Results 101 to 110 of about 134,256 (265)
PlaceRaider: Virtual Theft in Physical Spaces with Smartphones [PDF]
, 2012 As smartphones become more pervasive, they are increasingly targeted by malware. At the same time, each new generation of smartphone features increasingly powerful onboard sensor suites.
Crandall, David +3 more
core
Energy Science &Engineering, Volume 14, Issue 3, Page 1431-1455, March 2026.Overview of the proposed work. ABSTRACT Identifying cyber threats maintains the security and operational stability of smart grid systems because they experience escalating attacks that endanger both operating data reliability and system stability and electricity grid performance.
Priya R. Karpaga +3 more
wiley +1 more source
A3CM: Automatic Capability Annotation for Android Malware
IEEE Access, 2019 Android malware poses serious security and privacy threats to the mobile users. Traditional malware detection and family classification technologies are becoming less effective due to the rapid evolution of the malware landscape, with the emerging of so ...
Junyang Qiu +6 more
doaj +1 more source
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
doaj +1 more source
A Review of Android Malware Detection Approaches Based on Machine Learning
IEEE Access, 2020 Android applications are developing rapidly across the mobile ecosystem, but Android malware is also emerging in an endless stream. Many researchers have studied the problem of Android malware detection and have put forward theories and methods from ...
Kaijun Liu +5 more
semanticscholar +1 more source
Mission Aware Cyber‐Physical Security
Systems Engineering, Volume 29, Issue 2, Page 354-367, March 2026.ABSTRACT Perimeter cybersecurity, while essential, has proven insufficient against sophisticated, coordinated, and cyber‐physical attacks. In contrast, mission‐centric cybersecurity emphasizes finding evidence of attack impact on mission success, allowing for targeted resource allocation to mitigate vulnerabilities and protect critical assets.
Georgios Bakirtzis +3 more
wiley +1 more source
Significant Permission Identification for Machine-Learning-Based Android Malware Detection
IEEE Transactions on Industrial Informatics, 2018 The alarming growth rate of malicious apps has become a serious issue that sets back the prosperous mobile ecosystem. A recent report indicates that a new malicious app for Android is introduced every 10 s.
Jin Li +5 more
semanticscholar +1 more source
Expert Systems, Volume 43, Issue 3, March 2026.ABSTRACT Zero‐day exploits remain challenging to detect because they often appear in unknown distributions of signatures and rules. The article entails a systematic review and cross‐sectional synthesis of four fundamental model families for identifying zero‐day intrusions, namely, convolutional neural networks (CNN), deep neural networks (DNN ...
Abdullah Al Siam +3 more
wiley +1 more source
A cybersecurity risk analysis framework for systems with artificial intelligence components
International Transactions in Operational Research, Volume 33, Issue 2, Page 798-825, March 2026.Abstract The introduction of the European Union Artificial Intelligence (AI) Act, the NIST AI Risk Management Framework, and related international norms and policy documents demand a better understanding and implementation of novel risk analysis issues when facing systems with AI components: dealing with new AI‐related impacts; incorporating AI‐based ...
J.M. Camacho +3 more
wiley +1 more source
The Journal of World Intellectual Property, Volume 29, Issue 1, Page 130-161, March 2026.Abstract Understanding the role of information communication technologies (ICTs) in development, especially in relation to marginalized populations, has been the focus of many related disciplinary categories within the broader ecosystem of information sciences.
Chidi Oguamanam
wiley +1 more source