Firewalls are crucial for network security, regulating traffic to prevent cyber threats. This review explores firewall rule analyzers, examining their functionalities, methodologies, and implications. The authors delve into firewall policy reconnaissance, anomaly detection, and rule optimization techniques. Integrating advanced technologies like machine learning and SDN, they analyze automation's role and compliance implications. This review provides insights into enhancing network security posture through effective firewall management.
Top1. Introduction
Computer networks of our modern time could not be protected from diverse cyber threats if not for the network firewalls as the first-line-of-defence against the cyber adversaries who may want to compromise systems of organizations and the networks in general (Alatalo, 2022). Security is one of the core components affecting the access policy configurations of the incoming and outgoing network traffic and serves as a gate of networks guarding them from external sources (Ali et al., 2014). However, the performance of firewall policies relies heavily on their accuracy, thoroughness and how much technology adheres to the organization needs (Andalib & Babamir, 2023).
While the threat environment has kept on getting elaborated by the offensive weapons characterized by the high-grade cyber-attacks and abruptly appearing new business needs, the complexity of managing internetworking policies have exponentially grown (Asad & Gashi, 2022). The sheer complexity and size of the firewall policies that must be taken into consideration become barriers to organizations' ability to meticulously categorize, optimize as well as maintain these instances to build a solid security posture (As-Suhbani & Khamitkar, 2017). As firewalls have been facing several challenges, network rule analyzer setup has become an appropriate response to keep the process of firewall policy management up to date (Bansal & Mahajan, 2014).
The network firewall gate rules scrutineers or analyzers are specialized software tools that are designed to assess, optimize, and audit firewall rules across various network environments (Chen et al., 2022). With these analyzers, organizations can perform a set of functions including crosschecking rules, digitally simulating traffic among computer security components, creating clear policies, visualization, highlighting and solving anomalies and policy conflicts (Clark & Agah, 2015; Cordova et al., 2018). Machine learning and data mining techniques utilize classifying, sorting, and predicting technology to accelerate tedious policy management processes, lower security risks, and improve network resilience (Coscia et al., 2017; Omrani & Mashiach, 2016).
By unique way in this impressive review, we will explore the depths of the world of network firewall rule analyzers and their capabilities, advantages, disadvantages, and current use in real life. We intend to achieve this by formulating a comprehensive review of the existing literature and the emerging evidences on the answers of the questions including: which type of analyzer is needed, how to deploy analyzers, and how to reap the full benefit of the analyzers to help organizations achieve the top-notch cybersecurity defense in the continuously challenging cyber security environment.