Wireless powered mobile edge computing networks: A survey

X Wang, J Li, Z Ning, Q Song, L Guo, S Guo… - ACM Computing …, 2023 - dl.acm.org
Wireless Powered Mobile Edge Computing (WPMEC) is an integration of Mobile Edge
Computing (MEC) and Wireless Power Transfer (WPT) technologies, to both improve …

Machine learning–based cyber attacks targeting on controlled information: A survey

Y Miao, C Chen, L Pan, QL Han, J Zhang… - ACM Computing Surveys …, 2021 - dl.acm.org
Stealing attack against controlled information, along with the increasing number of
information leakage incidents, has become an emerging cyber security threat in recent …

Deep learning based attack detection for cyber-physical system cybersecurity: A survey

J Zhang, L Pan, QL Han, C Chen… - IEEE/CAA Journal of …, 2021 - ieeexplore.ieee.org
With the booming of cyber attacks and cyber criminals against cyber-physical systems
(CPSs), detecting these attacks remains challenging. It might be the worst of times, but it …

Malware detection using deep learning and correlation-based feature selection

ES Alomari, RR Nuiaa, ZAA Alyasseri, HJ Mohammed… - Symmetry, 2023 - mdpi.com
Malware is one of the most frequent cyberattacks, with its prevalence growing daily across
the network. Malware traffic is always asymmetrical compared to benign traffic, which is …

Detecting vulnerability on IoT device firmware: A survey

X Feng, X Zhu, QL Han, W Zhou… - IEEE/CAA Journal of …, 2022 - ieeexplore.ieee.org
Internet of things (IoT) devices make up 30% of all network-connected endpoints,
introducing vulnerabilities and novel attacks that make many companies as primary targets …

Mobile operating system (Android) vulnerability analysis using machine learning

V Mahor, K Pachlasiya, B Garg, M Chouhan… - … Conference on Network …, 2021 - Springer
Because of the computational processing, seamless functioning and benefits that it gives to
Android-users, cyber thieves have been drawn towards it. Conventional AMD: android …

Deep learning for android malware defenses: a systematic literature review

Y Liu, C Tantithamthavorn, L Li, Y Liu - ACM Computing Surveys, 2022 - dl.acm.org
Malicious applications (particularly those targeting the Android platform) pose a serious
threat to developers and end-users. Numerous research efforts have been devoted to …

Deep learning for zero-day malware detection and classification: A survey

F Deldar, M Abadi - ACM Computing Surveys, 2023 - dl.acm.org
Zero-day malware is malware that has never been seen before or is so new that no anti-
malware software can catch it. This novelty and the lack of existing mitigation strategies …

A survey of malware analysis using community detection algorithms

A Amira, A Derhab, EB Karbab, O Nouali - ACM Computing Surveys, 2023 - dl.acm.org
In recent years, we have witnessed an overwhelming and fast proliferation of different types
of malware targeting organizations and individuals, which considerably increased the time …

Cyber code intelligence for android malware detection

J Qiu, QL Han, W Luo, L Pan, S Nepal… - IEEE Transactions …, 2022 - ieeexplore.ieee.org
Evolving Android malware poses a severe security threat to mobile users, and machine-
learning (ML)-based defense techniques attract active research. Due to the lack of …