been affiliated since 2014.
His research interests include AI for cybersecurity, network security, ethical hacking, and digital forensics. During his doctoral studies at NYCU, he conducted research at the High Speed Networking Laboratory under the supervision of Prof. Ying-Dar Lin, focusing on network security and AI-driven approaches. He also served as a Research Assistant at the Industrial Technology Research Institute (ITRI), Taiwan, where he designed Kubernetes-based testbeds and generated high-fidelity network traffic datasets for security research.
Beyond academia, he is an active professional in the cybersecurity community. He is a Certified EC-Council Instructor (CEI), authorized to deliver training for the Certified Ethical Hacker (CEH) and Certified Hacking Forensic Investigator (CHFI) programs, and holds Cellebrite certifications including Cellebrite Certified Operator (CCO) and Cellebrite Certified Physical Analyst (CCPA) in mobile device forensics. He is also a trainer at IDNIC (Indonesia Network Information Center).
He has received several award including the Taiwan Scholarship, Beasiswa Unggulan from the Ministry of Education and Culture of Indonesia, and Fellowships from the Asia Pacific Regional Internet Conference on Operational Technologies (APRICOT) and the Asia Pacific Advanced Network (APAN) Meeting 48.
selected publications
- PublishedReproducing ATT&CK Techniques and Lifecycles to Train Machine Learning ClassifierIEEE Network, 2025
- PublishedA Scalable Multi-Datasource IDS Dataset with Technique and Lifecycle Labels Based on MITRE ATT&CKIn 2025 IEEE Conference on Dependable and Secure Computing (DSC), 2025
- PublishedFrom Flow to Packet: A Unified Machine Learning Approach for Advanced Intrusion DetectionSecurity and Communication Networks, 2025
- PublishedTwo-Stage Multi-Datasource Machine Learning for Attack Technique and Lifecycle DetectionComputers & Security, 2024