A Comparative Assessment of Obfuscated Ransomware Detection Methods

Clicks: 181
ID: 171567
2019
Free PDF
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Emerging

Ranked #15 of 24 articles by views in informatică economică

Most read Least read

Bar heights use a square-root scale.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Sign in to mint
Abstract
Ransomware represents a class of malicious applications that encrypts the files of infected system and demands from victims a payment in cryptocurrency in order to receive the decryption key. The mainstream adoption of cryptocurrencies increased the number of ransomware attack. The outbreaks had risen in complexity and received mass-media attention in 2017 when two destructive campaigns crippled companies and institutions around the world. These outbreaks continue at an accelerated pace even though efforts are made to improve the detection and mitigation of ransomware. The purpose of this research is to assess the efficiency of current malware analysis methods and technologies in the detection of ransomware. The experiments presented here were performed using antivirus engines and dynamic malware analysis against live obfuscated ransomware samples.
Reference Key
sechel2019ainformatic Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors SECHEL, Sergiu;
Journal informatică economică
Year 2019
DOI
DOI not found
URL
http://revistaie.ase.ro/content/90/05%20-%20sechel.pdf
Keywords
Medicine (General) Information technology Science economics as a science finance economic theory. demography computer engineering. computer hardware electronic computers. computer science bibliography. library science. information resources risk in industry. risk management international relations

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

Comments

No comments yet. Be the first to comment on this article.