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@article{206795,
        author = {Preethi and Sanjana C Suvarna and Shreya S Rao and Sowjanya and Yamini},
        title = {ThreatLens: A Unified Tool},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {no},
        pages = {470-474},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=206795},
        abstract = {As digital services are expanding rapidly, we are increasingly depending on websites, which leaves people open to phishing scams and having their passwords stolen. Our paper describes ThreatLens, a small addition to the browser that tackles both of these big problems as they happen and only on a computer. The ThreatLens components that identify phishing sites examine the web address (URL) by searching for common tricks in the words and how the address is built, and then label each site as safe, possibly a problem, or dangerous. For passwords, the password security part of ThreatLens determines their strength by measuring the amount of random variation they have and the number of characters they have. It also checks if your password is on a list of those used in past data leaks, using SHA-1 hashing with k-anonymity that keeps your details private. Importantly, your private information does not go to any other location. When we tested it, ThreatLens was fast, got things right most of the time, and did not slow down the browser much. This tool integrates these capabilities into a single platform with an intuitive design for ease-of-use and provides users with actionable warnings to enable safe browsing practices.},
        keywords = {Browser extension security; cybersecurity; data breach detection; k-anonymity; password strength analysis; phishing detection; privacy preservation; real-time threat detection; secure authentication; SHA-1 hashing; URL analysis, web security.},
        month = {July},
        }