A survey of random forest based methods for intrusion detection systems

PAA Resende, AC Drummond - ACM Computing Surveys (CSUR), 2018 - dl.acm.org
Over the past decades, researchers have been proposing different Intrusion Detection
approaches to deal with the increasing number and complexity of threats for computer …

Mobile malware attacks: Review, taxonomy & future directions

A Qamar, A Karim, V Chang - Future Generation Computer Systems, 2019 - Elsevier
A pervasive increase in the adoption rate of smartphones with Android OS is noted in recent
years. Android's popular and attractive environment not only captured the attention of users …

Datasets are not enough: Challenges in labeling network traffic

JL Guerra, C Catania, E Veas - Computers & Security, 2022 - Elsevier
In contrast to previous surveys, the present work is not focused on reviewing the datasets
used in the network security field. The fact is that many of the available public labeled …

A study on malicious software behaviour analysis and detection techniques: Taxonomy, current trends and challenges

P Maniriho, AN Mahmood, MJM Chowdhury - Future Generation Computer …, 2022 - Elsevier
There has been an increasing trend of malware release, which raises the alarm for security
professionals worldwide. It is often challenging to stay on top of different types of malware …

Mobile botnet detection: a comprehensive survey

S Hamzenejadi, M Ghazvini, S Hosseini - International Journal of …, 2023 - Springer
The number of people using mobile devices is increasing as mobile devices offer different
features and services. Many mobile users install various applications on their mobile …

Android botnet detection using machine learning models based on a comprehensive static analysis approach

J Alqatawna, AZ Ala'M, MA Hassonah, H Faris - Journal of Information …, 2021 - Elsevier
Today, Android stands out amongst the most well-known and far reaching smartphones'
operating systems. It has millions of applications that are distributed at either accredited or …

Human-guided auto-labeling for network traffic data: The GELM approach

M Kim, I Lee - Neural networks, 2022 - Elsevier
Data labeling is crucial in various areas, including network security, and a prerequisite for
applying statistical-based classification and supervised learning techniques. Therefore …

Android botnets: a proof-of-concept using hybrid analysis approach

A Karim, V Chang, A Firdaus - Journal of Organizational and End …, 2020 - igi-global.com
Mobile botnets are gaining popularity with the expressive demand of smartphone
technologies. Similarly, the majority of mobile botnets are built on a popular open source …

TriDroid: a triage and classification framework for fast detection of mobile threats in android markets

A Amira, A Derhab, EMB Karbab, O Nouali… - Journal of Ambient …, 2021 - Springer
The Android platform is highly targeted by malware developers, which aim to infect the
maximum number of mobile devices by uploading their malicious applications to different …

Features representation of botnet detection using machine learning approaches

PC Tikekar, SS Sherekar… - 2021 International …, 2021 - ieeexplore.ieee.org
Over the past ten years, Botnet has been an emerging threat that is increasing day by day &
has gained popularity amongst researchers. Botnet detection is a very challenging task, so …