Detection model for SQL injection attack: An approach for preventing a web application from the SQL injection attack

Buja, Geogiana; Jalil, Kamarularifin Bin Abd; Ali, Fakariah Bt. Hj Mohd; Rahman, Teh Faradilla Abdul

doi:10.1109/iscaie.2014.7010210

Cited by 35 publications

(14 citation statements)

References 2 publications

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“…It is important to understand the seriousness of vulnerable websites or webservers. An attacker may potentially steal sensitive data from the server or disrupt website operations or simply deface pages of the website [4]. It is crucial to realize that protecting the web application with just firewalls is not enough hence we need a periodical detailed VAPT to ensure the system is fool proof.…”

Section: Vulnerability Assessment and Penetration Testingmentioning

confidence: 99%

Vulnerability Assessment of Web Applications using Penetration Testing

Simran T*,

2019

IJRTE

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In recent years, utilization of web applications, web hacking exercises have grown exponentially. Organizations are confronting extremely critical difficulties in anchoring their web applications from rising cyber threats, as bargain with the assurance issues don't appear to be the right approach. Vulnerability Assessment and Penetration Testing (VAPT) methods help us find these vulnerabilities / security loopholes in our systems even before an intruder could find a way to get it. This helps avoid zero-day exploits. This paper aims to elucidate the overview of Vulnerability Assessment and Penetration Testing and introduce the most efficient open source tools used to perform these tests. This paper also presents a combined VAPT testing methodology that incorporates strengths of several existing approaches, with the goal to understand their utility and benefit the most from the tests.

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Section: Vulnerability Assessment and Penetration Testingmentioning

confidence: 99%

Vulnerability Assessment of Web Applications using Penetration Testing

Simran T*,

2019

IJRTE

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“…The model composed a module which will execute a process by employing the Boyer Moore string matching algorithm to make it more efficient and accurate detection [7]. Another research suggested a model, Escrow for detecting large-scale SQLi in an efficient manner.…”

Section: Literature Reviewmentioning

confidence: 99%

SAISAN: An Automated Local File Inclusion Vulnerability Detection Model

Hassan¹,

Bhuyian²,

Sohel³

et al. 2018

IJET

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Communicating and delivering services to the consumers through web applications are now become very popular due to its user friendly interface, global accessibility, and easy manageability. Careless design and development of web applications are the key reasons for security breaches which are very alarming for the users as well as the web administrators. Currently, Local File Inclusion (LFI) vulnerability is found present commonly in several web applications that lead to remote code execution in host server and initiates sensitive information disclosure. Detection of LFI vulnerability is getting very critical concern for the web owner to take effective measures to mitigate the risk. After reviewing literatures, we found insignificant researches conducted on automated detection of LFI vulnerability. This paper has proposed an automated LFI vulnerability detection model, SAISAN for web applications and implemented it through a tool. 265 web applications of four different sectors has been examined and received 88% accuracy from the tool comparing with the manual penetration testing method.

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“…Experimental results show that the proposed approach is more accurate in detecting the attacks than existing approaches. Geogiana Buja et al [10] proposed a detection model for detecting and recognizing the web vulnerability which is; SQL Injection based on the defined and identified criteria. In addition, the proposed detection model will be able to generate a report regarding the vulnerability level of the web application.…”

Section: Related Workmentioning

confidence: 99%

Vulnerability detection and prevention of SQL injection

Kumar¹,

Anaswara²

2018

IJET

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SQL injection attack is the most serious security vulnerabilities on databases are connected with web or within an intranet, most of these vulnerabilities are affected by lack of input validation and SQL parameters are use. The attackers are trying to steal the data which was hidden and by attacking the database using the attacking technique that is called SQL injection attacks. The SQL injection attack detection and prevention technologies are experimented in this paper. There are different defence methods are used to prevent such as, parameterized statement, stored procedures and white list input validation. The comparative results of these methods are highlighted in the table with SQL injection query, prepared statement insertion and selection queries, stored procedures and modify queries. The comparison of these methods used for detection and prevention vulnerability in web server.

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Detection model for SQL injection attack: An approach for preventing a web application from the SQL injection attack

Cited by 35 publications

References 2 publications

Vulnerability Assessment of Web Applications using Penetration Testing

Vulnerability Assessment of Web Applications using Penetration Testing

SAISAN: An Automated Local File Inclusion Vulnerability Detection Model

Vulnerability detection and prevention of SQL injection

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