SEC595: Applied Data Science and AI/Machine Learning for Cybersecurity Professionals

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Contact UsThe unique and intrinsic methods by which Linux application containers are created, deployed, networked, and operated do not lend themselves well to the conventional application of methods for conducting intrusion detection and analysis in traditional physical and virtual machine networks. While similarities exist in some of the methods used to perform intrusion detection and analysis in conventional networks as compared to container networks, the effectiveness between the two has not been thoroughly measured and assessed: this presents a gap in application container security knowledge. By researching the efficacy of these methods as implemented in container networks compared to traditional networks, this research will provide empirical evidence to identify the gap, and provide data useful for identifying and developing new and more effective methods to secure application container networks