Challenges and opportunities in edge computing

B Varghese, N Wang, S Barbhuiya… - … conference on smart …, 2016 - ieeexplore.ieee.org
Many cloud-based applications employ a data centers as a central server to process data
that is generated by edge devices, such as smartphones, tablets and wearables. This model …

A survey on sensor-based threats and attacks to smart devices and applications

AK Sikder, G Petracca, H Aksu… - … Surveys & Tutorials, 2021 - ieeexplore.ieee.org
Modern electronic devices have become “smart” as well as omnipresent in our day-to-day
lives. From small household devices to large industrial machines, smart devices have …

Madam: Effective and efficient behavior-based android malware detection and prevention

A Saracino, D Sgandurra, G Dini… - IEEE Transactions on …, 2016 - ieeexplore.ieee.org
Android users are constantly threatened by an increasing number of malicious applications
(apps), generically called malware. Malware constitutes a serious threat to user privacy …

Taintart: A practical multi-level information-flow tracking system for android runtime

M Sun, T Wei, JCS Lui - Proceedings of the 2016 ACM SIGSAC …, 2016 - dl.acm.org
Mobile operating systems like Android failed to provide sufficient protection on personal
data, and privacy leakage becomes a major concern. To understand the security risks and …

An analysis of conti ransomware leaked source codes

S Alzahrani, Y Xiao, W Sun - IEEE Access, 2022 - ieeexplore.ieee.org
In recent years, there has been an increase in ransomware attacks worldwide. These attacks
aim to lock victims' machines or encrypt their files for ransom. These kinds of ransomware …

Survey on enterprise Internet-of-Things systems (E-IoT): A security perspective

LP Rondon, L Babun, A Aris, K Akkaya, AS Uluagac - Ad Hoc Networks, 2022 - Elsevier
As technology becomes more widely available, millions of users worldwide have installed
some form of smart device in their homes or workplaces. These devices are often off-the …

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 …

{6thSense}: A context-aware sensor-based attack detector for smart devices

AK Sikder, H Aksu, AS Uluagac - 26th USENIX Security Symposium …, 2017 - usenix.org
Sensors (eg, light, gyroscope, accelerometer) and sensing enabled applications on a smart
device make the applications more user-friendly and efficient. However, the current …

Monet: a user-oriented behavior-based malware variants detection system for android

M Sun, X Li, JCS Lui, RTB Ma… - IEEE Transactions on …, 2016 - ieeexplore.ieee.org
Android, the most popular mobile OS, has around 78% of the mobile market share. Due to its
popularity, it attracts many malware attacks. In fact, people have discovered around 1 million …

A novel machine learning approach for android malware detection based on the co-existence of features

E Odat, QM Yaseen - IEEE Access, 2023 - ieeexplore.ieee.org
This paper proposes a machine learning model based on the co-existence of static features
for Android malware detection. The proposed model assumes that Android malware …