Search Results for author:
Found 6 papers, 3 papers with code
An Evaluation of Lightweight Deep Learning Techniques in Medical Imaging for High Precision COVID-19 Diagnostics
Timely and rapid diagnoses are core to informing on optimum interventions that curb the spread of COVID-19.
Utilising Flow Aggregation to Classify Benign Imitating Attacks
The features used in these studies are broadly similar and have demonstrated their effectiveness in situations where cyber-attacks do not imitate benign behaviour.
Leveraging Siamese Networks for One-Shot Intrusion Detection Model
Supervised ML is based upon learning by example, demanding significant volumes of representative instances for effective training and the need to re-train the model for every unseen cyber-attack class.
AndroShield: Automated Android Applications Vulnerability Detection, a Hybrid Static and Dynamic Analysis Approach
The security of mobile applications has become a major research field which is associated with a lot of challenges.
Improving SIEM for Critical SCADA Water Infrastructures Using Machine Learning
Like other Internet of Things (IoT) implementations, SCADA systems are vulnerable to cyber-attacks, therefore, a robust anomaly detection is a major requirement.
A Taxonomy of Network Threats and the Effect of Current Datasets on Intrusion Detection Systems
This manuscript aims to pinpoint research gaps and shortcomings of current datasets, their impact on building Network Intrusion Detection Systems (NIDS) and the growing number of sophisticated threats.
