Data Security Analysis with Advanced Firewall Filtering at PT PUSRI

Misinem, . and Muhammad Ari, Januarta and Tamsir, Aryadi and Ahmad, Qudri and Nurul Adha Oktarini, Saputri (2024) Data Security Analysis with Advanced Firewall Filtering at PT PUSRI. Journal of Data Science, 2024 (41). pp. 1-8. ISSN 2805-5160

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Abstract

Data and network security analysis are essential for ensuring the integrity, confidentiality, and availability of organizational data. Among the various threats, sniffing attacks—where malicious actors intercept and monitor data transmitted over a network—pose a significant risk to data security. This study analyzes the network security performance of the IT Service Department of PT—Palembang, focusing on the impact of sniffing attacks and the effectiveness of countermeasures. The research involves a comprehensive evaluation of the existing security infrastructure, testing for vulnerabilities to sniffing attacks, and implementing advanced security mechanisms. These mechanisms include encryption protocols, network segmentation, and intrusion detection systems. The analysis assesses the performance of these countermeasures in mitigating risks and enhancing overall network security. Findings from this study reveal that the proper implementation of security mechanisms significantly reduces the risk of sniffing attacks. Encryption ensures the confidentiality of transmitted data, network segmentation limits unauthorized access, and intrusion detection systems provide real-time threat identification. Additionally, the research highlights the importance of proactive measures, such as training IT staff on security best practices and implementing enhanced real-time monitoring systems. This study not only evaluates the technical aspects of network security but also provides actionable recommendations for sustainable improvements. By addressing both current vulnerabilities and future preparedness, the analysis underscores the critical role of a multi-layered security approach in safeguarding organizational data

Item Type:	Article
Uncontrolled Keywords:	Network security, Sniffing attacks, Encryption, Network segmentation, Intrusion Detection
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software T Technology > T Technology (General) T Technology > TK Electrical engineering. Electronics Nuclear engineering
Depositing User:	Unnamed user with email masilah.mansor@newinti.edu.my
Date Deposited:	08 Nov 2024 03:46
Last Modified:	31 Dec 2024 07:11
URI:	http://eprints.intimal.edu.my/id/eprint/2022

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