Strike prediction is the problem of forecasting when and where a lightning event will occur. It depends on signals such as storm structure, electric-field buildup, and local geography, but the result is always uncertain because the atmosphere changes quickly. In practice, the goal is not perfect certainty; it is narrowing the risk window enough to plan sensors, crews, or safety measures.
In cybersecurity, the same idea shows up whenever defenders try to predict an attacker’s strike point: which host, account, or network path is most likely to be hit next. Threat intelligence, anomaly detection, and attack-path analysis all aim to improve that forecast. Better prediction helps teams focus logging, hardening, and monitoring before an intrusion lands, while weak prediction leaves gaps that attackers can exploit.