In a rapidly transforming threat landscape, cyber defense solutions must be both innovative and flexible to harden organizational security against ever-evolving adversarial attacks. While current signature detection techniques effectively combat known attack structures, they are inherently reactive and require significant time to respond to sophisticated attacks. These challenges are compounded by the individualized characteristics of a given network, as each demands a system that understands its unique threats. Cybersecurity experts face the challenge of building flexible solutions that can learn the norms of a given network while rapidly adapting to defend against new attack structures. Generating timely identification of cyber threats hidden within the high volume of data generated by a network is an industry-wide problem that continues to challenge and stress organization’s cybersecurity operations.
To address such complex challenges, many organizations have taken on efforts to implement artificial intelligence (AI)-based solutions into their cyber operations. According to an April 2019 survey by the Consumer Technology Association, AI’s top use in 2018 was in cybersecurity, with 44 percent of all AI applications being used to detect and deter security intrusions. In a July 2019 survey by Capgemini, more than two-thirds of respondents said that they believe AI will be necessary to respond to future cyberattacks given the current threat environment.