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@article{169366,
        author = {Yogesh Bihani and Neelam Chandolikar and Abhinandan Bhuse and Vedant Bijjargi and Avinash Birajdar and Samruddhi Bobde and Kshitij Bhutada},
        title = {Cyber Shield: Recognizing and analyzing fake link to identify intrusion attack},
        journal = {International Journal of Innovative Research in Technology},
        year = {2024},
        volume = {11},
        number = {6},
        pages = {1558-1566},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=169366},
        abstract = {The prevalence of cyber-attacks has underscored the need for advanced intrusion detection systems capable of identifying and mitigating threats in real-time. Our project, "Intrusion Attack Identification by Identifying Fake Links," addresses this critical challenge by focusing on the detection of malicious links used in various cyber-attack vectors, including phishing, malware distribution, and social engineering. By leveraging machine learning algorithms and advanced pattern recognition techniques, we developed a robust system that analyzes URLs for signs of deception and anomalous behavior. Our system integrates seamlessly with existing network infrastructure, providing real-time alerts and comprehensive reports on identified threats. It utilizes a multi-layered approach to scrutinize URLs, examining factors such as domain reputation, URL structure, and embedded scripts. Additionally, it incorporates natural language processing to detect phishing attempts that use social engineering tactics to deceive users. One of the key features of our system is its adaptive learning capability, which allows it to continuously improve its detection accuracy by learning from new threats and user feedback. This dynamic feature guarantees that the system will continue to be successful in the face of changing cyberthreats. Additionally, our technology is built to reduce false positives, which eases the workload for cybersecurity staff and frees them up to concentrate on real threats. Our experimental results demonstrate a high detection accuracy and low false-positive rate, highlighting the system's effectiveness in enhancing cybersecurity measures. This project contributes to the broader effort of securing digital environments by providing a proactive approach to detecting and neutralizing fake link-based intrusion attempts. By addressing the ever-growing threat landscape, our system marks a substantial leap in the field of cybersecurity, offering robust protection against a wide range of cyber-attacks.},
        keywords = {cyber-security, intrusion, malware, phishing},
        month = {November},
        }