Machine learning algorithms for network intrusion detection

J Li, Y Qu, F Chao, HPH Shum, ESL Ho, L Yang - AI in Cybersecurity, 2019 - Springer
Network intrusion is a growing threat with potentially severe impacts, which can be
damaging in multiple ways to network infrastructures and digital/intellectual assets in the …

Dynamic fuzzy rule interpolation and its application to intrusion detection

N Naik, R Diao, Q Shen - IEEE Transactions on Fuzzy Systems, 2017 - ieeexplore.ieee.org
Fuzzy rule interpolation (FRI) offers an effective approach for making inference possible in
sparse rule-based systems (and also for reducing the complexity of fuzzy models). However …

Feature selection with harmony search

R Diao, Q Shen - IEEE Transactions on Systems, Man, and …, 2012 - ieeexplore.ieee.org
Many search strategies have been exploited for the task of feature selection (FS), in an effort
to identify more compact and better quality subsets. Such work typically involves the use of …

Backward fuzzy rule interpolation

S **, R Diao, C Quek, Q Shen - IEEE Transactions on Fuzzy …, 2014 - ieeexplore.ieee.org
Fuzzy rule interpolation offers a useful means to enhancing the robustness of fuzzy models
by making inference possible in sparse rule-based systems. However, in real-world …

Cyberthreat Hunting-Part 1: triaging ransomware using fuzzy hashing, import hashing and YARA rules

N Naik, P Jenkins, N Savage… - 2019 IEEE International …, 2019 - ieeexplore.ieee.org
Ransomware is currently one of the most significant cyberthreats to both national
infrastructure and the individual, often requiring severe treatment as an antidote. Triaging …

Honeypots that bite back: A fuzzy technique for identifying and inhibiting fingerprinting attacks on low interaction honeypots

N Naik, P Jenkins, R Cooke… - 2018 IEEE International …, 2018 - ieeexplore.ieee.org
The development of a robust strategy for network security is reliant upon a combination of in-
house expertise and for completeness attack vectors used by attackers. A honeypot is one of …

Cyberthreat hunting-part 2: Tracking ransomware threat actors using fuzzy hashing and fuzzy c-means clustering

N Naik, P Jenkins, N Savage… - 2019 IEEE international …, 2019 - ieeexplore.ieee.org
Threat actors are constantly seeking new attack surfaces, with ransomeware being one the
most successful attack vectors that have been used for financial gain. T his has been …

A fuzzy approach for detecting and defending against spoofing attacks on low interaction honeypots

N Naik, P Jenkins - 2018 21st International Conference on …, 2018 - ieeexplore.ieee.org
Honeypots are a well-recognised entrapment mechanism for baiting attackers in the field of
network security. They gather real-time and valuable information from the attacker regarding …

Genetic algorithm-aided dynamic fuzzy rule interpolation

N Naik, R Diao, Q Shen - 2014 IEEE International Conference …, 2014 - ieeexplore.ieee.org
Fuzzy rule interpolation (FRI) is a well established area for reducing the complexity of fuzzy
models and for making inference possible in sparse rule-based systems. Regardless of the …

Big data security analysis approach using computational intelligence techniques in R for desktop users

N Naik, P Jenkins, N Savage… - 2016 IEEE Symposium …, 2016 - ieeexplore.ieee.org
Big Data security analysis is commonly used for the analysis of large volume security data
from an organisational perspective, requiring powerful IT infrastructure and expensive data …