Meharaj Begum A; Michael Arock
Abstract
Whatever malware protection is upcoming, still the data are prone to cyber-attacks. The most threatening Structured Query Language Injection Attack (SQLIA) happens at the database layer of web applications leading to unlimited and unauthorized access to confidential information through malicious code ...
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Whatever malware protection is upcoming, still the data are prone to cyber-attacks. The most threatening Structured Query Language Injection Attack (SQLIA) happens at the database layer of web applications leading to unlimited and unauthorized access to confidential information through malicious code injection. Since feature extraction accuracy significantly influences detection results, extracting the features of a query that predominantly contributes to SQL Injection (SQLI) is the most challenging task for the researchers. So, the proposed work primarily focuses on that using modified parse-tree representation. Some existing techniques used graph representation to identify characteristics of the query based on a predefined fixed list of SQL keywords. As the complete graph representation requires high time complexity for traversals due to the unnecessary links, a modified parse tree of tokens is proposed here with restricted links between operators (internal nodes) and operands (leaf nodes) of the WHERE clause. Tree siblings from the leaf nodes comprise the WHERE clause operands, where the attackers try to manipulate the conditions to be true for all the cases. A novelty of this work is identifying patterns of legitimate and injected queries from the proposed modified parse tree and applying a pattern-based neural network (NN) model for detecting attacks. The proposed approach is applied in various machine learning (ML) models and a neural network model, Multi-Layer Perceptron (MLP). With the scrupulously extracted patterns and their importance (weights) in legitimate and injected queries, the MLP model provides better results in terms of accuracy (97.85%), precision (93.8%) and AUC (97.8%)
Mohammed S. Albulayhi; Dina M. Ibrahim
Abstract
The Open Web Application Security Project (OWASP) is a nonprofit organization battling for the improvements of software protection and enhancing the security of web applications. Moreover, its goal is to make application security “accessible” so that individuals and organizations can make ...
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The Open Web Application Security Project (OWASP) is a nonprofit organization battling for the improvements of software protection and enhancing the security of web applications. Moreover, its goal is to make application security “accessible” so that individuals and organizations can make educated decisions about security threats. The OWASP is a repository of tools and standards for web security study. OWASP released an annual listing of the top 10 most common vulnerabilities on the web in 2013 and 2017. This research paper proposed a comprehensive study on Components with known vulnerabilities attack, which is ninth attack (A9) among the top 10 vulnerabilities. Components with known vulnerabilities are the third-party components that focal system uses as authentication frameworks. Depending on the vulnerability it could range from subtle to seriously bad. This danger arises because the app’s modules, like libraries and frameworks, are almost always run with the highest privileges. If a compromised aspect is abused, the hacker’s task of causing significant loss of information or server takeover is easier.