Prompt: How should we approach the development of cyber-policy and -infrastructure given the “short arm” of predictive knowledge?

Approaches to developing cyber policy and infrastructure seem daunting. To boot, predicting the future is impossible. Technological advances are happening at an exponential rate, so predicting every threat that could potentially arise will be like playing a game of whack-a-mole. On top of this, the world is constantly online, meaning malicious threat actors can operate anywhere at any time. Threats may seem endless and unstoppable, but grounded fundamentals are always key in any development phase. Starting with a strong foundation for anything, be it a building, vehicle, company, or cyber policy results in something that is prone to last. In regard to cyber policy, an example of a principle that can help create a strong cyber foundation would be the principle of least privilege. Individuals on a network device are only allowed as much control as they need to complete their tasks or job. This reduction in access reduces a large swath of potential threat vectors with a simple principle. Though very powerful, grounded fundamentals alone will not be sufficient to combat daily threats. During development, flexible policies and infrastructure are necessary. Without flexibility, the ability to reconfigure or build onto existing systems is unobtainable. As new information is gathered, updates, changes, or patches may be needed to keep cyber infrastructure secure or cyber policy watertight. The final approach one should take in the development stage of cyberinfrastructure would be to place emphasis on the scalability of their systems. Rapid expansion or consolidation of network devices could overwhelm systems. For policy, adding clauses and methods for cyber security teams to scale systems up and down is a crucial factor in predictive knowledge, as one does not know when upscaling or downscaling will occur, only that it will. To close, one does not have all the answers to every problem. That being said, laying a groundwork that is flexible, scalable, and has solid principles is the greatest approach given the “short arm” of predictive knowledge.