Publications: Studiawan, Hudan

Journal Article

Studiawan, H., Sohel, F. and Payne, C. (2020) Anomaly detection in operating system logs with deep Learning-based sentiment analysis. IEEE Transactions on Dependable and Secure Computing, 18 (5). pp. 2136-2148.

Studiawan, H., Sohel, F. and Payne, C. (2020) Sentiment analysis in a forensic timeline with deep learning. IEEE Access, 8 . pp. 60664-60675.

Studiawan, H., Sohel, F. and Payne, C. (2019) A survey on forensic investigation of operating system logs. Digital Investigation, 29 . pp. 1-20.

Studiawan, H., Payne, C. and Sohel, F. (2017) Graph clustering and anomaly detection of access control log for forensic purposes. Digital Investigation, 21 . pp. 76-87.

Conference Paper

Studiawan, H., Sohel, F. and Payne, C. (2020) Automatic event log abstraction to support forensic investigation. In: ACSW '20: Australasian Computer Science Week 2020, 3 - 7 February 2020, Swinburne University of Technology, Melbourne

Studiawan, H. and Sohel, F. (2020) Performance evaluation of anomaly detection in imbalanced system log data. In: 2020 Fourth World Conference on Smart Trends in Systems, Security and Sustainability (WorldS4), 27 - 28 July 2020, London, UK

Shiddiqi, A.M., Baskoro, F., Wijaya, A.Y. and Studiawan, H. (2019) Sensor energy preservation for leak quantification using Distance-Based feature selection method. In: 12th International Conference on Information & Communication Technology and System (ICTS) 2019, 18 July 2019, Surabaya, Indonesia

Studiawan, H., Sohel, F. and Payne, C. (2018) Automatic log parser to support forensic analysis. In: 16th Australian Digital Forensics Conference, 4 - 5 December 2018, Edith Cowan, Joondalup

Book Chapter

Studiawan, H., Payne, C. and Sohel, F. (2019) Automatic Graph-Based clustering for security logs. In: Barolli, L., Takizawa, M., Xhafa, F. and Enokido, T., (eds.) Primate Life Histories, Sex Roles, and Adaptability. Springer, pp. 914-926.

Thesis

Studiawan, Hudan (2020) Forensic investigation of event logs by automatic anomaly detection. PhD thesis, Murdoch University.