Results 51 to 60 of about 23,085,884 (219)
VAE‐Based SPC for Botnet Detection in IoT Systems
ABSTRACT The rapid proliferation of Internet of Things (IoT) devices has created new security risks, particularly botnet infections. This paper proposes an unsupervised monitoring framework that combines a β$\beta$‐variational autoencoder (VAE) with multivariate statistical process control (SPC) for botnet detection in IoT networks.
Jorge Proaño +3 more
wiley +1 more source
Boutique Malware – Custom made for e-business [PDF]
Malware are typically known through extensive publicity in the media when incidents such as infection by Conficker on the computers around the globe. Such Malware infects all who are vulnerable to its bite.
Fung, C.C., Pan, J.Y.
core
Normal‐Mode‐Aware Augmented Kernel One‐Class SVM for Heterogeneous Normality Modeling
Despite the rapid advances in anomaly detection, many existing methods assume that normal data are homogeneous and can be modeled by a single one‐class boundary. However, in many practical scenarios, normal data are heterogeneous and consist of multiple latent modes, making conventional latent‐space kernels insufficient to characterize normality.
Wenqian Yu, Jiaying Wu, Jinglu Hu
wiley +1 more source
Devious chatbots - interactive malware with a plot [PDF]
Many social robots in the forms of conversation agents or Chatbots have been put to practical use in recent years. Their typical roles are online help or acting as a cyber agent representing an organisation.
Wong, K.W., Fung, C.C., Pan, J.Y.
core
Fighting fire with fire – a Pre-emptive approach to restore control over IT assets from malware infection [PDF]
Malware is a major threat as they induce multiple risks to infected organizations. Current Anti-Malware solutions meant to keep Malware away are challenged on how to keep the risks at bay effectively. When a Malware manages to penetrate an organization’s
Pan, J.Y.
core
Anti-analysis trends in banking malware
Banking Malware, has become a popular and ever more prevalent mechanism to monetise malware development. Since the development of the Zeus malware kit in 2007, the frequency and complexity of banking malware has been increasing.
Black, Paul +3 more
core +1 more source
Visualization and deep-learning-based malware variant detection using OpCode-level features
Malicious software (malware) is a major threat to the systems and networks’ security. Although anti-malware products are used to protect systems and networks against malware attacks, obfuscated malware that is capable of evading analysis and detection by
Alhashmi, A. +9 more
core +1 more source
Bayesian Active Malware Analysis
We propose a novel technique for Active Malware Analysis (AMA) formalized as a Bayesian game between an analyzer agent and a malware agent, focusing on the decision making strategy for the analyzer. In our model, the analyzer performs an action on the system to trigger the malware into showing a malicious behavior, i.e., by activating its payload.
Riccardo Sartea +3 more
openaire +3 more sources
Graph neural network‐based attack prediction for communication‐based train control systems
Abstract The Advanced Persistent Threats (APTs) have emerged as one of the key security challenges to industrial control systems. APTs are complex multi‐step attacks, and they are naturally diverse and complex. Therefore, it is important to comprehend the behaviour of APT attackers and anticipate the upcoming attack actions.
Junyi Zhao +3 more
wiley +1 more source
Pattern for malware remediation – A last line of defence tool against Malware in the global communication platform [PDF]
Malware is becoming a major problem to every organization that operates on the global communication platform. The malicious software programs are advancing in sophistication in many ways in order to defeat harden deployed defenses. When an organization’s
Fung, Chun Che +3 more
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