What could go wrong if you don’t protect your data and how to get it right

By Brian Landa, Financial Services Industry - Business Consulting Lead at Think Big Analytics (a Teradata company)

As a new era of the data revolution unfolds, the organisations that will thrive and successfully transform will be those that can identify and take advantage of data to derive meaningful insights into human behaviour. However, given the increased security risks that come with new and emerging technologies, businesses must be prepared to protect this valuable asset.

An IDC whitepaper released last year revealed that, by 2025, the global datasphere will grow to 163 zettabytes (or 163 trillion gigabytes). All this data will unlock unique user experiences and a new world of business opportunities.

But as this data and its value increases, so do the threats of a data breach. With cyberattacks increasing at unprecedented rates, it’s become clear that industry and government organisations need to do more to safeguard sensitive data, as well as their own reputations.

The exponential growth of data has created significant new cybersecurity risks. In essence, online attackers have a bigger digital forest to hide in, whether their goal is covert data exfiltration, unauthorised file sharing, or phishing expeditions to dupe unwary users into opening malicious files.

Conventional approaches to cyber security are largely reactive and, many times, disparate. The result is that it takes too long from the time of intrusion to remediation, allowing unnecessary and debilitating economic and reputational harm. Fortunately, big data and emerging security technology solutions are a powerful way to handle the volume and complexity of cyberattack detection and prevention, letting organisations stay ahead of evolving threats.

Older, layered defense strategies generate large volumes of false-positive alerts, overwhelming security professionals. Traditional cybersecurity tools cannot effectively process large volumes of data, resulting in missed signals that should trigger real threat alerts. Bad actors remain undetected, hiding in plain sight on an organisation’s network. Businesses need an advanced, strategic approach to network security that disrupts adversary tools and techniques, rendering them ineffective.

Traditional thinking suggests that network data volumes are too large; therefore, the analysis needed to mitigate cyberthreats is too complex and time consuming to be cost effective. However, today’s integrated analytic solutions help organisations leverage structured data and big data to build formidable defenses against cybersecurity threats.

Specific tools exist to help organisations predict and prevent external threats. Most organisations have systems that help secure networks or monitor traffic to prevent an attack. Big data algorithms and machine learning tools take this prevention a step further, letting organisations collect and analyse massive amounts of data to predict threats.

There are three steps organisations should take to maximise the use of big data to improve security:

  • Conduct a cyber risk assessment. The first step in integrating big data analytics for security is to complete a cyber risk assessment of the organisation’s data and network assets to identify the most critical systems to protect. There are a variety of frameworks that should be included in the assessment. The frameworks identify: organisational objectives; the processes involved in accomplishing those objectives; risks that could prevent their successful execution; controls to manage or prevent risk; testing to ensure the controls are effective; and reassessment.
  • Develop a roadmap for prioritising actions. After completing the security risk assessment, the strengths and weaknesses of the legacy cyberdefences should be catalogued, quantified, and used to develop a roadmap for prioritising actions. This is a crucial step for addressing and aligning the information security risk with the overall risk tolerance of the organisation.
  • Optimise effectiveness of existing security solutions. Introducing integrated security data and big data analytics can significantly improve the efficiency and effectiveness of existing security solutions as well as the personnel that operate them.

A comprehensive data architecture to combat cyberthreats must leverage existing, new, and emerging technologies to gain visibility into broad network activity, identify intelligent signals, and establish a strong defence posture. Ultimately, the goal is to evolve the security approach to next-generation threat detection. By capturing and visualising precisely what’s happening on networks as events occur, organisations can correlate activity through its network data elements as they are generated from each application, transaction, communication, or transmission.

 

 

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