数据泄漏检测的进展:SQL 注入检测技术与挑战综述

Komalseerut Kaur
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引用次数: 0

摘要

在当前重要流程几乎完全依赖网络应用程序的情况下,SQL 注入成为全球许多组织信息窃取的重要问题。本文旨在从 SQL 注入的技术角度回顾数据泄漏的检测方法,包括将相关风险降至最低的策略和技术。首先,本文概述了 SQL 注入及其相关后果,然后进一步介绍了各种重要的检测方法,如签名和基于异常的流程。值得注意的是,本文还探讨了机器学习和人工智能在提高识别正确性方面的作用。在说明 SQL 注入攻击对不同组织的影响时,我们还将模拟总结经验教训的过程,以预防和打击此类攻击。本文阐述了该领域的障碍和前景,这将为研究人员和从业人员提供指导,帮助他们提高数据泄漏检测技术的质量,并将其应用于众多经济领域。本文将对当前的黑客攻击进行梳理,旨在找出攻击者通过 SQL 注入手段进入系统的漏洞。关键词-- 数据泄露检测、SQL 注入、网络应用、安全、检测技术、机器学习、基于异常的检测、基于签名的检测、预防、缓解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Advances in Data Leak Detection: A Review of SQL Injection Detection Techniques and Challenges
In the current landscape where important processes are almost entirely dependent on web apps, SQL injection becomes an important issue for information-stealing throughout many organizations worldwide. This paper aims to review that data leak can be detected from a technical perspective of SQL injection including strategies and techniques to minimize related risk. As a first step, as an overview SQL injection and its associates with them consequences, the paper then go further to various important detection methods such as signatures and anomalies-based processes. It is noteworthy that the paper also explores the function of machine learning and artificial intelligence in improving recognition correctness. As we illustrate the effects of SQL injection attacks on various organizations, we will as well simulate the process of drawing the lessons learnt to prevent and combat the attacks. Obstacles and perspectives in the sphere are stated, which will guide a researcher and a practitioner on his way to raise the quality of data leak detecting technologies used across numerous branches of the economy. This article will weaving together the current blackout and will aims at identifying the gaps through which the attackers are able to get access to the system by the means of SQL injection. Keywords— Data leak detection, SQL injection, Web applications, Security, Detection techniques, Machine learning, Anomaly-based detection, Signature-based detection, Prevention, Mitigation.
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