Mobile malware attacks: Review, taxonomy & future directions

A Qamar, A Karim, V Chang - Future Generation Computer Systems, 2019 - Elsevier
A pervasive increase in the adoption rate of smartphones with Android OS is noted in recent
years. Android's popular and attractive environment not only captured the attention of users …

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 …

[HTML][HTML] DL-Droid: Deep learning based android malware detection using real devices

MK Alzaylaee, SY Yerima, S Sezer - Computers & Security, 2020 - Elsevier
The Android operating system has been the most popular for smartphones and tablets since
2012. This popularity has led to a rapid raise of Android malware in recent years. The …

Effective and efficient hybrid android malware classification using pseudo-label stacked auto-encoder

S Mahdavifar, D Alhadidi, AA Ghorbani - Journal of network and systems …, 2022 - Springer
Android has become the target of attackers because of its popularity. The detection of
Android mobile malware has become increasingly important due to its significant threat …

Dynamic android malware category classification using semi-supervised deep learning

S Mahdavifar, AFA Kadir, R Fatemi… - 2020 IEEE Intl Conf …, 2020 - ieeexplore.ieee.org
Due to the significant threat of Android mobile malware, its detection has become
increasingly important. Despite the academic and industrial attempts, devising a robust and …

A system call-based android malware detection approach with homogeneous & heterogeneous ensemble machine learning

P Bhat, S Behal, K Dutta - Computers & Security, 2023 - Elsevier
The enormous popularity of Android in the smartphone market has gained the attention of
malicious actors as well. Also, considering its open system architecture, malicious attacks …

[PDF][PDF] Iotguard: Dynamic enforcement of security and safety policy in commodity IoT.

ZB Celik, G Tan, PD McDaniel - NDSS, 2019 - cs.uwaterloo.ca
Broadly defined as the Internet of Things (IoT), the growth of commodity devices that
integrate physical processes with digital connectivity has changed the way we live, play, and …

Deep ground truth analysis of current android malware

F Wei, Y Li, S Roy, X Ou, W Zhou - … , DIMVA 2017, Bonn, Germany, July 6-7 …, 2017 - Springer
To build effective malware analysis techniques and to evaluate new detection tools, up-to-
date datasets reflecting the current Android malware landscape are essential. For such …

{Explanation-Guided} backdoor poisoning attacks against malware classifiers

G Severi, J Meyer, S Coull, A Oprea - 30th USENIX security symposium …, 2021 - usenix.org
Training pipelines for machine learning (ML) based malware classification often rely on
crowdsourced threat feeds, exposing a natural attack injection point. In this paper, we study …

Droidcat: Effective android malware detection and categorization via app-level profiling

H Cai, N Meng, B Ryder, D Yao - IEEE Transactions on …, 2018 - ieeexplore.ieee.org
Most existing Android malware detection and categorization techniques are static
approaches, which suffer from evasion attacks, such as obfuscation. By analyzing program …