[HTML][HTML] A systematic literature review of methods and datasets for anomaly-based network intrusion detection

Z Yang, X Liu, T Li, D Wu, J Wang, Y Zhao, H Han - Computers & Security, 2022‏ - Elsevier
As network techniques rapidly evolve, attacks are becoming increasingly sophisticated and
threatening. Network intrusion detection has been widely accepted as an effective method to …

Application domains, evaluation data sets, and research challenges of IoT: A systematic review

R Lohiya, A Thakkar - IEEE Internet of Things Journal, 2020‏ - ieeexplore.ieee.org
We are at the brink of Internet of Things (IoT) era where smart devices and other wireless
devices are redesigning our environment to make it more correlative, flexible, and …

A survey on machine learning techniques for cyber security in the last decade

K Shaukat, S Luo, V Varadharajan, IA Hameed… - IEEE …, 2020‏ - ieeexplore.ieee.org
Pervasive growth and usage of the Internet and mobile applications have expanded
cyberspace. The cyberspace has become more vulnerable to automated and prolonged …

Toward develo** a systematic approach to generate benchmark android malware datasets and classification

AH Lashkari, AFA Kadir, L Taheri… - … conference on security …, 2018‏ - ieeexplore.ieee.org
Malware detection is one of the most important factors in the security of smartphones.
Academic researchers have extensively studied Android malware detection problems …

Extensible android malware detection and family classification using network-flows and API-calls

L Taheri, AFA Kadir, AH Lashkari - … Carnahan conference on …, 2019‏ - ieeexplore.ieee.org
Android OS-based mobile devices have attracted numerous end-users since they are
convenient to work with and offer a variety of features. As a result, Android has become one …

A taxonomy of network threats and the effect of current datasets on intrusion detection systems

H Hindy, D Brosset, E Bayne, AK Seeam… - IEEe …, 2020‏ - ieeexplore.ieee.org
As the world moves towards being increasingly dependent on computers and automation,
building secure applications, systems and networks are some of the main challenges faced …

[HTML][HTML] Kronodroid: Time-based hybrid-featured dataset for effective android malware detection and characterization

A Guerra-Manzanares, H Bahsi, S Nõmm - Computers & Security, 2021‏ - Elsevier
Android malware evolution has been neglected by the available data sets, thus providing a
static snapshot of a non-stationary phenomenon. The impact of the time variable has not had …

Malware detection on highly imbalanced data through sequence modeling

R Oak, M Du, D Yan, H Takawale, I Amit - … of the 12th ACM Workshop on …, 2019‏ - dl.acm.org
We explore the task of Android malware detection based on dynamic analysis of application
activity sequences using deep learning techniques. We show that analyzing a sequence of …

[HTML][HTML] Machine learning for android malware detection: mission accomplished? a comprehensive review of open challenges and future perspectives

A Guerra-Manzanares - Computers & Security, 2024‏ - Elsevier
The extensive research in machine learning based Android malware detection showcases
high-performance metrics through a wide range of proposed solutions. Consequently, this …

[HTML][HTML] Malicious webshell family dataset for webshell multi-classification research

Y Zhao, S Lv, W Long, Y Fan, J Yuan, H Jiang, F Zhou - Visual Informatics, 2024‏ - Elsevier
Malicious webshells currently present tremendous threats to cloud security. Most relevant
studies and open webshell datasets consider malicious webshell defense as a binary …