Performance Evaluation of Network Packet Analysis Tools using Analytical Techniques.

This study rigorously evaluates the performance of two widely used network packet analysis tools, Wireshark and Nmap, through analytical methods and experimental testing. Key metrics—packet capture rate, latency, CPU utilization, and memory consumption—are assessed across diverse network conditions, including low, medium, and high traffic loads. The research aims to equip network administrators and security professionals with actionable insights for selecting the optimal tool for specific tasks, balancing detailed analysis with resource efficiency. Experimental findings indicate that Wireshark outperforms in scenarios demanding in-depth packet inspection and real-time monitoring, achieving a packet capture rate of 98.5% and latency of 2.67 ms, though it incurs higher resource demands (15.43% CPU, 125 MB memory). Conversely, Nmap excels in resource efficiency, with lower CPU (13.13%) and memory (108 MB) usage, making it ideal for rapid network scans and security audits. The study delineates clear trade-offs: Wireshark suits forensic investigations, application performance analysis, and detailed troubleshooting, while Nmap is better tailored for network discovery, vulnerability detection, and resource-constrained environments. Additionally, the research examines the influence of network topology, scalability, and emerging technologies— such as IoT and machine learning—on tool performance. By offering a data-driven comparison, this work enriches the understanding of network analysis tools and provides practical deployment recommendations. Future research directions include evaluating these tools in complex architectures, integrating machine learning for advanced analysis, and assessing their efficacy in IoT and cloud-based settings. [ABSTRACT FROM AUTHOR]