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@article{180478,
        author = {Prof. Shah Saloni Niranjan and Dr. Taware G. G. and Shreyash Bhandwalkar and Vaishnavi Ghadge and Komal Papal},
        title = {Internal Intrusion Detection and Protection by Self-Monitoring via Forensic Techniques and help of  Data Mining},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {1},
        pages = {1327-1333},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=180478},
        abstract = {Nowadays, billions of individuals around 
the world rely on the internet for daily activities. With 
this increasing reliance comes a growing need for 
advanced cybersecurity solutions. One such emerging 
technology is intrusion detection, which plays a vital 
role in identifying and preventing malicious actions 
within a system. This project introduces a new 
generation of security technology known as the 
Intrusion Detection and Protection System (IDPS), 
which continuously monitors user behavior across a 
network using a localized grid-based process. The 
system is designed to detect suspicious activities and 
respond effectively by analyzing behavioral patterns 
and building user profiles for real-time monitoring. To 
validate the effectiveness of the proposed system, it is 
assessed using both traditional intrusion detection 
systems and modern forensic analysis methods. The 
foundational study also includes a comprehensive 
literature review of various Intrusion Detection 
Systems (IDS) and Internal Intrusion Detection 
Systems (IIDS), each leveraging distinct algorithms 
and data processing techniques to detect intrusions in 
real time. The Internal Intrusion Detection System 
(IIDS), specifically developed during this research, 
utilizes pre-established algorithms to identify and 
differentiate between legitimate and unauthorized user 
activities 
within a network environment. This 
approach aims to enhance cyber analytics by offering 
more precise and timely threat detection.},
        keywords = {},
        month = {June},
        }