Malicious accounts: Dark of the social networks
Over the last few years, online social networks (OSNs), such as Facebook, Twitter and
Tuenti, have experienced exponential growth in both profile registrations and social …
Tuenti, have experienced exponential growth in both profile registrations and social …
Androdialysis: Analysis of android intent effectiveness in malware detection
The wide popularity of Android systems has been accompanied by increase in the number
of malware targeting these systems. This is largely due to the open nature of the Android …
of malware targeting these systems. This is largely due to the open nature of the Android …
DeepFlow: Deep learning-based malware detection by mining Android application for abnormal usage of sensitive data
D Zhu, H Jin, Y Yang, D Wu… - 2017 IEEE symposium on …, 2017 - ieeexplore.ieee.org
The open nature of Android allows application developers to take full advantage of the
system. While the flexibility is brought to developers and users, it may raise significant issues …
system. While the flexibility is brought to developers and users, it may raise significant issues …
Machine learning for anomaly detection and categorization in multi-cloud environments
Cloud computing has been widely adopted by application service providers (ASPs) and
enterprises to reduce both capital expenditures (CAPEX) and operational expenditures …
enterprises to reduce both capital expenditures (CAPEX) and operational expenditures …
CloudRPS: a cloud analysis based enhanced ransomware prevention system
JK Lee, SY Moon, JH Park - The Journal of Supercomputing, 2017 - Springer
Recently, indiscriminate ransomware attacks targeting a wide range of victims for monetary
gains have become a worldwide social issue. In the early years, ransomware has used e …
gains have become a worldwide social issue. In the early years, ransomware has used e …
Reinforcement learning based mobile offloading for cloud-based malware detection
X Wan, G Sheng, Y Li, L Xiao… - GLOBECOM 2017-2017 …, 2017 - ieeexplore.ieee.org
Cloud-based malware detection improves the detection performance for mobile devices that
offload their malware detection tasks to security servers with much larger malware database …
offload their malware detection tasks to security servers with much larger malware database …
Designing an online and reliable statistical anomaly detection framework for dealing with large high-speed network traffic
N Moustafa - 2017 - unsworks.unsw.edu.au
Abstract Despite a Network Anomaly Detection System (NADS) being capable of detecting
existing and zero-day attacks, it is still not universally implemented in industry and real …
existing and zero-day attacks, it is still not universally implemented in industry and real …
Network-based detection of Android malicious apps
S Garg, SK Peddoju, AK Sarje - International Journal of Information …, 2017 - Springer
Users leverage mobile devices for their daily Internet needs by running various mobile
applications (apps) such as social networking, e-mailing, news-reading, and video/audio …
applications (apps) such as social networking, e-mailing, news-reading, and video/audio …
Droidclassifier: Efficient adaptive mining of application-layer header for classifying android malware
A recent report has shown that there are more than 5,000 malicious applications created for
Android devices each day. This creates a need for researchers to develop effective and …
Android devices each day. This creates a need for researchers to develop effective and …
A novel chaotic chicken swarm optimization algorithm for feature selection
K Ahmed, AE Hassanien… - 2017 Third International …, 2017 - ieeexplore.ieee.org
Feature selection is an important task in data mining, which aims to reduce the
dimensionality of the data sets while at least maintaining the classification performance …
dimensionality of the data sets while at least maintaining the classification performance …