For too long, cybersecurity has been reactive, rather panicked response to an inevitable breach. However, the enterprise attack surface is massive and continuing to grow and evolve rapidly.
‘It is estimated that cybercrime will cost businesses worldwide $10.5 trillion annually by 2025- CyberSecurity Ventures Report.’
Organizations are under intense pressure to get their data protection and security rights. Thus, it’s understandable that organizations want to take a proactive approach against threats in order to create an environment of continuous compliance.
What are the key challenges for security managers?
Life has never been easy for security teams. Unfortunately, things are only getting harder with new challenges popping up. Here are the 5 key challenges faced by security managers…
- Rising volume & sophistication of cyber attacks
- The explosive growth in endpoints
- The digital-physical convergence
- Ensuring business continuity
- The widening skills gap
Keeping these challenges in mind, today’s security teams have to come up with new tactics to fend off the advanced threats being leveled against their increasingly interconnected enterprise networks.
An intelligence-led cybersecurity approach
The biggest hurdle in managing cyber-security risks is probably the speed of the cyber-attacks and the amount of data and its inter-dependencies that must be analyzed in order to be able to respond in real-time. Taking an intelligence-led security approach holds the key.
An intelligence-led security approach is a shift away from event-driven cybersecurity, wherein you embrace insights and intelligence to be proactive instead of being reactive to cyber-attacks by raising awareness of the threats before an attack. In this approach, the cybersecurity team works on the assumption that you are already under attack. The process should be as automated as possible to derive the maximum benefit.
Intelligent cybersecurity management is primarily based on Artificial Intelligence (AI) and Machine Learning (ML) including neural network-based deep learning. It applies various AI and ML methods that eventually seek intelligent decision-making in cyber applications or services.
Curating threat intelligence from millions of research papers and articles, AI technologies and natural language processing provide quick insights to cut through the noise of daily alerts, thereby considerably reducing the response time. Nourishing intelligence into a security operations center (SOC) can drive threat detection and response more aggressively.
Stay predictive and proactive
Innovation and digitization will continue to grow at an exponential pace. The traditional cybersecurity approach is to attack the problem and solve it. However, with the increasing adoption of digital, you can’t do something once and hope that you’ll be safe forever. Risk management and resolution must be ongoing. Managing security in the digital world involves the gathering, synthesis, and analysis of security data as standard. It’s no longer just about the data, but what the data can tell us in order to be predictive and proactive. An intelligence-led cybersecurity approach will not only ensure safety and business continuity but also help you gain a competitive advantage.