Transitioning to Next Gen SIEM: The Future of Cyber Threat Detection
Cyber threat detection has changed and continues to change as the threat landscape evolves. Detection that is solely based on threat identities no longer works given the prevalence of sophisticated zero-day attacks. Similarly, rules-based detection is no longer as effective as it was before. Cybercriminals can rapidly produce new malware or tweak their attacks to evade detection.
The good news is that most organizations appear to be willing to improve their cybersecurity, particularly through cumulative investments and C-suite collaboration. As PwC’s 2023 Global Digital Insights report shows, there is an appetite for improving cybersecurity. Senior executives acknowledge the rise in cyber threats their organizations are not fully ready to address. Also, most CISOs admit that they still need to progress further when it comes to their ability to detect, identify, and respond to cyber attacks as well as in establishing protective and recovery measures.
One area where cybersecurity improvement is urgently needed is security information and event management (SIEM), as it no longer has the efficacy in dealing with new kinds of attacks. There is a need to transition to a better way of undertaking SIEM to keep up with the growing aggressiveness and sophistication of threats.
The need for next gen SIEM
Nearly two decades after its introduction, legacy SIEM’s successor is already being used by many organizations. Next gen SIEM is significant upgrade that addresses almost all of the flaws of its predecessor.
Veering away from heavily relying on threat identity and rules-based detection, the new generation of SIEM takes advantage of new technologies to detect and mitigate threats. The effectiveness of signature-based threat detection has steadily eroded as threats became more complex, rapidly evolving, and aggressive. Next gen SIEM now uses behavioral analysis and other related security technologies to spot and stop potentially anomalous actions.
Additionally, conventional SIEM is unable to keep up with the pace of attacks because of its heavy reliance on manual analysis and response. It is not unusual for cybersecurity teams to fail to detect and respond to certain threats because of the sheer volume of data and incidents they are dealing with. Delays in detection and response allow attackers more opportunities to penetrate defenses, explore more vulnerabilities, or inflict more damage.
Another issue with conventional SIEM is the high occurrence of either false positives or false negatives. Its threat detection capabilities tend to be less accurate than desired because of the other weaknesses mentioned above. It can be too sensitive that it flags data or instances that are not really anomalous or harmful. This is a problem because it needlessly pads up the incident response queue, resulting in security alert fatigue and taking up time that could have been used to address real threats. On the other hand, false negatives or the failure to detect threats create a false sense of protection, which is also a bane for cybersecurity.
Moreover, scalability is a concern for legacy SIEM. It is not designed to handle the enormous amounts of data and highly complex networks modern organizations deal with on a regular basis. It is not suitable for the evolving infrastructure, varied data formats and sources, and different network setups of organizations at present.
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New capabilities to address new and emerging needs
Next generation SIEM solutions are built to address the limitations of traditional security information and event management, but how exactly does it do it? There are four keywords to succinctly answer this question: automation, integration, real-time monitoring and response, and advanced analytics.
Legacy SIEM had some parts of it automated. However, its level of automation has not been enough to respond to the kind of threats organizations have been encountering recently. For this, next gen SIEM employs extensive automation and orchestration to cut process times significantly and enable quicker event detection, isolation, mitigation, and remediation. It can also streamline response workflows to reduce opportunities for reconnaissance, vulnerability exploitation, and attacks to as little as possible.
Integration is also a key feature of next gen SIEM, as it expands its security data and attack surface coverage to areas not covered by legacy SIEM. It can integrate internal, external, and other sources of threat intelligence. It can also correlate data from various sources to gain a comprehensive grasp of the threat situation. This considerably reduces the number of false positives and negatives and facilitates faster detection and response.
Another key nex gen SIEM capability is real-time monitoring and response. It can radically reduce response latency by instituting real-time monitoring of security data and events. This supports proactive threat hunting and much faster response to security incidents.
Also notably, NG SIEM harnesses artificial intelligence to perform advanced analytics and enable more accurate threat detection without over-relying on threat intelligence and cybersecurity frameworks. It can have its own way of detecting threats by analyzing user behaviors. SIEM can integrate machine learning to go over vast amounts of data related to an IT network or infrastructure and establish benchmarks of safe or regular activity.
These benchmarks serve as a basis for spotting potentially harmful or malicious actions not only by external actors but also insiders. Advanced behavioral analytics powered by machine learning allows next gen SIEM to detect and prevent both known and unknown attacks.
The future of cyber threat detection
The future of cyber threat generation is changing. It will always have to change in response to the neverending changes in the cyber threat landscape. New technologies are bound to provide new benefits and create new challenges in the process. As such, it is vital to continuously change to address issues that are beyond the capabilities of previous security solutions.
SIEM can achieve enhanced detection accuracy, improved response times, flexibility, and scalability by integrating new technologies and enhancing its detection and response mechanisms. New technologies, particularly artificial intelligence, can be integrated to bolster detection and response effectiveness.
Cybercriminals will stop at nothing to find and exploit new vulnerabilities and defeat existing security controls. It is incumbent upon cybersecurity teams to discover or develop new methods, strategies, or tools to address emergent threats while also utilizing proven-effective solutions and observing best practices.
Effective cyber threat detection is not dependent on a single solution or technology. It has to integrate various tools, strategies, methods, platforms, frameworks, and other components to support a formidable security posture. All of these entail an openness to change and the adoption of new tools or solutions in response to new threats.
SIEM: Revitalized and Improved
Despite the declaration of some cybersecurity pundits that SIEM is dead, it can be argued that it continues to be relevant. Not in its original or traditional form and operation, though. The core idea of conducting SIEM continues to be relevant because organizations will always need a way to manage all of their security data and incidents. Hence, there is a need to transition to a better iteration of SIEM and keep up with the latest when it comes to cyber threat detection.