Cybersecurity race has no finishing point to define victory over it. The continuous evolvement of the cyber landscape keeps the standards out of reach of security agencies determined for the same. Each year the investment in cybersecurity surges from the previous one still agency are not able to have their intended returns. New technologies continue to find applications in the security environment for forging a robust security system to combat against the onslaughts. Still reports project that the myriad of cyber attacks continues to upswing, resulting in safeguarding strategies to lack behind.
Obstacles in the Roadmap
Businesses are migrating to mobile devices and cloud platforms, breaking the traditional perimeters for security agencies to operate on. Federal agencies hold the potential to safeguard the hard-wired networks only, but now are evolving from it to address the required real-time, ubiquitous, and evolving challenges in the vertical.
However, several security organizations fail to patch the gap as they embraced modern cyber tools without adequately analyzing their need and compatibility with their security model. Such pitfalls allow hackers to carry out malicious activities in the network.
Another could be considered roadblock is the need for human intervention to carry out effective safeguarding of the network. Adding to the hurdles, hackers are also on the move of applying cutting-edge technologies to breach in the security layers. As technology lacks morality, it is next to impossible to refrain its use in malicious jobs.
Role of AI and ML
Artificial intelligence already has firm grounds in the security landscape and continues to deepen its roots for security ameliorations. Federal agencies already have made AI tools an integral weapon of their arsenal. AI technology enables security frameworks to combat threats in real-time and automatically develop a strategy against the zero-day ones for the future. Algorithms can patch the security potholes easily without human intervention in real-time.
Machine learning—subset technology of AI—empowers organizations to harness its self-learning capability for completely automated cybersecurity framework. Developers strive to comprehend deep neural network decision making to develop algorithms accordingly. Once it’s accurately done, technology can replace human from the security framework management layer. The only drawback is, hackers can utilize the same technological advancement.