A survey on deep learning for cybersecurity: Progress, challenges, and opportunities
As the number of Internet-connected systems rises, cyber analysts find it increasingly difficult
to effectively monitor the produced volume of data, its velocity and diversity. Signature-based …
to effectively monitor the produced volume of data, its velocity and diversity. Signature-based …
[HTML][HTML] An in-depth review of machine learning based Android malware detection
It is estimated that around 70% of mobile phone users have an Android device. Due to this
popularity, the Android operating system attracts a lot of malware attacks. The sensitive …
popularity, the Android operating system attracts a lot of malware attacks. The sensitive …
Botnet attack detection in Internet of Things devices over cloud environment via machine learning
With the arrival of the Internet of Things (IoT) many devices such as sensors, nowadays can
communicate with each other and share data easily. However, the IoT paradigm is prone to …
communicate with each other and share data easily. However, the IoT paradigm is prone to …
Deep learning for android malware defenses: a systematic literature review
Malicious applications (particularly those targeting the Android platform) pose a serious
threat to developers and end-users. Numerous research efforts have been devoted to …
threat to developers and end-users. Numerous research efforts have been devoted to …
Safety, security and privacy in machine learning based internet of things
Recent developments in communication and information technologies, especially in the
internet of things (IoT), have greatly changed and improved the human lifestyle. Due to the …
internet of things (IoT), have greatly changed and improved the human lifestyle. Due to the …
Robust deep learning early alarm prediction model based on the behavioural smell for android malware
E Amer, S El-Sappagh - Computers & Security, 2022 - Elsevier
Due to the widespread expansion of the Android malware industry, malicious Android
processes mining became a necessity to understand their behavior. Nevertheless, due to …
processes mining became a necessity to understand their behavior. Nevertheless, due to …
A survey on mobile malware detection methods using machine learning
The prevalence of mobile devices (smartphones) along with the availability of high-speed
internet access world-wide resulted in a wide variety of mobile applications that carry a large …
internet access world-wide resulted in a wide variety of mobile applications that carry a large …
An enhanced deep learning neural network for the detection and identification of android malware
Android-based mobile devices have attracted a large number of users because they are
easy to use and possess a wide range of capabilities. Because of its popularity, Android has …
easy to use and possess a wide range of capabilities. Because of its popularity, Android has …
Self-supervised vision transformers for malware detection
Malware detection plays a crucial role in cyber-security with the increase in malware growth
and advancements in cyber-attacks. Previously unseen malware which is not determined by …
and advancements in cyber-attacks. Previously unseen malware which is not determined by …
Intrusion detection based on machine learning in the internet of things, attacks and counter measures
E Rehman, M Haseeb-ud-Din, AJ Malik… - The Journal of …, 2022 - Springer
Globally, data security and privacy over the Internet of Things (IoT) are necessary due to its
emergence in daily life. As the IoT will soon invade each part of our lives, attention to IoT …
emergence in daily life. As the IoT will soon invade each part of our lives, attention to IoT …