The popularity of the internet has made the use of web applications ubiquitous and essential to the daily lives of people, businesses and governments. Web servers and web applications are commonly used to handle tasks and data that can be critical and highly valuable, making them a very attractive target for attackers and a vector for successful attacks that are aimed at the application layer. Existing misuse and anomaly-based detection and prevention techniques fail to cope with the volume and sophistication of new attacks that are continuously appearing, which suggests that there is a need to provide new additional layers of protection. This work aims to design a new layer of defense based on deception that is employed in the context of web application-layer traffic with the purpose of detecting and preventing attacks. The proposed design is composed of five deception strategies: Deceptive Comments, Deceptive Request Parameters, Deceptive Session Cookies, Deceptive Status Codes and Deceptive JavaScript. The strategies were implemented as a software artifact and their performance evaluated in a testing environment using a custom test script, the OWASP ZAP penetration testing tool and two vulnerable web applications. Deceptive Parameter strategy obtained the best security performance results, followed by Deceptive Comments and Deceptive Status Codes. Deceptive Cookies and Deceptive JavaScript got the poorest security performance results since OWASP ZAP was unable to detect and use deceptive elements generated by these strategies. Operational performance results showed that the deception artifact could successfully be implemented and integrated with existing web applications without changing their source code and adding a low operational overhead.
Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:ltu-64419 |
Date | January 2017 |
Creators | Izagirre, Mikel |
Publisher | Luleå tekniska universitet, Institutionen för system- och rymdteknik |
Source Sets | DiVA Archive at Upsalla University |
Language | English |
Detected Language | English |
Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
Format | application/pdf |
Rights | info:eu-repo/semantics/openAccess |
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