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Found 6 papers, 1 papers with code
Deep Learning-Based Speech and Vision Synthesis to Improve Phishing Attack Detection through a Multi-layer Adaptive Framework
The ever-evolving ways attacker continues to im prove their phishing techniques to bypass existing state-of-the-art phishing detection methods pose a mountain of challenges to researchers in both industry and academia research due to the inability of current approaches to detect complex phishing attack.
An Investigation into the Performances of the State-of-the-art Machine Learning Approaches for Various Cyber-attack Detection: A Survey
Of all the proposed methods, machine learning had been the most effective method in securing a system with capabilities ranging from early detection of software vulnerabilities to real-time detection of ongoing compromise in a system.
Generation of Games for Opponent Model Differentiation
Attackers in the real world are predominantly human actors, and the protection methods often incorporate opponent models to improve the performance when facing humans.
Performance Comparison and Implementation of Bayesian Variants for Network Intrusion Detection
Bayesian classifiers perform well when each of the features is completely independent of the other which is not always valid in real world application.
Conditional Networks
In this work we tackle the problem of out-of-distribution generalization through conditional computation.
Local Context Normalization: Revisiting Local Normalization
In many vision applications the local spatial context of the features is important, but most common normalization schemes including Group Normalization (GN), Instance Normalization (IN), and Layer Normalization (LN) normalize over the entire spatial dimension of a feature.
