Chief information officers (CIOs) and chief information security officers (CISOs) face tough decisions every day. They understand that harnessing and interpreting data insights are key to any effective cybersecurity strategy.
However, the task has become increasingly complex owing to the sheer volume and diversity of disparate data. Traditional security information and event management (SIEM) tools struggle to keep up, often demanding significant costs for increased data ingestion while relying on operationally laborious threat-detection capabilities.
“Some legacy systems have been in this space for years and have become a core component of security operations. They’re very much embedded within processes that the teams are currently operating on,” explains Randeep Gill, senior security strategist at Gurucul. “But they were not designed to cope with the realities of today’s cyber-threat landscape, IT complexity, evolving regulations and data-sovereignty requirements. Nor were they built to handle the sheer volume of data organisations now face.”
Getting real value out of these tools has traditionally been a huge challenge and security teams have been disappointed by false promises
Security leaders are forced to make difficult choices about data prioritisation, resulting in either blind spots or unsustainable costs. “It’s the lesser of two evils – you either pay a premium or accept a greater level of vulnerability,” says Gill. This data security dilemma is not new. However, it is becoming harder to justify a decision to stick with legacy systems.
Indeed, research from 2021 found that half of security professionals were dissatisfied with their SIEM solutions, with 40% citing excessive costs and more having concerns over scalability and data management. This issue is compounded by the rapid growth in data generation – it is estimated that 90% of the world’s data was generated in the last two years.
Legacy SIEM providers have attempted to keep up with the demands of modern organisations. But these often result in a patchwork of technology acquisitions or partnerships, which serve only as a band-aid to the problem and remain difficult to use and costly to run.
But what if organisations could reduce risks and costs simultaneously? Modern security-analytics platforms are doing precisely that, in a paradigm shift that addresses the limitations of traditional SIEM solutions and establishes the future of security operations
Out with the old, in with the new
A new generation of security-analytics platforms address the challenges of the data dilemma facing security leaders. These big-data platforms leverage advanced machine learning (ML) models, artificial intelligence and automation to effectively and affordably gain complete visibility to detect and respond to real threats. They accomplish this in two ways.
The first is native data-pipeline management. This enables teams to accommodate large volumes of data from various sources, preparing it for analytics while also ensuring complete control over data residency. These modules filter non-critical data and direct them to low-cost storage, resulting in cost savings while allowing federated search from within the platform. They also enrich and normalise critical data for analytics readiness.
The second method is advanced analytics. This reduces false positives while streamlining investigation and response efforts by leveraging advanced behaviour-focused ML models. By centralising all relevant data, these ML models put anomalies into context to prioritise and escalate the most risky user and entity behaviour.
But the benefits go beyond cost and risk reduction. They also address the growing complexity and lack of visibility that has plagued many organisations.
Many security teams have invested in a patchwork of tools over the years to address the increasingly sophisticated threat landscape. But this only increases complexity and creates data silos that hinder visibility across the IT environment. This produces a deluge of incomplete alerts, resulting in false positives, which require manual and cumbersome investigations across various tools to validate.
“Getting real value out of these tools has traditionally been a huge challenge and security teams have been scorned by false promises,” says Phil Close, VP of Europe at Gurucul. “To reap the true value of these legacy systems, you have to spend an inordinate amount of time managing, maintaining and navigating across platforms. It’s time these teams don’t have.”
When approaching a security operations modernisation initiative, beyond selecting the right platform, security leaders must ask some critical questions: what does our current cybersecurity framework look like? How are we assessing risk in the context of our environment? How are we measuring the effectiveness of our tools and security posture? Where are our blind spots and what data collection is necessary to illuminate them? Even with the best tools in the world, unless leaders understand the risk in the organisation, they’re going to fall at the first hurdle.
“The security-operations centre needs a single source of truth, where all insights should reside. Your analytics shouldn’t be running from disparate components within your organisation,” says Close.
Eliminate the risk of doing nothing
It’s important for security leaders to ensure their SIEM is capable of handling risks in a way that is cost-effective and manageable without sacrificing security. Ultimately, those security leaders must consider the cost of inaction.
That’s because many times leaders will know the technology isn’t fulfilling their organisation’s needs, but they are reluctant to act out of fear that any new investment might be too risky or will just add more costs and complexity to their operations. But reducing cost no longer means increasing risk. The next generation of SIEM solutions can address an organisation’s commercial and operational costs without compromising security.
Gurucul’s Reveal security analytics platform is designed for agility, flexibility and scalability. Powered by advanced ML and AI, Reveal delivers high-fidelity threat detection and risk prioritisation in real time, cutting investigation times by 50% and eliminating false positives.
Moreover, Reveal offers substantial SIEM cost savings, typically exceeding 40% in reduced data costs compared with traditional SIEM. In essence, next-generation platforms such as Gurucul Reveal can remove those barriers to action.
As organisations navigate the evolving threat landscape and grapple with the limitations of their existing security tools, the time has come to embrace a new era of security analytics. By leveraging the capabilities of modern platforms, CIOs and CISOs can reduce costs, mitigate risks, minimise complexity while maximising analyst output and gain the comprehensive visibility they need to protect their organisations effectively.
For more information please visit gurucul.com
Chief information officers (CIOs) and chief information security officers (CISOs) face tough decisions every day. They understand that harnessing and interpreting data insights are key to any effective cybersecurity strategy.
However, the task has become increasingly complex owing to the sheer volume and diversity of disparate data. Traditional security information and event management (SIEM) tools struggle to keep up, often demanding significant costs for increased data ingestion while relying on operationally laborious threat-detection capabilities.
“Some legacy systems have been in this space for years and have become a core component of security operations. They’re very much embedded within processes that the teams are currently operating on,” explains Randeep Gill, senior security strategist at Gurucul. “But they were not designed to cope with the realities of today’s cyber-threat landscape, IT complexity, evolving regulations and data-sovereignty requirements. Nor were they built to handle the sheer volume of data organisations now face.”
