TY  - JOUR
AU  - Sharma, Ishu 
AU  - Sajid, Ahthasham 
AU  - Suud, Mazliham Mohd 
AU  - Alam, Muhammad Mansoor 
PY  - 2026
TI  - Enhancing Network Security through Accurate Asset Discovery Using Lightweight Agent-Based Approach
JF  - Journal of Computer Science
VL  - 22
IS  - 4
DO  - 10.3844/jcssp.2026.1158.1174
UR  - https://thescipub.com/abstract/jcssp.2026.1158.1174
AB  - Any organization's network administrators and security professionals must have an accurate and real state of assets connected to the network to devise different policies for securing critical resources by identifying vulnerabilities. Asset discovery is a challenging and critical task in vulnerability assessment. The vulnerability of the organization’s network can be correctly analysed only with the accurate prediction of connected devices. In this paper, the recent research activities in asset identification are explored to identify the gaps for future research directions. This paper provides a systematic review of the techniques that can be utilized for asset identification tasks in the organization. The comparative analysis presented in this paper lists the parameters required to choose a specific policy for network discovery. The proposed lightweight agent-based technique is inspired by socket communication and can fetch the accurately installed application software details on remote devices. The proposed method is tested on the campus area network by mapping Nmap Scanning results with the results achieved from the proposed methodology to optimize the network discovery task. The state-of-the-art network discovery tool Nmap provides probability-based results, and our proposed lightweight agent-based technique can enhance the finding of Nmap with exact details on IT assets.