Secure Lock: An Approach at Protecting Company Data via Filtered IP Specifications
Project Author
Issue Date
2024-05-03
Authors
Kelly, Peyton
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Embargo
First Reader
Bonham-Carter, Oliver N.
Additional Readers
Kapfhammer, Gregory
Keywords
Django , Python , Security
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Abstract
This research project focuses on developing a robust system for tracking user interactions within a web application, specifically targeting unauthorized access attempts based on IP addresses. The primary objective was to establish a system of checks capable of identifying and blocking restricted IPs from accessing the application, with a particular emphasis on the pivotal role of administrators in managing security measures.The scope of the study revolves around data protection and security within web environments. Utilizing the Django framework, a web application was constructed, integrating IPSTACK to gather pertinent information about accessing IPs. The research methodology centered on evaluating the efficacy of restricting access to designated areas deemed off-limits. Findings from the study indicate that the implemented system effectively renders the site unavailable to restricted IPs, thereby mitigating potential security breaches. Additionally, monitoring of CPU and RAM usage revealed insights into the detection of malicious activities such as SQL injections or unauthorized data entry attempts.The significance of this research lies in its practical application, offering a user-friendly security solution suitable for small businesses and educational institutions seeking to safeguard their data. Furthermore, this study underscores the potential for future enhancements, particularly through the integration of machine learning algorithms, which could further automate and optimize the security measures, potentially reducing the reliance on administrative oversight.In conclusion, this research contributes to the ongoing efforts in enhancing web application security, providing a viable solution for organizations looking to fortify their data protection measures in an increasingly digital landscape.
Description
Chair
Major
Computer Science
Department
Computer and Information Science