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 …

Measuring and modeling the label dynamics of online {Anti-Malware} engines

S Zhu, J Shi, L Yang, B Qin, Z Zhang, L Song… - 29th USENIX Security …, 2020 - usenix.org
VirusTotal provides malware labels from a large set of anti-malware engines, and is heavily
used by researchers for malware annotation and system evaluation. Since different engines …

Understanding android obfuscation techniques: A large-scale investigation in the wild

S Dong, M Li, W Diao, X Liu, J Liu, Z Li, F Xu… - Security and privacy in …, 2018 - Springer
Program code is a valuable asset to its owner. Due to the easy-to-reverse nature of Java,
code protection for Android apps is of particular importance. To this end, code obfuscation is …

A close look at a daily dataset of malware samples

X Ugarte-Pedrero, M Graziano… - ACM Transactions on …, 2019 - dl.acm.org
The number of unique malware samples is growing out of control. Over the years, security
companies have designed and deployed complex infrastructures to collect and analyze this …

Machine-Learning based analysis and classification of Android malware signatures

I Martín, JA Hernández, S de los Santos - Future Generation Computer …, 2019 - Elsevier
Multi-scanner Antivirus (AV) systems are often used for detecting Android malware since the
same piece of software can be checked against multiple different AV engines. However, in …

The Effect of the Ransomware Dataset Age on the Detection Accuracy of Machine Learning Models

QM Yaseen - Information, 2023 - mdpi.com
Several supervised machine learning models have been proposed and used to detect
Android ransomware. These models were trained using different datasets from different …

Re-measuring the label dynamics of online anti-malware engines from millions of samples

J Wang, L Wang, F Dong, H Wang - Proceedings of the 2023 ACM on …, 2023 - dl.acm.org
VirusTotal is the most widely used online scanning service in both academia and industry.
However, it is known that the results returned by antivirus engines are often inconsistent and …

MalNet: A binary-centric network-level profiling of IoT malware

A Davanian, M Faloutsos - Proceedings of the 22nd ACM Internet …, 2022 - dl.acm.org
Where are the IoT C2 servers located? What vulnerabilities does IoT malware try to exploit?
What DDoS attacks are launched in practice? In this work, we conduct a large scale study to …

Advances in computer communication and computational sciences

SK Bhatia, S Tiwari, KK Mishra, MC Trivedi - Proceedings of IC4S, 2017 - Springer
The IC4S is a major multidisciplinary conference organized with the objective of bringing
together researchers, developers, and practitioners from academia and industry working in …

Towards {Large-Scale} Hunting for Android {Negative-Day} Malware

LP Yuan, W Hu, T Yu, P Liu, S Zhu - 22nd International Symposium on …, 2019 - usenix.org
Android malware writers often utilize online malware scanners to check how well their
malware can evade detection, and indeed we can find malware scan reports that were …