Results 61 to 70 of about 37,609 (225)
Applied Sciences, 2021 Malware are developed for various types of malicious attacks, e.g., to gain access to a user’s private information or control of the computer system. The identification and classification of malware has been extensively studied in academic societies and ...
Dong-Kyu Chae +4 more
doaj +1 more source
Quantum Information Processing, 2006 When quantum communication networks proliferate they will likely be subject to a new type of attack: by hackers, virus makers, and other malicious intruders. Here we introduce the concept of "quantum malware" to describe such human-made intrusions. We offer a simple solution for storage of quantum information in a manner which protects quantum networks
Lian-Ao Wu, Daniel A. Lidar
openaire +3 more sources
VAE‐Based SPC for Botnet Detection in IoT Systems
Quality and Reliability Engineering International, EarlyView.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]
, 2010 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
Telematics and Informatics ReportsThe ever-increasing growth of online services and smart connectivity of devices have posed the threat of malware to computer system, android-based smart phones, Internet of Things (IoT)-based systems.
Santosh K. Smmarwar +2 more
doaj +1 more source
Normal‐Mode‐Aware Augmented Kernel One‐Class SVM for Heterogeneous Normality Modeling
IEEJ Transactions on Electrical and Electronic Engineering, EarlyView.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]
, 2009 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
Learning and classification of malware behavior
, 2022 S.108-125Malicious software in form of Internet worms, computer viruses, and Trojan horses poses a major threat to the security of networked systems. The diversity and amount of its variants severely undermine the effectiveness of classical signature ...
Düssel, P. +4 more
core +1 more source
Effective and Reliable Malware Group Classification for a Massive Malware Environment
International Journal of Distributed Sensor Networks, 2016 Most of the cyber-attacks are caused by malware, and damage from them has escalated from cyber space to home appliances and infrastructure, thus affecting the daily living of the people. As such, anticipative analysis and countermeasures for malware have
Taejin Lee, Jin Kwak
doaj +1 more source
Graph neural network‐based attack prediction for communication‐based train control systems
CAAI Transactions on Intelligence Technology, EarlyView.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