Welcome to the InfoSci Platform
Reference Hub5
Automated Detection of SQL Injection Attack on Blockchain-Based Database

Automated Detection of SQL Injection Attack on Blockchain-Based Database

Keshav Sinha, Amit Kumar Keshari
Copyright: © 2021 |Pages: 21
ISBN13: 9781799864493|ISBN10: 1799864499|ISBN13 Softcover: 9781799864509|EISBN13: 9781799864516
DOI: 10.4018/978-1-7998-6449-3.ch017
Cite Chapter Cite Chapter

MLA

Sinha, Keshav, and Amit Kumar Keshari. "Automated Detection of SQL Injection Attack on Blockchain-Based Database." Handbook of Research on Library Response to the COVID-19 Pandemic, edited by Barbara Holland, IGI Global, 2021, pp. 321-341. https://doi.org/10.4018/978-1-7998-6449-3.ch017

APA

Sinha, K. & Keshari, A. K. (2021). Automated Detection of SQL Injection Attack on Blockchain-Based Database. In B. Holland (Ed.), Handbook of Research on Library Response to the COVID-19 Pandemic (pp. 321-341). IGI Global. https://doi.org/10.4018/978-1-7998-6449-3.ch017

Chicago

Sinha, Keshav, and Amit Kumar Keshari. "Automated Detection of SQL Injection Attack on Blockchain-Based Database." In Handbook of Research on Library Response to the COVID-19 Pandemic, edited by Barbara Holland, 321-341. Hershey, PA: IGI Global, 2021. https://doi.org/10.4018/978-1-7998-6449-3.ch017

Export Reference

Mendeley
Favorite

Abstract

In the era of computing, where the data are stored in a cloud or distributed environment, the privacy of data is one of the challenging tasks. The attacks like denial of service attacks (DoS), insider attack compromised the security of the system. In this chapter, the authors discussed a blockchain-based database, where data are encrypted and stored. The Web API is used as an interface for the storage and sharing of data in the blockchain system. There are several types of attacks that are performed by the adversary on the database to destroy the vulnerability of the system. Here, the authors are mainly focused on the SQL injection attack which is performed by the adversary on Web API. To cope with this problem, they present the case study based on the Snort and Moloch for automated detection of SQL attack, network analysis, and testing of the system.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.