Results 51 to 60 of about 6,055 (181)
Journal of Cybersecurity and Privacy, 2022 Combating the OS-level malware is a very challenging problem as this type of malware can compromise the operating system, obtaining the kernel privilege and subverting almost all the existing anti-malware tools.
Niusen Chen, Bo Chen
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Assessment of a Model‐Based Approach to Achieve Authorization to Operate
Systems Engineering, EarlyView.ABSTRACT Accreditation of United States Government (USG) Information Systems (IS) is required to assure their function and security before delivery to the operational environment. However, in many cases, the baseline document‐based accreditation processes are sources of cost and schedule overruns.
Edan C. Sanchez +2 more
wiley +1 more source
Multi-Line Defense Against Windows Adversarial Malware by Using Windows PE Information
IEEE AccessDeep learning has recently been in the spotlight among malware detection researchers in the sense that its training-based robust decision process can lead to efficient and effective malware detection.
Hannah Ho, Jun-Won Ho, Sungjin Ho
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DQN‐Guided Subset‐Induced OCSVM Kernel Approximation for Imbalanced Anomaly Detection
IEEJ Transactions on Electrical and Electronic Engineering, EarlyView.Anomaly detection under limited normal data remains a fundamental challenge due to severe class imbalance and scarcity of anomalies. We propose a novel framework that reformulates support vector selection in One‐Class SVM as a sequential decision‐making problem.
Wenqian Yu, Jiaying Wu, Jinglu Hu
wiley +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
CAAI Transactions on Intelligence Technology, EarlyView.Abstract Graph neural networks (GNNs) have revolutionised the processing of information by facilitating the transmission of messages between graph nodes. Graph neural networks operate on graph‐structured data, which makes them suitable for a wide variety of computer vision problems, such as link prediction, node classification, and graph classification.
Amit Sharma +4 more
wiley +1 more source
Survey on Visualization of Information Diffusion over Networks
Computer Graphics Forum, EarlyView.Abstract Information Diffusion (ID) describes how a value (e.g., a pathogen, a rumor, a packet) spreads through an underlying “medium” network of elements (e.g., a social or computer network). Understanding the information diffusion process is essential to predicting trends, controlling misinformation, and enhancing decision‐making as well as ...
T. Baumgartl +8 more
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Cyberattacks on Small Banks and the Impact on Local Banking Markets
Journal of Money, Credit and Banking, EarlyView.Abstract Cyberattacks on small banks have direct and spillover effects in local markets. Following successful cyberattacks, hacked small banks experience a decline in deposit growth rates. This effect of cyberattacks is not observed in hacked large banks.
FABIAN GOGOLIN +2 more
wiley +1 more source
Journal of Information Processing and Management, 2002 ネットワーク社会を迎えて，われわれは日々，ウィルス，トロイの馬，ワームなどといったコンピュータシステムに対する脅威にさらされている。このような悪性ソフトウエアは，ハードウエアの性能向上，ソフトウエアの利便性の向上，ネットワークへの社会活動の依存度の増大にともなって進化を遂げてきた。悪性ソフトウエアとは何か，そして，それを防ぐ手だてはあるのだろうか？本稿では，悪性ソフトウエアが誕生し，発展してきた歴史的な背景から悪性ソフトウエアの問題点について議論し，現状で取りうる方策について述べる。
openaire +2 more sources
Applied Sciences, 2020 Traditional malware classification relies on known malware types and significantly large datasets labeled manually which limits its ability to recognize new malware classes.
Zhijie Tang, Peng Wang, Junfeng Wang
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