Electrical and Electronic Engineering - Research Publications

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Online Trajectory Anomaly Detection Based on Intention Orientation

Wang, C ; Erfani, S ; Alpcan, T ; Leckie, C (IEEE, 2023-01-01)
Local Intrinsic Dimensionality Signals Adversarial Perturbations

Weerasinghe, S ; Abraham, T ; Alpcan, T ; Erfani, SM ; Leckie, C ; Rubinstein, BIP (IEEE, 2022)
Detection of Anomalous Communications with SDRs and Unsupervised Adversarial Learning

Weerasinghe, S ; Erfani, SM ; Alpcan, T ; Leckie, C ; Riddle, J ; Cherkaoui, S ; Andersson, K ; AlTurjman, F (IEEE, 2019-02-08)

Software-defined radios (SDRs) with substantial cognitive (computing) and networking capabilities provide an opportunity for observing radio communications in an area and potentially identifying malicious rogue agents. Assuming a prevalence of encryption methods, a cognitive network of such SDRs can be used as a low-cost and flexible scanner/sensor array for distributed detection of anomalous communications by focusing on their statistical characteristics. Identifying rogue agents based on their wireless communications patterns is not a trivial task, especially when they deliberately try to mask their activities. We address this problem using a novel framework that utilizes adversarial learning, non-linear data transformations to minimize the rogue agent's attempts at masking their activities, and game theory to predict the behavior of rogue agents and take the necessary countermeasures.