• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.337-340
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• 2022

SQL Injection attacks are one of the older attack techniques and are the dominant type of hacking attempts against web services. There have been many attempts to hack SQL injection attacks by exposing data or obtaining privileges. In this paper, we implement a log analysis system that can respond to SQL injection attacks in real time using the open source ELK Stack. did. By providing a visualization of SQL injection attack log data through the implemented system, it is expected that users will be able to easily grasp the degree of attack risk and quickly prepare for attacks.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.6
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• pp.2576-2590
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• 2020

The fundamental reason why most SQL injection detection methods are difficult to use in practice is the low reusability of the implementation code. This paper presents a reusable SQL injection detection method for Java Web applications based on AOP (Aspect-Oriented Programming) and dynamic taint analysis, which encapsulates the dynamic taint analysis processes into different aspects and establishes aspect library to realize the large-grained reuse of the code for detecting SQL injection attacks. A metamodel of aspect library is proposed, and a management tool for the aspect library is implemented. Experiments show that this method can effectively detect 7 known types of SQL injection attack such as tautologies, logically incorrect queries, union query, piggy-backed queries, stored procedures, inference query, alternate encodings and so on, and support the large-grained reuse of the code for detecting SQL injection attacks.

• Journal of Information Processing Systems
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• v.13 no.4
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• pp.689-702
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• 2017

The Structured Query Language (SQL) Injection continues to be one of greatest security risks in the world according to the Open Web Application Security Project's (OWASP) [1] Top 10 Security vulnerabilities 2013. The ease of exploitability and severe impact puts this attack at the top. As the countermeasures become more sophisticated, SOL Injection Attacks also continue to evolve, thus thwarting the attempt to eliminate this attack completely. The vulnerable data is a source of worry for government and financial institutions. In this paper, a detailed survey of different types of SQL Injection and proposed methods and theories are presented, along with various tools and their efficiency in intercepting and preventing SQL attacks.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.867-869
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• 2015

최근 폭발적으로 증가하는 데이터양과 데이터 특성들로 인해 관계형 데이터베이스는 빅데이터 처리에 어려움이 발생하기 시작했으며, 이러한 빅데이터의 신속한 처리를 위해 비정형 데이터 분산처리, 병렬 처리 등 특정한 영역에서 우수한 성능을 보이는 NoSQL 데이터베이스의 활용이 증가하고 있다. 기존 관계형 데이터베이스에서 악의적인 SQL Injection 공격이 시스템에 치명적인 피해를 주는 것과 마찬가지로, 다른 쿼리 언어를 사용하는 NoSQL 데이터베이스에서도 Injection 공격에 대한 취약점이 여전히 존재할 뿐만 아니라, NoSQL 데이터베이스가 비교적 최신 기술이기 때문에 개발자들은 Injection 공격에 대한 인식이 부족한 실정이다. 본 논문에서는 NoSQL 데이터베이스에 대한 대표적인 2가지 Injection 공격 방법을 소개하고, "NoSQL Injection Defender(NID)"라 명명한 Injection 공격 방어 시스템의 설계 방안을 제시하고자 한다.

• The KIPS Transactions:PartA
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• v.15A no.3
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• pp.181-188
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• 2008

Nowadays, most web sites are developed using dynamic web pages where web pages are generated and transmitted by web application programs. Therefore, the ratio of attacks injecting malevolent strings to vulnerable web applications is increasing. In this paper, we present a static program analyzer which analyzes whether a web application program has vulnerabilities to the SQL injection attack and the cross site scripting(XSS) attack. To analyze programs using abstract interpretation framework, we designed an abstract domain which models potential string set along with excluded strings and developed an abstract interpreter for the PHP language. Also, based on them, we implemented a static analyzer. According to our experiments, our analyzer has competitive analysis speed and accuracy compared with related research results.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.303-306
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• 2010

Personal information being leaked, and personal assets that through a malicious web site for hackers to exploit. Other confidential information via the web site of the country, and your personal information by illegally accessing the data has been obtained who Hacker forces are operating in some countries. Due to the problem of web site management has many vulnerabilities that web sites, as well as programs. In this paper, in the trend world, as well as domestic XSS, SQL Injection, Web Shell analysis of the vulnerability to attacks and XSS, SQL Injection, Web Shell is a direct attack to attack. Security measures are presented what after the attack demonstrated the hack to data collection, analysis. In this study, web site management, web site security and safety can be improved and research will contribute.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.18 no.5
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• pp.135-148
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• 2008

The expansion of the internet has made web applications become a part of everyday lift. As a result the number of incidents which exploit web application vulnerabilities are increasing. A large percentage of these incidents are SQL Injection attacks which are a serious security threat to databases with potentially sensitive information. Therefore, much research has been done to detect and prevent these attacks and it resulted in a decline of SQL Injection attacks. However, there are still methods to bypass them and these methods are too complex to implement in real web applications. This paper proposes a simple and effective SQL Query attribute value removal method which uses Static and Dynamic Analysis and evaluates the efficiency through various experiments.

• Journal of the Korea Convergence Society
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• v.10 no.10
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• pp.21-26
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• 2019

At present, it is indispensable to utilize data as an information society. Therefore, the database is used to manage large amounts of data. In real life, most of the data in a database is the personal information of a group of members. Because personal information is sensitive data, the role of the database administrator who manages personal information is important. However, there is a growing number of attacks on databases to use this personal information in a malicious way. SQL Injection is one of the most known and old hacking techniques. SQL Injection attacks are known as an easy technique, but countermeasures are easy, but a lot of efforts are made to avoid SQL attacks on web pages that require a lot of logins, but some sites are still vulnerable to SQL attacks. Therefore, this study suggests effective defense measures through analysis of SQL hacking technology cases and contributes to preventing web hacking and providing a secure information communication environment.

• Proceedings of the Korea Information Processing Society Conference
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• 2014.04a
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• pp.441-444
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• 2014

인터넷의 보급에 따른 신속정확하고 편리한 정보처리의 장점에도 불구하고 최근 들어 급증하고 있는 보안 관련 사고들로 인하여 개인정보 및 기업정보의 관리에 대한 대책 마련이 시급한 가운데 있다. 그 중에서도 SQL 삽입 공격에 의한 악의적인 관리자 권한 획득 및 비정상적인 로그인 등으로 인하여 많은 피해가 발생하고 있다. 현재 SQL Injection에 관련된 대부분의 연구는 공격을 탐지하는 방법에 초점이 맞추어져 있다. 본 논문에서는 프로그램 코드를 분석하여 따옴표가 포함된 취약한 인라인 SQL 쿼리 구문을 찾아서 매개변수화된 쿼리로 변경하는 기능을 제공함으로써 근본적인 해결책을 찾고자 하였으며 Java, C#.net 등 다양한 언어를 지원하여 개발 업무에서의 활용성을 높이고자 하였다.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.3
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• pp.455-464
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• 2020

With a variety of data types and high utilization of data, non-relational databases are a popular data storage because it supports better availability and scalability. The increasing use of this technology also brings the risk of NoSQL injection attacks. Existing works mostly discuss the rule-based detection of NoSQL injection attacks that it is hard to deal with NoSQL queries beyond the coverage of the rules. In this paper, we propose a model for detecting NoSQL injection attacks. Our model is based on deep learning algorithms that select features from NoSQL queries using CNN, and classify NoSQL queries using RNN. Also, we experiment the proposed model to compare with existing models, and find that our model outperforms traditional models in terms of detection rate.