Time-Series Modeling for Intrusion Detection Systems

The advent of computer networks and the Internet has drastically altered means by which we share information & interact with each other. However, this technological advancement also created room for malevolent behaviour where individuals exploit weak points intent gaining access to confidential data, blocking activity etc. To end, intrusion detection systems (IDS) are needed filter malicious traffic prevent common attacks. In past, these relied on a fixed set rules or comparison previous increased availability computational power machine learning emerged as promising solution task. While many now use methodology in real-time reactive approach mitigation, aim explore potential configuring it proactive time series prediction. work, delve into possibility further. More specifically, convert classic IDS dataset time-series format predictive models forecast forthcoming malign packets. findings indicate that our model performs strongly, exhibiting accuracy is within 4% margin when compared conventional detection.