Digital transformation in toxicology: improving communication and efficiency in risk assessment

AV Singh, G Bansod, M Mahajan, P Dietrich… - ACS …, 2023 - ACS Publications
Toxicology is undergoing a digital revolution, with mobile apps, sensors, artificial
intelligence (AI), and machine learning enabling better record-kee**, data analysis, and …

Android source code vulnerability detection: a systematic literature review

J Senanayake, H Kalutarage, MO Al-Kadri… - ACM Computing …, 2023 - dl.acm.org
The use of mobile devices is rising daily in this technological era. A continuous and
increasing number of mobile applications are constantly offered on mobile marketplaces to …

MAPAS: a practical deep learning-based android malware detection system

J Kim, Y Ban, E Ko, H Cho, JH Yi - International Journal of Information …, 2022 - Springer
A lot of malicious applications appears every day, threatening numerous users. Therefore, a
surge of studies have been conducted to protect users from newly emerging malware by …

The evolution of android malware and android analysis techniques

K Tam, A Feizollah, NB Anuar, R Salleh… - ACM Computing …, 2017 - dl.acm.org
With the integration of mobile devices into daily life, smartphones are privy to increasing
amounts of sensitive information. Sophisticated mobile malware, particularly Android …

A survey of app store analysis for software engineering

W Martin, F Sarro, Y Jia, Y Zhang… - IEEE transactions on …, 2016 - ieeexplore.ieee.org
App Store Analysis studies information about applications obtained from app stores. App
stores provide a wealth of information derived from users that would not exist had the …

On the safety of iot device physical interaction control

W Ding, H Hu - Proceedings of the 2018 ACM SIGSAC Conference on …, 2018 - dl.acm.org
Emerging Internet of Things (IoT) platforms provide increased functionality to enable human
interaction with the physical world in an autonomous manner. The physical interaction …

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 …

Applications in security and evasions in machine learning: a survey

R Sagar, R Jhaveri, C Borrego - Electronics, 2020 - mdpi.com
In recent years, machine learning (ML) has become an important part to yield security and
privacy in various applications. ML is used to address serious issues such as real-time …

[PDF][PDF] Free for all! assessing user data exposure to advertising libraries on android.

S Demetriou, W Merrill, W Yang, A Zhang, CA Gunter - NDSS, 2016 - ndss-symposium.org
Many studies focused on detecting and measuring the security and privacy risks associated
with the integration of advertising libraries in mobile apps. These studies consistently …

[PDF][PDF] A Survey of Android Security Threats and Defenses.

B Rashidi, CJ Fung - J. Wirel. Mob. Networks Ubiquitous Comput …, 2015 - isyou.info
With billions of people using smartphones and the exponential growth of smartphone apps,
it is prohibitive for app marketplaces, such as Google App Store, to thoroughly verify if an …