Results 81 to 90 of about 16,685 (199)
Mobile SDNs: Associating End‐User Commands with Network Flows in Android Devices
IET Communications, Volume 19, Issue 1, January/December 2025.In our research, we combine user interface context with network flow data to improve network profiling on Android, achieving over 98.5% accuracy. We create “AppJudicator”, an Android access control app using host‐based SDN and default Android APIs, effectively addressing security concerns in enterprise networks.
Shuwen Liu +4 more
wiley +1 more source
IET Cyber-Physical Systems: Theory &Applications, Volume 10, Issue 1, January/December 2025.The article proposes a novel concept of autonomous device protection based on behavioural profiling by continuously monitoring internal resource usage and exploiting a large language model to distinguish between benign and malicious behaviour. Abstract Demand for autonomous protection in computing devices cannot go unnoticed, considering the rapid ...
Sandeep Gupta, Bruno Crispo
wiley +1 more source
Review of Android Malware Detection Based on Deep Learning
IEEE Access, 2020 At present, smartphones running the Android operating system have occupied the leading market share. However, due to the Android operating system's open-source nature, Android malware has increased dramatically.
Zhiqiang Wang, Qian Liu, Yaping Chi
doaj +1 more source
IET Cyber-Physical Systems: Theory &Applications, Volume 10, Issue 1, January/December 2025.This paper addresses a critical gap in the literature of industrial robotics cybersecurity by presenting a comprehensive analysis of vulnerabilities in the sensing systems of industrial robots. In particular, we systematically explore how sensor performance limits, faults and biases can be exploited by attackers who can then turn these inherent ...
Abdul Kareem Shaik +2 more
wiley +1 more source
Alexandria Engineering JournalWith the fast growth of mobile phone usage, malicious threats against Android mobile devices are enhanced. The Android system utilizes a wide range of sensitive apps like banking apps; thus, it develops the aim of malware that uses the vulnerability of ...
Shoayee Dlaim Alotaibi +7 more
doaj +1 more source
AEDroid: Adaptive Enhanced Android Malware Detection‐Based on Interpretability of Deep Learning
IET Information Security, Volume 2025, Issue 1, 2025.As the most widely used operating system in the world, Android has naturally become the main target of malicious hackers. The current research on Android malware detection relies on manually defined sensitive API feature sets. With the continuous innovation and change of malicious behavior, new threats and attack methods have emerged.
Pengfei Liu +5 more
wiley +1 more source
XAI and Android Malware Models
Android malware detection based on machine learning (ML) and deep learning (DL) models is widely used for mobile device security. Such models offer benefits in terms of detection accuracy and efficiency, but it is often difficult to understand how such learning models make decisions. As a result, these popular malware detection strategies are generally
Maithili Kulkarni, Mark Stamp
openaire +2 more sources
Backdoor Attack and Defense Methods for AI–Based IoT Intrusion Detection System
IET Information Security, Volume 2025, Issue 1, 2025.The Internet of Things (IoT) is an emerging technology that has attracted significant attention and triggered a technical revolution in recent years. Numerous IoT devices are directly connected to the physical world, such as security cameras and medical equipment, making IoT security a critical issue.
Bowen Ma +5 more
wiley +1 more source
ANFIS-AMAL: Android Malware Threat Assessment Using Ensemble of ANFIS and GWO
Cybernetics and Information TechnologiesThe Android malware has various features and capabilities. Various malware has distinctive characteristics. Ransomware threatens financial loss and system lockdown.
Nwasra Nedal +2 more
doaj +1 more source
A family of droids -- Android malware detection via behavioral modeling: static vs dynamic analysis [PDF]
, 2019 Following the increasing popularity of mobile ecosystems, cybercriminals have increasingly targeted them, designing and distributing malicious apps that steal information or cause harm to the device's owner.
Almeida, Mario +5 more
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