Malware Analysis and Classification: A Survey

@inproceedings{Gandotra2014MalwareAA,
  title={Malware Analysis and Classification: A Survey},
  author={Ekta Gandotra and Divya Bansal and Sanjeev Sofat},
  year={2014}
}
One of the major and serious threats on the Internet today is malicious software, often referred to as a malware. The malwares being designed by attackers are polymorphic and metamorphic which have the ability to change their code as they propagate. Moreover, the diversity and volume of their variants severely undermine the effectiveness of traditional defenses which typically use signature based techniques and are unable to detect the previously unknown malicious executables. The variants of… CONTINUE READING

Figures, Tables, Results, and Topics from this paper.

Key Quantitative Results

  • The obtained results depicted that overall best performance is achieved by J48 decision tree with a recall of 95.9%, a false positive rate of 2.4%, a precision of 97.3%, and an accuracy of 96.8%.

Citations

Publications citing this paper.
SHOWING 1-10 OF 86 CITATIONS

Deep learning at the shallow end: Malware classification for non-domain experts

VIEW 6 EXCERPTS
CITES METHODS & BACKGROUND
HIGHLY INFLUENCED

Feature Selection and Improving Classification Performance for Malware Detection

  • 2016 IEEE International Conferences on Big Data and Cloud Computing (BDCloud), Social Computing and Networking (SocialCom), Sustainable Computing and Communications (SustainCom) (BDCloud-SocialCom-SustainCom)
  • 2016
VIEW 4 EXCERPTS
HIGHLY INFLUENCED

Malware classification using byte sequence information

VIEW 3 EXCERPTS
CITES BACKGROUND & METHODS
HIGHLY INFLUENCED

A Survey on Malware Detection Using Data Mining Techniques

VIEW 4 EXCERPTS
CITES METHODS & BACKGROUND
HIGHLY INFLUENCED

The Rise of Ransomware

VIEW 3 EXCERPTS
CITES BACKGROUND
HIGHLY INFLUENCED

A Semi-supervised Learning Methodology for Malware Categorization using Weighted Word Embeddings

Hugo Leonardo Duarte-Garcia, Carlos Domenick Morales-Medina, +4 authors Víctor Sánchez
  • 2019 IEEE European Symposium on Security and Privacy Workshops (EuroS&PW)
  • 2019
VIEW 1 EXCERPT
CITES BACKGROUND

CapJack: Capture In-Browser Crypto-jacking by Deep Capsule Network through Behavioral Analysis

  • IEEE INFOCOM 2019 - IEEE Conference on Computer Communications
  • 2019
VIEW 1 EXCERPT
CITES BACKGROUND

FILTER CITATIONS BY YEAR

2014
2019

CITATION STATISTICS

  • 5 Highly Influenced Citations

  • Averaged 19 Citations per year from 2017 through 2019

References

Publications referenced by this paper.
SHOWING 1-10 OF 35 REFERENCES

The WEKA data mining software: an update

  • SIGKDD Explorations
  • 2009
VIEW 3 EXCERPTS
HIGHLY INFLUENTIAL

Automated malware classification based on network behavior

  • 2013 International Conference on Computing, Networking and Communications (ICNC)
  • 2013
VIEW 1 EXCERPT

An approach for malware behavior identification and classification

  • 2011 3rd International Conference on Computer Research and Development
  • 2011
VIEW 1 EXCERPT