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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
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
core
Investigation of Android Malware Using Deep Learning Approach [PDF]
, 2022 V. Joseph Raymond, Ritik Raj
openalex +1 more source
, 2021 In the XXI century, the world has witnessed the creation, development and proliferation of mobile devices until the massive usage apparent nowadays. The portability, instantaneity and ease of use that these devices offer has encouraged the great majority of the population to have one of them at arm’s length.
Puente Arribas, Daniel +2 more
openaire +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
HTTP behavior characteristics generation and extraction approach for Android malware
Dianxin kexue, 2016 Growing of Android malware，not only seriously endangered the security of the Android market，but also brings challenges for detection.A generation and extraction approach of automatic Android malware behavioral signatures was proposed based on HTTP ...
Yaling LUO, Wenwei LI, Xin SU
doaj +2 more sources
Why an Android App is Classified as Malware? Towards Malware Classification Interpretation [PDF]
, 2020 Bozhi Wu +6 more
openalex +1 more source
KTSDroid: A Framework for Android Malware Categorization Using the Kernel Task Structure [PDF]
, 2023 Saneeha Khalid +2 more
openalex +1 more source
Mağallaẗ Al-kūfaẗ Al-handasiyyaẗAndroid malware has grown steadily into a major internet threat. Despite efforts to identify and categorize malware in seemingly safe Android apps, addressing this issue is still lacking.
abdullah alsraratee, Ahmed Al-Azawei
doaj +1 more source
Not so Crisp, Malware! Fuzzy Classification of Android Malware Classes
2018 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 2018 Mobile devices have been spreading at great rate in recent years. Not only smartphone, but also tablets and IoT devices, are gaining an increasingly place in our everyday lives. This is the reason why attackers are developing more and more aggressive techniques with the aim to exfiltrate our sensitive and private information.
Mercaldo F., Saracino A.
openaire +4 more sources