As the world’s technology continues to rapidly advance over time, it’s clear that the reliance upon cyberspace will increase as well. This has given rise to progressively complex cyber threats across the information processing realm – becoming increasingly more serious and frequent to every industry (40% increase in reported data breaches and incidents) – and government bodies are no exception. Implementing cybersecurity measures is a constant challenge as threats rapidly evolve, expand, and become more customized. It is now common for attacks to persist undetected, and slowly gain control of critical assets – requiring organizations to continuously monitor internal and external security threats.
With the explosion of data (50% annual growth), devices and connections in the world today, cybersecurity monitoring has become even more challenging due to the overwhelming amount of information needing to be analyzed. Many attacks are sophisticated (Advanced Persistent Threats) and detected only after a deviation from normal behavior has been identified – with the intrusion already having deeply infiltrated critical information systems for an extended period of time. As a result, organizations must evolve their approach to cybersecurity: moving from traditional reactive detection methods (defensive measures) to prediction of potential threats.
In combating the sophisticated landscape of today’s cyber threats, leading organizations have turned to analytics (real-time data correlation, pattern identification, etc.) to improve protection. For example, IBM’s Identity Resolution technology provides unique capabilities to government organizations in order to quickly discover the source behind unauthorized transactions – in real time. By delivering an instrumented approach (underpinned with advanced data analytics), clients are able to proactively detect and prevent threats. Further, the sharing of information (on a real-time basis) across the various levels of government significantly improves the effectiveness of cyber security programs, primarily as a result of the robust data repository able to be federated across the enterprise.
However, the complexity of security threats does not remain static. As the proliferation of data and devices continue to accelerate over time, current security techniques will not keep pace with the velocity and variety of future threats. More advanced capabilities and approaches will be required to protect against the most sophisticated cyber threats – with cognitive computing, such asIBM Watson, being a cornerstone technology.
Learn through this video that how IBM security solutions are helping government organizations to address security concerns:
Cognitive systems can help predict and prevent emerging and undocumented threats by uniquely utilizing both supervised and unsupervised machine learning techniques. Dynamically-adapting predictive models analyze data in real-time and provide insight into previously-hidden patterns (anomalous behavior) – anticipating changes to the cyber landscape in order to identify and disrupt unknown threats as they occur. So while no single technology or approach to cybersecurity will universally protect against all (current and future) threats, organizations need to put a high priority on the continuous transformation of their security environment – and the use of cognitive technologies is key to a successful path forward.
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