Jill Slay
Jill Slay
University of South Australia SmartSat Chair in Cybersecurity
Verified email at - Homepage
Cited by
Cited by
UNSW-NB15: a comprehensive data set for network intrusion detection systems (UNSW-NB15 network data set)
N Moustafa, J Slay
2015 military communications and information systems conference (MilCIS), 1-6, 2015
Lessons learned from the maroochy water breach
J Slay, M Miller
International conference on critical infrastructure protection, 73-82, 2007
The evaluation of Network Anomaly Detection Systems: Statistical analysis of the UNSW-NB15 data set and the comparison with the KDD99 data set
N Moustafa, J Slay
Information Security Journal: A Global Perspective 25 (1-3), 18-31, 2016
A holistic review of network anomaly detection systems: A comprehensive survey
N Moustafa, J Hu, J Slay
Journal of Network and Computer Applications 128, 33-55, 2019
The significant features of the UNSW-NB15 and the KDD99 data sets for network intrusion detection systems
N Moustafa, J Slay
2015 4th international workshop on building analysis datasets and gathering …, 2015
Novel geometric area analysis technique for anomaly detection using trapezoidal area estimation on large-scale networks
N Moustafa, J Slay, G Creech
IEEE Transactions on Big Data 5 (4), 481-494, 2017
Generating realistic intrusion detection system dataset based on fuzzy qualitative modeling
W Haider, J Hu, J Slay, BP Turnbull, Y Xie
Journal of Network and Computer Applications 87, 185-192, 2017
Validation and verification of computer forensic software tools—Searching Function
Y Guo, J Slay, J Beckett
digital investigation 6, S12-S22, 2009
Big data analytics for intrusion detection system: Statistical decision-making using finite dirichlet mixture models
N Moustafa, G Creech, J Slay
Data analytics and decision support for cybersecurity, 127-156, 2017
A hybrid feature selection for network intrusion detection systems: Central points
N Moustafa, J Slay
arXiv preprint arXiv:1707.05505, 2017
Towards developing network forensic mechanism for botnet activities in the IoT based on machine learning techniques
N Koroniotis, N Moustafa, E Sitnikova, J Slay
International Conference on Mobile Networks and Management, 30-44, 2017
Evaluating host-based anomaly detection systems: Application of the one-class SVM algorithm to ADFA-LD
M Xie, J Hu, J Slay
2014 11th International Conference on Fuzzy Systems and Knowledge Discovery …, 2014
Digital forensics: Validation and verification in a dynamic work environment
J Beckett, J Slay
2007 40th Annual Hawaii International Conference on System Sciences (HICSS …, 2007
Recovery of skype application activity data from physical memory
M Simon, J Slay
2010 International Conference on Availability, Reliability and Security, 283-288, 2010
Money laundering and terrorism financing in virtual environments: a feasibility study
ASM Irwin, J Slay, KKR Choo, L Lui
Journal of Money Laundering Control, 2014
Information technology security and risk management
J Slay, A Koronios
Wiley, 2006
Anomaly detection system using beta mixture models and outlier detection
N Moustafa, G Creech, J Slay
Progress in computing, analytics and networking, 125-135, 2018
Mobile device forensics: A snapshot
C Tassone, B Martini, KKR Choo, J Slay
Trends and Issues in Crime and Criminal Justice, 1-7, 2013
Generalized outlier gaussian mixture technique based on automated association features for simulating and detecting web application attacks
N Moustafa, G Misra, J Slay
IEEE Transactions on Sustainable Computing, 2018
Creating novel features to anomaly network detection using DARPA-2009 data set
N Moustaf, J Slay
Proceedings of the 14th European Conference on Cyber Warfare and Security …, 2015
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