This report looks at the present state of Malicious uses of AI, then makes predictions for the future. It ends with recommendations to prevent malicious use of AI. (more available)

From the report, “With endpoint security products continuing to be at the tip of the spear of cyber defenses for years to come, the question is how to ensure the best possible security posture. (more available)

To provide insights into the complex challenges faced by organizations as they fight to protect their brands, Radware produces an annual Global Application & Network Security Report. (more available)

In this whitepaper they cover the different defense technologies used over time, how different attacks vectors influenced this evolution, how the industry adopted different approaches over time, and why the prevention approach has returned and why it matters. (more available)

This is a very good guide to building a good threat detection model for machine learning.

In this white paper, they aim to define generations of machine learning and to explain the maturity levels of artificial intelligence (AI) and machine learning (ML) that are being applied to cybersecurity today. (more available)

This report takes a look at some of the problems in AI, and machine based cyber security, and seeks to show how they can be overcome. (more available)

A close inspection of one of the most exciting and promising fields of research in 2017, and how it might be applied to the fast-moving world of mobile security. (more available)

This paper delivers insights into the prevalent cybersecurity issues facing organizations today: from ransomware to exploits and machine learning, it shares the experiences and future plans of IT managers across the globe. (more available)