A recent IT trends report found that IT professionals face a looming challenge with the growing complexity of new security tools and technologies, increased tech requirements and fragmented legacy and modern technologies that further complicate and widen the attack surface.
Cybersecurity is now out of the scope of manual handling and warrants artificial intelligence.
The COVID-19 global pandemic pushed organizations toward rapid digital transformation to ensure business continuity without allowing the luxury of ensuring cybersecurity. As a result, every industry saw an uptick in cyberattacks and breaches.
81% of global companies experienced increased cyber threats during the pandemic, while 79% of organizations suffered downtime due to security risks during peak business season. Google blocked 18 million COVID-related scams daily. Average ransomware payment amounts surged by 60 percent during the second quarter of 2020, and daily cybercrime complaints increased by 300-400 percent.
Consequently, business leaders grew more aware and threatened by security risks, knowing it’s a matter of ‘when’ and not ‘if’ their company will be targeted.
Today’s enterprise needs AI/ML for security now more than ever. Sophisticated attacks, a widened attack surface, rapid innovation and the urgency to stay on top of vulnerabilities require more than human intelligence.
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Artificial intelligence and machine learning help scale data analysis, improve response speed, secure innovative and transformative technologies and stay proactively prepared for incidents. 93% of IT executives are already using or considering AI and ML to make their tech stack more resilient.
Here are a few specific reasons why CISOs prefer AI/ML over people in today’s threatscape-
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Enterprises spent $13.3 billion on Endpoint Protection Platforms in 2021, predicted to reach $26.4 billion by 2025, as per Gartner. They need to achieve more visibility and control over endpoints for zero-trust security.
The security perimeter in any organization has expanded to include human and machine identities, which can be secured only using data-driven insights and intelligence. AI/ML in cybersecurity identify malware attack patterns and fine-tune risk scores based on behavioral patterns, location and other parameters of privileged user accounts, preventing breach attempts.
According to a recent survey, 71% of IT professionals find patching complex and time-consuming, while 53% said organizing and prioritizing critical vulnerabilities leaves no time for patch management.
Organizations today can employ AI and ML technologies to locate, track and patch endpoints that need updating without spending useful hours on this monotonous activity. As cybersecurity platforms improve bots’ accuracy in predicting which endpoints need patching, vulnerability and patch management will get efficient and automated.
In an experience economy where businesses define themselves by the ease of working with them, identity and access management can become table stakes in minimizing friction. Modern IAM platforms with AI/ML can detect anomalous behavior even after authentication and trigger an appropriate response.
AI can enable zero-trust by dynamically protecting resources, implementing fine-grained access policies that factor in complexities in users, data and assets, eliminating personal data from access tokens and ensuring continuous verification.
AI and ML can help build threat simulators connecting with endpoints in an organizational network to emulate a threat lifecycle and test security defenses without interacting with production endpoints and servers. This way, organizations can identify gaps in their cybersecurity posture without compromising assets or impacting operations.
Cybersecurity simulations can also help identify talent gaps in an organization and point toward skills that need to be onboarded, whether in-house or outsourced.
A hybrid work culture requires support for remote workers accessing multiple devices from different locations. While zero trust enhances operations, it presents issues in coordination. AI can help manage digital identity by creating unique user profiles based on historical behaviors, role-based policies and contextual user data.
Automated identity management can strengthen an organization’s security posture without creating impossible work for their teams.
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Every organization will have a unique zero-trust security roadmap. AI and ML will prove central to zero trust as they help analyze, interpret and act on network telemetry data in real-time.
Technology continues to be a double-edged sword as new digital applications and services open new avenues for value creation while expanding the risk surface. With cloud technologies and IoT in place, organizations need more than talented cybersecurity professionals to execute protection, prevention and readiness strategies. They need AI and ML.
It’s no longer just here for the buzz, instead, it is here to create value. Our relationship with this technology goes way beyond the era of buzz and so we know and understand its importance with businesses. If you are looking to secure your business now or future-proof it from any further security threats, our AI/ML experts can be of your help!