Automation
In the cyber world, adversaries are attacking at machine speeds, so we need machines to police it. Cyber defenses produce a constant flow of warnings and alerts, and humans are easily overwhelmed. An automation strategy is now critical to staying ahead of attacks.
Machine learning (ML) and deep learning artificial intelligence (AI) tools are vital to this process. If you’re not using ML and AI today, organizations need a plan to do so in the future. The volumes of threats and attack vectors are now too plentiful for human defenders to keep pace. They need automation.
Machine learning can identify threats and can cut through the noise by understanding what constitutes normal in your environment and what constitutes as abnormal activity. AI takes that a step further by adding additional data sources and context; while machine learning will recognize an anomaly when a CPU is suddenly running at 99 percent of capacity, AI can go to the next level and recognize the anomaly is actually an event.
AI pays for itself by connecting dots faster than people can. If your environment is dealing with an advanced persistent threat, people can identify the problem, but it will still take time to respond; AI promises not only to recognize the attack more quickly, but to take decisive action in response before the attackers get what they want.
Information technology will continue to evolve rapidly and cyber defense must evolve just as fast – if not faster – to stay ahead of risk. Each new technology is a two-edged sword, on one side full of promise and the other a potential vulnerability. Cyber is forcing a culture change and security technology has to evolve to keep up. The only sure thing in cyber is change itself. There can be no standing still. Threats are everywhere. We must be focused and dedicated to stay ahead.