With the rapid expansion within the digital space, the risk of new threats and vulnerabilities are also increasing. This continuous expansion of activities and dependence on cyberspace has necessitated requirement for situational awareness. Thus, situational awareness within the digital space provides both a holistic and specific view of threats and vulnerabilities, allowing organizations the ability to identify, process, and comprehend information in real-time. Machine learning can be used in cyber situational awareness to experiment with hypothetical threat models to identify likelihood and impact of such threats. In addition, machine learning can be used to identify new hypotheses from the data.

CHAPTER 1: INTRODUCTION 

CHAPTER 2: EXECUTIVE SUMMARY

CHAPTER 3: MARKET OVERVIEW

CHAPTER 4: CYBER SITUATIONAL AWARENESS MARKET, BY COMPONENT

CHAPTER 5: CYBER SITUATIONAL AWARENESS MARKET, BY SOLUTION TYPE

CHAPTER 6: CYBER SITUATIONAL AWARENESS MARKET, BY DEPLOYMENT MODEL 

CHAPTER 7: CYBER SITUATIONAL AWARENESS MARKET, BY ORGANIZATION SIZE

CHAPTER 8: CYBER SITUATIONAL AWARENESS MARKET, BY INDUSTRY VERTICAL

CHAPTER 9: CYBER SITUATIONAL AWARENESS MARKET, BY REGION

CHAPTER 10: COMPETITIVE LANDSCAPE

CHAPTER 11: COMPANY PROFILES