Organisations need to adopt predictive and proactive threat detection software to counter cyber-attacks

As technology evolves, we often think of the benefits it can bring to organisations with new software and programmes being created to enhance society as a whole. But we often overlook the fact that these new, innovative products and systems are also available to those who want to do harm – specifically cybercriminals. In 2021, over a third (37%) of global organisations said they were a victim of some form of cyber-attack, according to IDC’s “2021 Ransomware Study”.


Cyber-attacks and data breaches are among the top risks faced by businesses in recent years. Furthermore, a new UK government report claims that most business leaders only prioritise cyber security after a major breach, noting that lots more still needs to be done to protect organisations up and down the country.


Challenges with the current software

No organisation wants to be a victim of a cyber-attack, with all having some sort of software in place to at least try and prevent an attack from occurring. Many currently rely on traditional reactive security monitoring software such as Security Information & Event Management (SIEM) solutions that offer aggregation and basic analysis of log data for detecting cyber incidents. 


However, most SIEM solutions only focus on the alert mechanisms to trigger once a previously known attack pattern has transpired. As a result, there are numerous challenges associated with this approach, leaving businesses open to new, unknown attacks. 


These challenges include:


1. A Dynamically Changing Threat Landscape

With technology evolving at a rapid pace, cybercriminals have access to the best software available. As a result, even the most advanced security software can now be bypassed. Legacy SIEM solutions cannot identify cybercriminals as they hide their activities in the hundreds of gigabytes of data collected from various log sources due to the software not being able to learn common user behaviour.


2. Excessive Alerts & False Positives

Traditional SIEM solutions have one major flaw – they generate too many alerts. With a large number of these alerts being false-positive triggers, it becomes difficult to pick up a true-positive alert in all the chaos. It is estimated that SOC analysts spend close to 25% of their time chasing erroneous alerts.


3. Deployment, Implementation & Scalability

Even with current technology, it can take up to a year or more from deployment to implementation to receive high-value alerts, which indicates that the effectiveness of a traditional SIEM solution is proportional to its architecture, algorithms, and maintenance.


4. High Data Volume, Insignificant Organisation-Wide Visibility

Organisations produce vast amounts of data globally and need technology capable of processing this data. Extracting security information is crucial for holistic threat detection. Legacy SIEM solutions are incapable of optimally integrating every data source used by their clients and therefore lack the overall visibility required for optimal threat detection.


So what can organisations do to limit the threat of cyber-attacks?


Utilising Predictive Threat Detection Software

Too many organisations are not adopting software that can identify complex cyber-attacks before they occur. However, with technology advancing at a remarkable pace in recent years, next-generation SIEM software that combines the power of artificial intelligence, machine learning and statistical modelling with a scalable architecture, can offer predictive cyber threat detection and user experience to customers – but how?


1. AI-Driven Predictive Cyber Threat Detection

With the right AI system in place, a next-generation SIEM solution can contextualise information to predict cyber threats, rather than just detecting them at the impact stage. Furthermore, multiple AI models can be used in sequence to optimise the threat detection output to detect early signs of a possible attack.


2. Enforced Learning Through Machine Learning

Traditional Security Operations Center (SOC) operations for many years have suffered from alert fatigue and a high rate of false positives, wasting a lot of analysts’ time during investigations. However, with reinforced machine learning feedback looping, false and true positives can be recorded and leveraged to influence future decision-making.


3. Native Contextual Cyber Threat Intelligence Integration

By integrating with automated data and web scrapers to incorporate the latest contextual threat intelligence for organisations, a next-gen SIEM solution can provide near real-time adjustment ability to reflect real exposure from vulnerabilities, compromised credentials, malicious domain spotting within the context, and risk exposure of any client. Additionally, alerts can be prioritised and adjusted based on the potential impact on the organisation, putting the most serious alerts at the top of the agenda.


4. Holistic Scenario-Focused Cyber Attack Detection

The implementation of AI means that threat detection software can look for commonalities or reference points between different events within organisations to form and identify a relationship between multiple kill chains. Rather than one single event, cyber-attacks consist of multiple events that occur in chronological order where time is a variable. Moreover, cybercriminals often spend years planning and actioning their attacks. This is a step forward from traditional tools that assume time as a constant and that attacks are orchestrated based on a fixed logic.


Conclusion: Adopting a Cost-Effective Next-Gen SIEM

Navigating through a challenging environment and adopting best practices can be overwhelming for business leaders. However, by adopting the correct threat detection solution, security teams can increase their ability to identify advanced multi-vector attacks against their environments. By doing this, organisations can protect their reputation, while ensuring no client or customer data is stolen.


Interested in adopting next-gen SIEM? Download our free guide today.


With organisations in constant fear of suffering a cyber-attack, next-gen SIEM threat detection software can play a pivotal role in ensuring peace of mind for business leaders. Organisations would be able to focus their attention away from the consequences of a cyber-attack, such as financial penalties or reputational impact, and use this time and money to focus elsewhere on the business, allowing them to expand their vision. 


About Blacklight AI Platform

Blacklight, our proprietary AI-based Security Operations Platform, helps you secure, monitor and detect beyond your traditional SIEM. Blacklight is architected, designed and built using industry best practices, offering the maximum level of flexibility and extensibility. 

Combined with SOC services, we provide the highest level of visibility into your organisation’s security for proactive monitoring. 

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