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Title:
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EXPLORING SQL INJECTION VULNERABILITIES USING
ARTIFICIAL BEE COLONY |
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Author(s):
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Kevin Baptista, Anabela Bernardino and Eugénia Bernardino |
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ISBN:
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978-989-8704-34-4 |
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Editors:
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Pedro Isaías and Hans Weghorn |
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Year:
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2021 |
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Edition:
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Single |
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Type:
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Full |
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First Page:
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147 |
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Last Page:
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154 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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Over the last couple of decades, there has been an enormous growth in technologies and services available on the
internet. This growth must take security into account, although due to the increase in complexity of systems this is not an
easy task. Nowadays, hardly any organization may say with certainty that their system is secure. The Open Web
Application Security listed "Injection" as the most security risk for web applications in 2020. There are many automated
tools to assist professionals in the field, in order to identify this vulnerability. However, keeping these tools up to date has
proven to be a challenge. Therefore, there has been some interest in applying Artificial Intelligence (AI) in this field. In
this paper, we propose an approach to detect SQL injection vulnerabilities in the source code, using Artificial Bee Colony
(ABC). To test this approach empirically we used web applications purposefully vulnerable as Bricks, bWAPP, and
Twitterlike. Simulation results verify the effectiveness of the ABC algorithm. |
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