Yap L. Dion
Negation of ransomware via gamification and enforcement of standards
Dion, Yap L.; Joshua, Abigail A.; Brohi, Sarfraz N.
Authors
Abigail A. Joshua
Sarfraz N. Brohi
Abstract
With the continued advancement of the internet and relevant programs, the number of exploitable loopholes in security systems increases. One such exploit that is plaguing the software scene is ransomware, a type of malware that weaves its way through these security loopholes and denies access to intellectual property and documents via encryption. The culprits will then demand a ransom as a price for data decryption. Many businesses face the issue of not having stringent security measures that are sufficient enough to negate the threat of ransomware. This jeopardizes the availability of sensitive data as corporations and individuals are at threat of losing data crucial to business or personal operations. Although certain countermeasures to deal with ransomware exist, the fact that a plethora of new ransomware cases keeps appearing every year points to the problem that they aren’t effective enough. This paper aims to conceptualize practical solutions that can be used as foundations to build on in hope that more effective and proactive countermeasures to ransomware can be developed in the future.
Presentation Conference Type | Conference Paper (Published) |
---|---|
Conference Name | 2017 International Conference on Computer Science and Artificial Intelligence |
Start Date | Dec 5, 2017 |
End Date | Dec 7, 2017 |
Acceptance Date | Nov 13, 2017 |
Online Publication Date | Dec 5, 2017 |
Publication Date | Dec 5, 2017 |
Deposit Date | Sep 9, 2022 |
Publisher | Association for Computing Machinery (ACM) |
Pages | 203-208 |
Book Title | CSAI 2017: Proceedings of the 2017 International Conference on Computer Science and Artificial Intelligence |
ISBN | 9781450353922 |
DOI | https://doi.org/10.1145/3168390.3168399 |
Keywords | Ransomware, Law Enforcement Gamification, Standardization |
Public URL | https://uwe-repository.worktribe.com/output/9942609 |
Publisher URL | https://dl.acm.org/doi/10.1145/3168390.3168399 |
Related Public URLs | http://www.csai.org/ https://dl.acm.org/doi/proceedings/10.1145/3168390 |
You might also like
Accuracy comparison of machine learning algorithms for predictive analytics in higher education
(2019)
Presentation / Conference Contribution
UAV’s applications, architecture, security issues and attack scenarios: A survey
(2020)
Book Chapter
A review and survey on smartphones: The closest enemy to privacy
(2019)
Presentation / Conference Contribution
Downloadable Citations
About UWE Bristol Research Repository
Administrator e-mail: repository@uwe.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2024
Advanced Search