A detailed investigation and analysis of using machine learning techniques for intrusion detection
P Mishra, V Varadharajan… - … surveys & tutorials, 2018 - ieeexplore.ieee.org
Intrusion detection is one of the important security problems in todays cyber world. A
significant number of techniques have been developed which are based on machine …
significant number of techniques have been developed which are based on machine …
A review on the use of deep learning in android malware detection
A Naway, Y Li - arXiv preprint arXiv:1812.10360, 2018 - arxiv.org
Android is the predominant mobile operating system for the past few years. The prevalence
of devices that can be powered by Android magnetized not merely application developers …
of devices that can be powered by Android magnetized not merely application developers …
Robust malware detection for internet of (battlefield) things devices using deep eigenspace learning
A Azmoodeh, A Dehghantanha… - IEEE transactions on …, 2018 - ieeexplore.ieee.org
Internet of Things (IoT) in military settings generally consists of a diverse range of Internet-
connected devices and nodes (eg, medical devices and wearable combat uniforms). These …
connected devices and nodes (eg, medical devices and wearable combat uniforms). These …
Detecting crypto-ransomware in IoT networks based on energy consumption footprint
Abstract An Internet of Things (IoT) architecture generally consists of a wide range of Internet-
connected devices or things such as Android devices, and devices that have more …
connected devices or things such as Android devices, and devices that have more …
A survey on dynamic mobile malware detection
P Yan, Z Yan - Software Quality Journal, 2018 - Springer
The outstanding advances of mobile devices stimulate their wide usage. Since mobile
devices are coupled with third-party applications, lots of security and privacy problems are …
devices are coupled with third-party applications, lots of security and privacy problems are …
CANDYMAN: Classifying Android malware families by modelling dynamic traces with Markov chains
A Martín, V Rodríguez-Fernández… - Engineering Applications of …, 2018 - Elsevier
Malware writers are usually focused on those platforms which are most used among
common users, with the aim of attacking as many devices as possible. Due to this reason …
common users, with the aim of attacking as many devices as possible. Due to this reason …
Talos: no more ransomware victims with formal methods
Ransomware is a very effective form of malware that is recently spreading out on an
impressive number of workstations and smartphones. This malware blocks the access to the …
impressive number of workstations and smartphones. This malware blocks the access to the …
Intelligent OS X malware threat detection with code inspection
HH Pajouh, A Dehghantanha, R Khayami… - Journal of Computer …, 2018 - Springer
With the increasing market share of Mac OS X operating system, there is a corresponding
increase in the number of malicious programs (malware) designed to exploit vulnerabilities …
increase in the number of malicious programs (malware) designed to exploit vulnerabilities …
Android malware permission-based multi-class classification using extremely randomized trees
F Alswaina, K Elleithy - IEEE Access, 2018 - ieeexplore.ieee.org
Due to recent developments in hardware and software technologies for mobile phones,
people depend on their smartphones more than ever before. Today, people conduct a …
people depend on their smartphones more than ever before. Today, people conduct a …
A family of droids-android malware detection via behavioral modeling: Static vs dynamic analysis
Following the increasing popularity of the mobile ecosystem, cybercriminals have
increasingly targeted mobile ecosystems, designing and distributing malicious apps that …
increasingly targeted mobile ecosystems, designing and distributing malicious apps that …