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[HTML][HTML] A systematic literature review of methods and datasets for anomaly-based network intrusion detection
As network techniques rapidly evolve, attacks are becoming increasingly sophisticated and
threatening. Network intrusion detection has been widely accepted as an effective method to …
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
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 …
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
Pervasive growth and usage of the Internet and mobile applications have expanded
cyberspace. The cyberspace has become more vulnerable to automated and prolonged …
cyberspace. The cyberspace has become more vulnerable to automated and prolonged …
Toward develo** a systematic approach to generate benchmark android malware datasets and classification
Malware detection is one of the most important factors in the security of smartphones.
Academic researchers have extensively studied Android malware detection problems …
Academic researchers have extensively studied Android malware detection problems …
Extensible android malware detection and family classification using network-flows and API-calls
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 …
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
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 …
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
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 …
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
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 …
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
The extensive research in machine learning based Android malware detection showcases
high-performance metrics through a wide range of proposed solutions. Consequently, this …
high-performance metrics through a wide range of proposed solutions. Consequently, this …
[HTML][HTML] Malicious webshell family dataset for webshell multi-classification research
Malicious webshells currently present tremendous threats to cloud security. Most relevant
studies and open webshell datasets consider malicious webshell defense as a binary …
studies and open webshell datasets consider malicious webshell defense as a binary …