Using spatio-temporal information in API calls with machine learning algorithms for malware detection - Semantic Scholar

Abstract

Run-time monitoring of program execution behavior is widely used to discriminate between benign and malicious processes running on an end-host. Towards this end, most of the existing run-time intrusion or malware detection techniques utilize information available in Windows Application Programming Interface (API) call arguments or sequences. In comparison… (More)

DOI: 10.1145/1654988.1655003

Topics

10 Figures and Tables

Statistics

Citations
Citation Velocity

Citations per Year

55 Citations

Semantic Scholar estimates that this publication has 55 citations based on the available data.

See our FAQ for additional information.

Cited By

Sort by:

A survey of the applications of text mining in financial domain

B. Shravankumar, Vadlamani Ravi
Knowl.-Based Syst.
2016

Mal-Netminer: Malware Classification Approach based on Social Network Analysis of System Call Graph

Jae-wook Jang, Jiyoung Woo, Aziz Mohaisen, Jaesung Yun, Huy Kang Kim
ArXiv
2015

Malware detection via API calls, topic models and machine learning

G. Ganesh Sundarkumar, Vadlamani Ravi, Ifeoma Nwogu, Venu Govindaraju
2015 IEEE International Conference on Automation…
2015

Enhancing the detection of metamorphic malware using call graphs

Ammar Ahmed E. Elhadi, Mohd Aizaini Maarof, Bazara I. A. Barry, Hentabli Hamza
Computers & Security
2014

A miner for malware detection based on API function calls and their arguments

Z. Salehi, M. Ghiasi, A. Sami
The 16th CSI International Symposium on…
2012

Classification of Malware Based on String and Function Feature Selection

Rafiqul Islam, Ronghua Tian, Lynn Batten, Steve Versteeg
2010 Second Cybercrime and Trustworthy Computing…
2010

Survey on the Usage of Machine Learning Techniques for Malware Analysis

Daniele Ucci, Leonardo Aniello, Roberto Baldoni
ArXiv
2017

Malware Detection with Deep Neural Network Using Process Behavior

Shun Tobiyama, Yukiko Yamaguchi, Hajime Shimada, Tomonori Ikuse, Takeshi Yagi
2016 IEEE 40th Annual Computer Software and…
2016

Differentiating malware from cleanware using behavioural analysis

Ronghua Tian, Md. Rafiqul Islam, Lynn Margaret Batten, Steven Versteeg
2010 5th International Conference on Malicious…
2010

Lightweight Classification of IoT Malware based on Image Recognition

Jiawei Su, Danilo Vasconcellos Vargas, Sanjiva Prasad, Daniele Sgandurra, Yaokai Feng, Kouichi Sakurai
ArXiv
2018

‹
1
2
3
4
›

References

Unfortunately, ACM prohibits us from displaying non-influential references for this paper.

To see the full reference list, please visit http://dl.acm.org/citation.cfm?id=1655003.

Slides referencing similar topics

Machine Learning for Malware Detection
Nov 29, 2017
Annotating Spatio-Temporal Information in Documents
Jannik Strötgen • Mar 01, 2016
Malware Detection Based On Mining API Calls
Mansour Ahmadi + 13 • Dec 07, 2015
Show More