Applying machine learning techniques for detection of malicious code in network traffic
Abstract The Early Detection, Alert and Response (eDare) system is aimed at purifying Web
traffic propagating via the premises of Network Service Providers (NSP) from malicious …
traffic propagating via the premises of Network Service Providers (NSP) from malicious …
Host based intrusion detection using machine learning
R Moskovitch, S Pluderman, I Gus… - 2007 IEEE …, 2007 - ieeexplore.ieee.org
Detecting unknown malicious code (malcode) is a challenging task. Current common
solutions, such as anti-virus tools, rely heavily on prior explicit knowledge of specific …
solutions, such as anti-virus tools, rely heavily on prior explicit knowledge of specific …
Virus detection using data mining techinques
JH Wang, PS Deng, YS Fan, LJ Jaw… - IEEE 37th Annual 2003 …, 2003 - ieeexplore.ieee.org
Malicious executables are computer programs, which may cause damages or
inconveniences for computer users when they are executed. Virus is one of the major kinds …
inconveniences for computer users when they are executed. Virus is one of the major kinds …
Malicious code detection using active learning
The recent growth in network usage has motivated the creation of new malicious code for
various purposes, including economic and other malicious purposes. Currently, dozens of …
various purposes, including economic and other malicious purposes. Currently, dozens of …
Unknown malcode detection using opcode representation
R Moskovitch, C Feher, N Tzachar, E Berger… - Intelligence and Security …, 2008 - Springer
The recent growth in network usage has motivated the creation of new malicious code for
various purposes, including economic ones. Today's signature-based anti-viruses are very …
various purposes, including economic ones. Today's signature-based anti-viruses are very …
Classification of malicious web code by machine learning
R Komiya, I Paik, M Hisada - 2011 3rd International …, 2011 - ieeexplore.ieee.org
Web applications make life more convenient through on the activities. Many web
applications have several kind of user input (eg personal information, a user's comment of …
applications have several kind of user input (eg personal information, a user's comment of …
Detection of malicious code by applying machine learning classifiers on static features: A state-of-the-art survey
This research synthesizes a taxonomy for classifying detection methods of new malicious
code by Machine Learning (ML) methods based on static features extracted from …
code by Machine Learning (ML) methods based on static features extracted from …
Malicious codes detection based on ensemble learning
B Zhang, J Yin, J Hao, D Zhang, S Wang - … , Hong Kong, China, July 11-13 …, 2007 - Springer
As malicious codes become more complex and sophisticated, the scanning detection
method is no longer able to detect various forms of viruses effectively. In this paper, we …
method is no longer able to detect various forms of viruses effectively. In this paper, we …
A scalable multi-level feature extraction technique to detect malicious executables
We present a scalable and multi-level feature extraction technique to detect malicious
executables. We propose a novel combination of three different kinds of features at different …
executables. We propose a novel combination of three different kinds of features at different …
Building a machine learning classifier for malware detection
Z Markel, M Bilzor - 2014 second workshop on anti-malware …, 2014 - ieeexplore.ieee.org
Current signature-based antivirus software is ineffective against many modern malicious
software threats. Machine learning methods can be used to create more effective …
software threats. Machine learning methods can be used to create more effective …