Author(s): Seshagirirao Lekkala*, Raghavaiah Avula and Priyanka Gurijala
Next-generation firewalls are available and use machine learning and generative modeling to enhance the detection of hard-to-detect cyber threats. These systems incorporate advanced security controls, policies, and protocols with Layer 7 of the OSI model. This chapter updates these steep AI-based protection systems and applications. We present a taxonomy of machine learning solutions for cybersecurity and outline a family of next-gen firewalls that incorporate intelligent AI-based technologies, including deep learning, generative adversarial networks, and convolutional neural networks. We present extensive experimental results that show how deep generative Gaussian models effectively identify hard-to-detect threats of particular interest. Then we conclude with recommendations and further R&D directions within the next-generation firewall ecosystem that benefits significantly from AI and machine learning.
Next-generation (next-gen) firewalls are already in the cybersecurity market, delivering crucial advancements previously not seen in traditional firewalls, in addition to incorporating the advanced security controls, policies, and protocols with Layer 7 of the OSI model. In general, next-gen firewalls leverage Artificial Intelligence (AI) and machine learning resources to keep up with the ongoing evolution of cyber threats as the systems develop and learn from accurate and incident data conditions. However, a shortcoming of some of the most expensive and advanced next-gen firewalls available is their reliance on supervised learning, which may require shared sensitive information from industries and extra difficulties.
View PDF