• Lakshmi Priyanka Vallabhajosyula
• Dr.Pretty Diana Cyril

The overview of traffic anomaly detection analysis provided by Traffic Anomaly Detection enables the security features of multimedia services. The author's method is based on the examination of time aggregating neighboring traffic periods. ML techniques and Python are frequently used for anomaly identification in traffic simulation. To begin with, the data from the traffic simulation must be gathered and prepared. This could entail acquiring information on numerous traffic metrics, such as vehicle speed, density, and flow, and then cleaning and translating the information into a format appropriate for ML algorithms.

"ANOMALY DETECTION IN NETWORK TRAFFIC SIMULATION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 5, page no.a709-a716, May-2023, Available :http://www.jetir.org/papers/JETIR2305100.pdf

"ANOMALY DETECTION IN NETWORK TRAFFIC SIMULATION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 5, page no. ppa709-a716, May-2023, Available at : http://www.jetir.org/papers/JETIR2305100.pdf