Application domains, evaluation data sets, and research challenges of IoT: A systematic review

R Lohiya, A Thakkar - IEEE Internet of Things Journal, 2020 - ieeexplore.ieee.org
We are at the brink of Internet of Things (IoT) era where smart devices and other wireless
devices are redesigning our environment to make it more correlative, flexible, and …

Malicious application detection in android—a systematic literature review

T Sharma, D Rattan - Computer Science Review, 2021 - Elsevier
Context: In last decade, due to tremendous usage of smart phones it seems that these
gadgets became an essential necessity of day-to-day life. People are using new …

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 …

MLDroid—framework for Android malware detection using machine learning techniques

A Mahindru, AL Sangal - Neural Computing and Applications, 2021 - Springer
This research paper presents MLDroid—a web-based framework—which helps to detect
malware from Android devices. Due to increase in the popularity of Android devices …

Toward developing a systematic approach to generate benchmark android malware datasets and classification

AH Lashkari, AFA Kadir, L Taheri… - … conference on security …, 2018 - ieeexplore.ieee.org
Malware detection is one of the most important factors in the security of smartphones.
Academic researchers have extensively studied Android malware detection problems …

Artificial intelligence algorithms for malware detection in android-operated mobile devices

H Alkahtani, THH Aldhyani - Sensors, 2022 - mdpi.com
With the rapid expansion of the use of smartphone devices, malicious attacks against
Android mobile devices have increased. The Android system adopted a wide range of …

[HTML][HTML] Kronodroid: time-based hybrid-featured dataset for effective android malware detection and characterization

A Guerra-Manzanares, H Bahsi, S Nõmm - Computers & Security, 2021 - Elsevier
Android malware evolution has been neglected by the available data sets, thus providing a
static snapshot of a non-stationary phenomenon. The impact of the time variable has not had …

Deep learning for effective Android malware detection using API call graph embeddings

A Pektaş, T Acarman - Soft Computing, 2020 - Springer
High penetration of Android applications along with their malicious variants requires efficient
and effective malware detection methods to build mobile platform security. API call …

A taxonomy and qualitative comparison of program analysis techniques for security assessment of android software

A Sadeghi, H Bagheri, J Garcia… - IEEE Transactions on …, 2016 - ieeexplore.ieee.org
In parallel with the meteoric rise of mobile software, we are witnessing an alarming
escalation in the number and sophistication of the security threats targeted at mobile …