BROWSER THREAT DETECTION PLUGIN SYSTEM OF OTIS PHILIPPINES INC.

Abstract

This study focuses on developing a browser extension to enhance security and detect potential threats in the browsing activities of employees at OTiS Philippines Inc. The Browser Threat Detection Plugin System employs machine learning algorithms to analyze web history, identify patterns, and recognize suspicious activities within the user's browser. OTiS Philippines Inc., established in February 2005, primarily publishes free magazines featuring a wide range of local advertisements. The researchers adopted the Waterfall Model (SDLC) as their development approach, ensuring a structured and systematic process. This methodology allowed for detailed monitoring of each development stage, including data collection, system planning, construction evaluation, and cybersecurity impact assessment. The implementation of the Browser Threat Detection Plugin System at OTiS Philippines Inc. has proven successful. The system effectively detects both malicious and harmful websites with a high level of accuracy, significantly improving the security of the company’s browsing activities. Employees at OTiS Philippines Inc. previously faced security risks due to suspicious and malicious websites. In response, the researchers developed the Browser Threat Detection Plugin System to enhance browsing safety. Feedback from the client was gathered through interviews and analyzed to refine the system. One limitation is that the system is currently optimized for Opera, the only browser permitted by company policy. Future developments will aim to expand compatibility across multiple browsers.