A Two-Phase Pattern Matching-parse Tree Validation Approach for Efficient SQL Injection Attacks Detection

  title={A Two-Phase Pattern Matching-parse Tree Validation Approach for Efficient SQL Injection Attacks Detection},
  author={Randa Osman Morsi and Mona F. Ahmed},
  journal={Journal of Artificial Intelligence},
Background and Objective: Data is one of the most valuable assets as it is the core for any organization website. SQL Injection Attack (SQLIA) is the way by which hackers gain access to data. An approach was proposed in this paper to efficiently detect SQLIA. Methodology: One of the most powerful algorithms, Parsing Tree validation (PT), depends only on accurate detection but takes much time so combining it with a fast dynamic algorithm with the purpose of learning and storing the malicious… Expand
2 Citations
SQLIA Detection and Prevention Techniques
Structure Query Language Injection (SQLI) is one of the top most threat to web-based applications (Like e-commerce, banking, shopping, trading, blogs, etc.) which are connected to the database. TheExpand
Intrusion Detection Systems for Mitigating SQL Injection Attacks: Review and State-of-Practice
The authors compare these tools using the CSIC dataset in order to examine the state-of-practice in database protection from SQL Injection attacks, identifying the main characteristics and implementation details needed for IDSs to successfully detect such attacks. Expand


An efficient technique for preventing SQL injection attack using pattern matching algorithm
A detection and prevention technique for preventing SQL Injection Attack (SQLIA) using Aho-Corasick pattern matching algorithm and an overview of the architecture is proposed. Expand
SQLiGoT: Detecting SQL injection attacks using graph of tokens and SVM
A novel approach to detect injection attacks by modeling SQL queries as graph of tokens and using the centrality measure of nodes to train a Support Vector Machine (SVM) is presented. Expand
Data-mining based SQL injection attack detection using internal query trees
This paper proposes a framework to detect SQLIAs at database level by using SVM classification and various kernel functions, and proposes a novel method to convert the query tree into an n-dimensional feature vector by using a multi-dimensional sequence as an intermediate representation. Expand
Detecting SQL injection attacks using query result size
A novel scheme that automatically transforms web applications, rendering them safe against SQL injection attacks, which dynamically analyzes the developer-intended query result size for any input, and detects attacks by comparing this against the result of the actual query. Expand
Detecting and Defeating SQL Injection Attacks
This paper proposes a SQL injection vulnerability scanner that is light-weight, fast and has a low false positive rate, and proposes a security mechanism to counter SQL Injection Attacks. Expand
SQL Injection Detection via Program Tracing and Machine Learning
This work proposes a novel hybrid approach for learning SQL statements with program tracing techniques in order to detect malicious behavior between the database and application. Expand
Using parse tree validation to prevent SQL injection attacks
A technique to prevent this kind of manipulation and hence eliminate SQL injection vulnerabilities is described, based on comparing, at run time, the parse tree of the SQL statement before inclusion of user input with that resulting after inclusion of input. Expand
Detection and Prevention of SQL Injection Attack: A Survey
SQL (structure query language) injection is one of threats to the applications, which are Web-based application, Mobile application and even desktop application, which are connected to the database.Expand
Prevention of SQL Injection Attack on Web Applications
The techniques for detection and prevention of SQL injection attack are presented and some predefined method of detection and modern techniques are discussed. Expand