[HTML][HTML] Cyber risk and cybersecurity: a systematic review of data availability

F Cremer, B Sheehan, M Fortmann, AN Kia… - The Geneva papers …, 2022 - ncbi.nlm.nih.gov
Cybercrime is estimated to have cost the global economy just under USD 1 trillion in 2020,
indicating an increase of more than 50% since 2018. With the average cyber insurance …

Naive Bayes: applications, variations and vulnerabilities: a review of literature with code snippets for implementation

I Wickramasinghe, H Kalutarage - Soft Computing, 2021 - Springer
Naïve Bayes (NB) is a well-known probabilistic classification algorithm. It is a simple but
efficient algorithm with a wide variety of real-world applications, ranging from product …

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 …

Android mobile malware detection using machine learning: A systematic review

J Senanayake, H Kalutarage, MO Al-Kadri - Electronics, 2021 - mdpi.com
With the increasing use of mobile devices, malware attacks are rising, especially on Android
phones, which account for 72.2% of the total market share. Hackers try to attack …

Pleasure or pain? An evaluation of the costs and utilities of bloatware applications in android smartphones

H Elahi, G Wang, J Chen - Journal of Network and Computer Applications, 2020 - Elsevier
We investigate the privacy, security, and trust issues of the Android bloatware applications
and evaluate the claims regarding their utility and the coverage of the functional needs of …

Blackmarket-driven collusion on online media: a survey

HS Dutta, T Chakraborty - ACM/IMS Transactions on Data Science (TDS …, 2022 - dl.acm.org
Online media platforms have enabled users to connect with individuals and organizations,
and share their thoughts. Other than connectivity, these platforms also serve multiple …

Android malware detection using multi-stage classification models

MFI Faiz, MA Hussain, N Marchang - Complex, Intelligent and Software …, 2021 - Springer
Android malware is a growing threat to the Android operating system. Various anti-virus
tools are developed to detect Android malware. Most of these tools use Machine Learning …

Hybrid classification model to detect android application-collusion

MFI Faiz, MA Hussain - 2020 43rd International Conference on …, 2020 - ieeexplore.ieee.org
Attacks launch by Android malware are getting harder to detect day by day. One such attack
is Android application-collusion in short app-collusion. In this attack, more than one app …

Detecting Malicious Collusion Between Mobile Software Applications: The Android TM Case

IM Asăvoae, J Blasco, TM Chen, HK Kalutarage… - Data Analytics and …, 2017 - Springer
Malware has been a major problem in desktop computing for decades. With the recent trend
towards mobile computing, malware is moving rapidly to smartphone platforms.“Total mobile …

Detection of collusive app-pairs using machine learning

MFI Faiz, MA Hussain… - 2018 IEEE International …, 2018 - ieeexplore.ieee.org
Mobile app collusion is a scenario where two or more applications work in collaborative
fashion to perform a malicious task. Colluding applications contain a critical set of …