Given the country’s massive multifaceted digital divides, is AI integration the timely antidote to correct rushed digitalization and repel AI-driven cyberattacks?

Sujata S Iyer, Head, AI Security, ManageEngine

SI: As is the case for CISOs around the world, three key ways for AI to be integrated into cybersecurity are:

  1. Threat detection

    Traditional cybersecurity technologies are rigid and bound by static conditions. This hinders organizations from detecting patterns in user behavior that are not noticeably different from the set threshold, but can still have a huge impact on overall security. This can be overcome by AI-powered detection, which is dynamic in nature and can have thresholds that are unique to each use case. Specialized tools — such as user and entity behavior analysis engines and behavior-based AI malware detection systems — detect anomalies and spot potential threats before the latter can infiltrate the network.

  2. Data analysis and threat intelligence

    AI-driven data analytics proves to be efficient in handling huge volumes of data and deriving real-time insights. Leveraging these insights, a user can foresee possible attack attempts and prepare themselves accordingly through enhanced proactive measures. These proactive measures can lead to practices (such as allocation of proper resources, enhancement of existing tools, etc.) and improve cyber resilience.

  3. Response automation

    When ambushed by sophisticated modes of attack, it is important to ensure that the organization’s response and remediation tactics are sufficiently advanced. AI-driven threat response mechanisms are promising, as they automate investigation processes, isolate affected systems, and contribute to reducing the time taken to cater to each aspect. This, in turn, increases the efficiency of cybersecurity teams, allowing them to be more vigilant of threats, and seamlessly mitigate any attempt to exploit vulnerabilities.