• Sanika Randive
• Rupashree Thakur
• Mrs. Neeta Ranade

Abstract In today’s cybersecurity environment, network traffic analysis is crucial. It helps in understanding what is happening on a network and identifying any suspicious or harmful activities. This process plays a vital role in keeping digital systems safe from hidden threats in cyberspace. By analyzing how data moves across a network, security professionals can detect unusual patterns that often signal potential problems. One important part of this process is closely monitoring network traffic. This involves capturing and analyzing data packets to extract useful information. When analysts examine these digital pieces, they can spot inconsistencies such as unexpected traffic volumes, unusual data transfers, or atypical communication methods. These anomalies act as early warning signs, prompting further investigation and action if necessary. To uncover hidden threats in network traffic, analysts use various methods. For example, statistical analysis helps in identifying anything that stands out from normal behavior. Machine learning algorithms are also valuable because they can learn from large datasets and detect complex patterns that might indicate harmful activities. Behavioral analysis is another approach that looks at how users and systems behave, helping to spot subtle anomalies that might be missed by standard detection tools. The effectiveness of network traffic analysis depends heavily on distinguishing between normal and malicious traffic. That’s why researchers have developed advanced models to classify this data. These models use a combination of details like protocol information, content, and traffic behavior. They are trained on large volumes of normal traffic and attack examples to make more accurate decisions about what they observe on the network.

Deep Packet Inspection,Lateral Movement,Command-and-Control (C2), Distributed Systems etc

"A real-time network traffic packet inspection and malicious threat classifier", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 9, page no.f523-f528, September-2025, Available :http://www.jetir.org/papers/JETIR2509568.pdf

"A real-time network traffic packet inspection and malicious threat classifier", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 9, page no. ppf523-f528, September-2025, Available at : http://www.jetir.org/papers/JETIR2509568.pdf