Results 151 to 160 of about 10,938 (187)

Visualizing a Malware Distribution Network

2016 IEEE Symposium on Visualization for Cyber Security (VizSec), 2016
In this paper, we present a case study of visual analytics of a Malware Distribution Network (MDN), a connected set of maliciously compromised domains used to disseminate malicious software to victimize computers and users. We formally define the graph of an MDN to visualize top-level-domain (TLD) data collected from Google Safe Browsing reports in a ...
Sebastian Peryt, Jose Andre Morales, William Casey, Aaron Volkmann, Bud Mishra, Yang Cai   +5 more
openaire   +1 more source

Byte Visualization Method for Malware Classification

Proceedings of the 2020 5th International Conference on Machine Learning Technologies, 2020
The exponential increase in the number of malware stems from the fact that attackers often create malware variants with automated tools. And automated tools generally tend to reuse similar function modules. It is essential, therefore, that security analysts distinguish malware families by recognizing similar modules.
Zhuojun Ren, Guang Chen, Wenke Lu
openaire   +1 more source

Experiments with Malware Visualization

2013
This paper proposes DotPlot visualizations [1,8] for comparing and clustering malware. We describe how to process and customize the malware memory images to get robust and scalable visualizations. We demonstrate the effectiveness of the visualizations for analysing, comparing and clustering malware.
Yongzheng Wu, Roland H. C. Yap
openaire   +1 more source

Visualization techniques for efficient malware detection

2013 IEEE International Conference on Intelligence and Security Informatics, 2013
Traditional tools for reverse engineering of binary and PE files are limited to heavy text base output, thus requiring skilled analysts to use them. In this paper, we present techniques that will visualize PE files, which will help analysts with basic skills to quickly understand their underlying structure.
John Donahue, Anand Paturi, Srinivas Mukkamala   +2 more
openaire   +1 more source

Visualization Approach for Malware Classification with ResNeXt

2020 IEEE Congress on Evolutionary Computation (CEC), 2020
The Internet has resulted in cyber-threats and cyber-crimes, which can occur anywhere at any time. Among various cyber threats, modern malware with applied metamorphosis and polymorphic technology is a concern as it can proliferate to advanced variants from its original shape.
Jin Ho Go, Tony Jan, Manoranjan Mohanty, Om Prakash Patel, Deepak Puthal, Mukesh Prasad   +5 more
openaire   +1 more source

Analysis of Visualization Techniques for Malware Detection

2020 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (EIConRus), 2020
Due to the steady growth of various sophisticated types of malware, different malware analysis systems are becoming more and more demanded. While there are various automatic approaches available to identify and detect malware, the malware analysis is still time-consuming process.
Anastasia Kartel, Evgenia Novikova, Aleksandr Volosiuk   +2 more
openaire   +1 more source

Mobile malware visual analytics and similarities of Attack Toolkits (Malware gene analysis)

2013 International Conference on Collaboration Technologies and Systems (CTS), 2013
We use Normalized Compression Distance (NCD) (owing to its capabilities to perform similarity measure of unstructured data) to enumerate code similarity between malicious Android apps and visualize their clusters. Our classification methods and visual analytics can help the antivirus community to ensure that a variant of a known malware can still be ...
Anand Paturi, Manoj Cherukuri, John Donahue, Srinivas Mukkamala   +3 more
openaire   +1 more source

Navigating and visualizing the malware intelligence space

IEEE Network, 2012
There is now a shift from traditional Cyber Security to Cyber Intelligence. We are only beginning to leverage the intelligence that can be extracted from the thousands of malware samples that are currently being gathered on a daily basis. By automatically creating analysis reports for each of these malware samples, it is possible to improve our ...
F. Massicotte, M. Couture, H. Normandin, M. Letourneau   +3 more
openaire   +1 more source

Neural Visualization of Android Malware Families

2016
Due to the ever increasing amount and severity of attacks aimed at compromising smartphones in general, and Android devices in particular, much effort have been devoted in recent years to deal with such incidents. However, scant attention has been devoted to study the interplay between visualization techniques and Android malware detection.
Alejandro González, Álvaro Herrero, Emilio Corchado   +2 more
openaire   +1 more source

Visual malware detection using local malicious pattern

Journal of Computer Virology and Hacking Techniques, 2018
In recent years, malware authors have had significant developments in offering new generations of malware and have tried to use different methods to make malware detection hard, so detecting malware has become one of the most important challenges for the security of computer systems.
Hashem Hashemi, Ali Hamzeh
openaire   +1 more source