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Castles provide lessons for information security: Only innovation protects against relentless change

Sudden technology shifts have destroyed many security strategies. That reality was clear to security executives who gathered near Zurich in the region once protected by the Helfenberg Castle. Without curtain walls and fortified towers, Helfenberg was stormed by peasants and burned in 1407 during the Appenzell Wars. Today, the ruins of the nearly forgotten fortress provide little more than shade for cows grazing on pastures growing around and among the walls. Many better-designed castles across Europe fell later in the 16th century when innovation made cannons powerful enough to penetrate the thickest walls. Like those stone castle walls of the past, today’s virtual walls provide little lasting security.  Technology shifts require innovation.

Helfenberg Castle. Photo by Eric Johnson

The Corporate Information Security Roundtable spent a day discussing the challenges of security leadership in the AI era. The group catalogued the growing difficulties with many widely used security strategies, from multifactor authentication to phishing training. But the rapid adoption of AI dominated the discussion. The vast promise of AI was accompanied by the realization that security teams would need to innovate to help their organizations protect against looming vulnerabilities. From deep fakes to massive intellectual property losses, AI presents a host of new threats and endless dark innovation.

 

As with any new threat, the first instinct is to build walls. Many organizations have done just that. In the case of Gen AI, walls are used to both keep users inside safe spaces and adversaries out. The approaches fall roughly into three categories.

 

  1. Develop policies that define when and how AI can be used, particularly in conjunction with corporate data. Then, encourage users to stay within a collection of safer apps. For example, organizations are building walled gardens with their own AI models as an alternative to using any of the growing number of AI apps. Data in these walled gardens is not shared across organizations and enjoys some protection.

 

  1. Block users attempting to access risky AI apps from corporate networks. In some cases, that could mean sweeping bans. In other cases, risk scoring could be employed to warn or block users based on the perceived risk of different AI tools. Users could also be pushed to a walled garden depending on the situation and user authorization.

 

  1. Softly block users by flagging attempts to use or share data with AI apps. Users trying to reach risky apps could be warned and then asked to reconsider the need and take responsibility for their actions. In some cases, users could be required to gain supervisor approval.

 

 

Of course, security vendors are rolling out products that combine and supplement these approaches. But the roundtable participants widely agreed that these were, at best, stop-gap solutions.

 

Over the past decade, organizations have tried to wall off users from earlier web-based innovations. From cloud services and storage to social media, walls were little more than speed bumps. Users who hit walls often find ways around the barrier, like moving to personal devices. Besides providing limited security, the walls also slow the adoption of powerful new technologies and meaningful organizational learning. And even the best walls afford limited security from determined users and adversaries.

 

For now, anyway, walls provide some time for security teams to learn from Gen AI user behavior and develop new innovative approaches. More importantly, the learning will help security teams advise their organizations on ethical policies guiding business AI adoption.

 

The group agreed that constant innovation is the only lasting security strategy, meaning they would have to run faster than the hackers to protect their organizations.

 

Eric Johnson è Bruce D. Henderson Professor of Strategy, Ralph Owen Dean, Emeritus, presso Owen Graduate School of Management, Vanderbilt University

 

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