Results 51 to 60 of about 4,213 (184)

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, John M. “Mike” Borky, Thomas H. Bradley   +2 more
wiley   +1 more source

Windows Malware Detection Under the Machine Learning Models and Neutrosophic Numbers [PDF]

Neutrosophic Sets and Systems
Significant cybersecurity risks are posed by malware assaults on Windows computers, which call for efficient detection and prevention systems.
Alber S. Aziz, Mohamed eassa, Ahmed Abdelhafeez, Ahmed A. Metwaly, Ashraf. M. Hussein , Nariman A. Khalil   +5 more
doaj   +1 more source

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

TTGNet-AMD: Android malware detection based on multi-modal feature fusion [PDF]

PeerJ Computer Science
The application of static features for Android malware detection has been extensively studied and developed. Existing methods exhibit limitations in both the completeness and discriminability of feature representation, which affects the enhancement of ...
Jiayin Feng, Meiyu Wang, JinLing Song, Chenfeng Yang, Lingzu Zhang, Yang Shen   +5 more
doaj   +2 more sources

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, Tao Tang, Bing Bu, Qichang Li   +3 more
wiley   +1 more source

Design and Performance Analysis of an Anti-Malware System Based on Generative Adversarial Network Framework

IEEE Access
The cyber realm is overwhelmed with dynamic malware that promptly penetrates all defense mechanisms, operates unapprehended to the user, and covertly causes damage to sensitive data.
Faiza Babar Khan, Muhammad Hanif Durad, Asifullah Khan, Farrukh Aslam Khan, Muhammad Rizwan, Aftab Ali   +5 more
doaj   +1 more source

Image and video analysis using graph neural network for Internet of Medical Things and computer vision applications

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, Ashutosh Sharma, Alexey Tselykh, Alexander Bozhenyuk, Byung‐Gyu Kim   +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, M. Sondag, V. Filipov, M. Tuscher, S. Rajendran, S. Miksch, D. Archambault, A. Arleo, T. von Landesberger   +8 more
wiley   +1 more source

BlockDroid: detection of Android malware from images using lightweight convolutional neural network models with ensemble learning and blockchain for mobile devices [PDF]

PeerJ Computer Science
Due to the increase in the volume and diversity of malware targeting Android systems, research on detecting this harmful software is steadily growing. Traditional malware detection studies require significant human intervention and resource consumption ...
Emre Şafak, İbrahim Alper Doğru, Necaattin Barışçı, İsmail Atacak   +3 more
doaj   +2 more sources

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, IVAN LIM, FRANCESCO VALLASCAS   +2 more
wiley   +1 more source