Data-driven cybersecurity incident prediction: A survey

N Sun, J Zhang, P Rimba, S Gao… - … surveys & tutorials, 2018 - ieeexplore.ieee.org
Driven by the increasing scale and high profile cybersecurity incidents related public data,
recent years we have witnessed a paradigm shift in understanding and defending against …

A survey of malware detection in Android apps: Recommendations and perspectives for future research

A Razgallah, R Khoury, S Hallé… - Computer Science …, 2021 - Elsevier
Android has dominated the smartphone market and has become the most popular operating
system for mobile devices. However, security threats in Android applications have also …

Maps: Scaling privacy compliance analysis to a million apps

S Zimmeck, P Story, D Smullen… - Proceedings on …, 2019 - petsymposium.org
The app economy is largely reliant on data collection as its primary revenue model. To
comply with legal requirements, app developers are often obligated to notify users of their …

Deeprefiner: Multi-layer android malware detection system applying deep neural networks

K Xu, Y Li, RH Deng, K Chen - 2018 IEEE European …, 2018 - ieeexplore.ieee.org
As malicious behaviors vary significantly across mobile malware, it is challenging to detect
malware both efficiently and effectively. Also due to the continuous evolution of malicious …

On the impact of sample duplication in machine-learning-based android malware detection

Y Zhao, L Li, H Wang, H Cai, TF Bissyandé… - ACM Transactions on …, 2021 - dl.acm.org
Malware detection at scale in the Android realm is often carried out using machine learning
techniques. State-of-the-art approaches such as DREBIN and MaMaDroid are reported to …

Cryptoguard: High precision detection of cryptographic vulnerabilities in massive-sized java projects

S Rahaman, Y Xiao, S Afrose, F Shaon, K Tian… - Proceedings of the …, 2019 - dl.acm.org
Cryptographic API misuses, such as exposed secrets, predictable random numbers, and
vulnerable certificate verification, seriously threaten software security. The vision of …

EveDroid: Event-aware Android malware detection against model degrading for IoT devices

T Lei, Z Qin, Z Wang, Q Li, D Ye - IEEE Internet of Things …, 2019 - ieeexplore.ieee.org
With the proliferation of the smart Internet of Things (IoT) devices based on Android system,
malicious Android applications targeting for IoT devices have received more and more …

" Get in Researchers; We're Measuring Reproducibility": A Reproducibility Study of Machine Learning Papers in Tier 1 Security Conferences

D Olszewski, A Lu, C Stillman, K Warren… - Proceedings of the …, 2023 - dl.acm.org
Reproducibility is crucial to the advancement of science; it strengthens confidence in
seemingly contradictory results and expands the boundaries of known discoveries …

Uncovering and exploiting hidden apis in mobile super apps

C Wang, Y Zhang, Z Lin - Proceedings of the 2023 ACM SIGSAC …, 2023 - dl.acm.org
Mobile applications, particularly those from social media platforms such as WeChat and
TikTok, are evolving into" super apps" that offer a wide range of services such as instant …

Gui-squatting attack: Automated generation of android phishing apps

S Chen, L Fan, C Chen, M Xue, Y Liu… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
Mobile phishing attacks, such as mimic mobile browser pages, masquerade as legitimate
applications by leveraging repackaging or clone techniques, have caused varied yet …