Blockchain-Based Data Breach Detection: Approaches, Challenges, and Future Directions

Author:

Ansar Kainat1,Ahmed Mansoor12ORCID,Helfert Markus2,Kim Jungsuk34ORCID

Affiliation:

1. Department of Computer Science, COMSATS University, Islamabad 44000, Pakistan

2. ADAPT Centre, Innovation Value Institute, Maynooth University, W23 F2H6 Maynooth, Ireland

3. Department of Biomedical Engineering, College of IT Convergence, Gachon University, Sujeong-gu, Seongnam-si 13120, Republic of Korea

4. Research and Development Laboratory, Cellico Company, Seongnam-si 13449, Republic of Korea

Abstract

In cybersecurity, personal data breaches have become one of the significant issues. This fact indicates that data breaches require unique detection systems, techniques, and solutions, which necessitate the potential to facilitate precise and quick data breach detection. Various research works on data breach detection and related areas in dealing with this problem have been proposed. Several survey studies have been conducted to comprehend insider data breaches better. However, these works did not examine techniques related to blockchain and innovative smart contract technologies to detect data breaches. In this survey, we examine blockchain-based data breach detection mechanisms developed so far to deal with data breach detection. We compare blockchain-based data breach detection techniques based on type, platform, smart contracts, consensus algorithm language/tool, and evaluation measures. We also present a taxonomy of contemporary data breach types. We conclude our study by outlining existing methodologies’ issues, offering ideas for overcoming those challenges, and pointing the way forward.

Funder

National Research Foundation of Korea

Energy

Korea Institute of Industrial Technology Evaluation and Management

Publisher

MDPI AG

Subject

General Mathematics,Engineering (miscellaneous),Computer Science (miscellaneous)

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3