AI in Cybersecurity: 20 years of innovation
From predictive systems to the recent proliferation of generative AI-based virtual assistants such as ChatGPT, artificial intelligence has become a key driver in many sectors, and cybersecurity is no exception. The disruptive impact of GenAI has popularized AI use recently but this technology has actually been deployed for over 20 years in the security sector, serving as an additional and critical tool for proactive threat management that enhances operational efficiency.
From Proactive Protection to Zero-Trust Application Service Model
Traditional security systems have relied on manual, reactive analysis to detect threats, making them inefficient, slow, and not scalable enough to address the growing volume of malware. In 2004, WatchGuard pioneered AI integration into protection systems, making it possible to detect threats before they arrived, rather than waiting for attacks to be identified manually. AI automated threat detection, which made endpoint security much more efficient and proactive.
Historically, cybersecurity has been understood in terms of establishing a perimeter that protects corporate networks from the inside out. However, this perimeter has been weakened over the years. Users' devices have become the first line of defense, and at WatchGuard, we have concentrated on adapting AI to hone its capabilities and leverage this new technology to protect our customers.
Introducing our Zero-Trust Application Service in 2015 proved a major milestone in this regard. Instead of simply preventing the execution of known malware, this solution only allows trusted applications to run, using AI to automatically validate which applications and processes are safe. This zero trust approach is still an effective protection strategy, as it blocks known and unknown malware, representing a crucial evolution in security policy.
AI as the Backbone of Endpoint Security
With 90% of cyberattacks and 70% of data breaches originating on devices, endpoint protection is a priority for any organization. Nonetheless, many traditional security solutions lack the visibility needed to detect applications that may contain threats or suspicious user and device behavior.
AI has been key to reducing response times and automating threat detection, delivering a significant advantage in shielding organizations against increasingly complex attacks. At WatchGuard, AI has not only automated threat classification, but it also helps detect anomalies that may indicate an attack in progress. This enables administrators to focus on the most critical cases and avoids wasting time on false or low-priority alerts.
Machine learning has further strengthened threat detection. At WatchGuard, we employ this technology to address critical points by improving operational efficiency, providing more agile and accurate detection. This not only reduces the risk of financial loss, but also simplifies real-time alert management, reducing its complexity.
AI is not magic; it is applied science
Although the recent fascination with this technology portrays it as almost magical, this is far from being the case. AI is essentially a tool that helps us gain efficiency in many and varied contexts and cybersecurity is one such field of application.
By integrating artificial intelligence over the last two decades, WatchGuard has implemented new ideas as disruptive as collective intelligence, thus becoming a powerful ally in solving real cybersecurity problems. What started as an innovative extra is now an indispensable pillar of modern security.
While AI visibility has grown exponentially over the past year, at WatchGuard, we know that the real innovation lies in how this technology can make operations more efficient, reduce response times, and ultimately protect one of business’s most valuable assets: information.
