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@article{191080,
        author = {Soham Murkar and Ayana Xavier and Aarohi Talele and Akanksha Singh and Nilambari Narkar},
        title = {Cyber Gaurdian},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {8},
        pages = {9023-9027},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=191080},
        abstract = {In today’s digital world, the rapid growth of online communication and data exchange has increased the chances of cyber threats through file sharing. Existing systems often lack efficient real-time detection and rely heavily on manual checks, making users vulnerable to malware, ransomware, and other harmful content. These threats can compromise data integrity, privacy, and overall system security, highlighting the urgent need for automated and reliable protection mechanisms. To address these challenges, we have proposed Cyber Guardian which introduces a secure platform that automatically scans uploaded files to detect and report potential risks. The system integrates file validation, malware detection algorithms, and an instant notification feature to alert users about harmful files. It uses a combination of pattern matching and threat analysis techniques to ensure accurate and fast detection of malicious content before it reaches the user’s device. The implementation of Cyber Guardian, aim to enhance user safety and promote secure file handling practices. The project demonstrates how automation and intelligent detection can act as a proactive defense against cyber threats. By simplifying the process of identifying harmful files, and contributes to a safer digital environment. It serves as an efficient first line of defense in modern cybersecurity.},
        keywords = {Python Core language for threat detection scripts and system monitoring. Tkinter /Electron/Flutter, Watchdog, Os library, Virus Total API, Real-time Notification Library},
        month = {January},
        }