The speed of digital innovation has completely transformed how organizations do business. Instant access to critical business tools and information via cloud-based applications lets any worker access any needed resources from any location on any device. However, this same innovation trend has also transformed cybercrime, raising the bar on both the speed and severity of attacks, with a successful data breach now costing an average of $3.86 million. And having a remote workforce rounds that cost up by nearly $137,000, to $4 million.
Part of the challenge is the speed at which attacks now occur, complicated by security tools unable to react in time to prevent serious cyber incidents. Previously, cyberattacks moved at human speed, with manual execution required for each step of an attack. These manual processes once provided a viable chance of catching an exploit before it caused major damage. Now, however, cybercriminals are likewise capitalizing on digital innovation, automating and applying artificial intelligence (AI) to many of their tactics. This has enabled them to quickly create more sophisticated, multi-vector attacks that be carried out at machine speeds. For example, cybercriminals are now leveraging AI and automation to actively locate and exploit multiple vulnerabilities simultaneously while evading detection. And automation enables these to be far more prolific and cause even more damage.
As cybercriminals research and carry out automated methods of creating, testing, and disseminating malware and other threats, CISOs and their teams – and the legacy security solutions they have in place – can be overwhelmed by the sheer volume of incidents and alerts that require correlation and investigation. It is impossible to defend against enhanced, automated attacks with isolated security devices, the hand correlation of data between siloed solutions, and manual responses.
Tasks like these in the current threat landscape have forced organizations to take a largely reactive approach to security because IT teams are struggling to validate and plug security holes while keeping operations running. In an effort to keep pace with new threats, and a rapidly expanding network footprint, cybersecurity teams often deploy disjointed point products. This has increased security complexity, especially when information needs to be coordinated across a disaggregated security architecture. As a result, many security teams are falling behind as their own networks become increasingly complex, the number of edges that need to be protected continues to expand, and the cyberthreat landscape accelerates.
CISOs now find themselves constantly searching for new tools to add to their arsenal, often to only find that cybercriminals have developed an even more advanced way to attack and circumvent security controls in place. Traditional security approaches and solutions need to be complemented with alternative models, such as AI and automation. These advantages enable CISOs to not only mitigate the risk brought on by automated cyberattacks with faster response times, broader visibility, and simplified network management, but actually get out ahead of their cyber adversaries.
The Critical Need for AI and Automation
As networks grow increasingly complex and distributed, a lack of visibility into and control over the various elements operating within a network, as well as the growing number of edges, many of which operate as largely autonomous environments, can create security gaps and an opportunity for zero-day threats to wreak havoc. Compounding this challenge further, most organizations are plagued with trying to hire and retain enough skilled resources to effectively manage their environments and to do incident response.
As a result, many of today’s breaches are actually the result of human error, whether a device was misconfigured, or a critical indication of compromise was overlooked. In many cases, it is simply the result of overworked IT admins. Even the most highly skilled IT and security professionals, with the best intentions, can occasionally make mistakes—but mistakes that can ultimately prove to be extremely costly for an organization. By leveraging automation and deploying AI-enabled technologies, it is much easier to identify threats, streamline workflows, and create consistent and efficient responses. They reduce the chances for human error by taking the human out of the loop, as well as through the elimination of slow manual processes.
Leveraging AI-driven solutions, such as AI-assisted network access control, cybersecurity professionals can achieve clear visibility into every device accessing a network at any given time. AI and automated tools simplify network management across these environments and alert security teams to imminent threats and process an automatic threat response. AI, especially, can continuously sift through mountains of data collected from devices across the network to identify threats. It can also automatically investigate the influx of alerts that have traditionally required manual input from security teams, enabling them to make better informed decisions, create a more proactive and efficient security program, and be more cost-effective. This frees up security teams to spend more time honing strategy, researching advanced threats, and cultivating a cyber-aware culture.
Speed is essential in any proactive threat management strategy. Cybercriminals take advantage of every second they can, and automated attacks increase their speed tenfold. That paired with their ever-evolving tactics and an ever-expanding digital attack surface, can lead to overwhelmed and outnumbered security teams. By leveraging solutions that incorporate AI and automation, CISOs can proactively tackle today’s automated cyberattacks and stay a step ahead of cybercriminals.
Find out how Fortinet integrates AI and machine learning capabilities across our Security Fabric to detect, identify, and respond to threats at machine speed.