By Mr. Zakir Hussain, CEO – BD Software Distribution As digital landscapes morph and expand, cybersecurity challenges intensify. The fusion of digital advancement, the adoption of hybrid workplaces, and the transition towards cloud-based operations are not only widening the threat horizons but also exposing them to heightened risks of disruptive attacks. Savvy to these shifts, cybercriminals are eschewing the old playbook in favour of more nuanced methods, bypassing many established security protocols. These adversaries are now adeptly weaving their malicious efforts into the evolving tapestry of communication channels, exploiting the vulnerabilities of these increasingly exposed digital terrains. Phishing is the number one attack vector today, using an organization’s biggest vulnerability—users—to make an initial breach on an end device, web application or Software as a Service (SaaS) platform. New threats are evolving from the ashes of previous campaigns, trying to get people to click on malicious links in an email or in-app message in an attempt to disrupt business operations. From there, they are able to spread freely across the network in search of more enticing targets. As cybersecurity techniques evolve, security teams find themselves in a reactive position, constantly adapting to stay abreast of threat actors who often seem to be a step ahead in exploiting vulnerabilities. This dynamic creates a perpetual cycle where defensive strategies are continuously updated to match the ever-advancing tactics of these adversaries.

The Limitations of Conventional Cybersecurity Approaches

Cybersecurity solutions of the past were crafted in a bygone digital era and persist in a landscape that has since dramatically evolved. They are rules-based and reactive, using known threat signatures to detect abnormal behaviour. Security analysts then must manually parse through mountains of alerts—much of them false positives—to determine what is important and figure out a resolution. Many times, this results in immense fatigue for these digital warriors. They become overwhelmed, unable to keep up with the manual, tedious tasks, and security postures degrade, making it easier for enterprising threat actors to find more vulnerabilities in the expanding threat surface—creating a never-ending snowball effect that keeps getting worse and worse. This disconnect has led to a major security gap that organizations need to address.

Implementing an Adaptive Cybersecurity Strategy

Adaptive cybersecurity continuously and automatically monitors growing attack surfaces to recognize threats, adapt in real-time, and provide actionable recommendations for fast, efficient, non-disruptive remediation. This new, proactive and preventative approach can be implemented and managed centrally with a network detect and response (NDR) or eXtended detection and response (XDR) solution, through a security operations centre (SOC) or from a managed XDR service provider. Whatever model you decide to go with, make sure it covers all three cybersecurity layers: prevention, protection, and response.

1. Prevention

Any prevention strategy needs to start with education. Users are organizations’ biggest vulnerabilities, so you can’t do enough training about maintaining good cyber hygiene. Make sure users know what constitutes risky behaviour and how their clicks can impact business operations. From a security team perspective, efficiency at scale is critical. Automating basic prevention tasks such as risk assessment goes a long way in preventing alert fatigue and security analyst burnout. It’s also important to focus on threats or vulnerabilities that impact your specific organization or industry. A data loss prevention (DLP) tool that has been trained to detect personal health care data isn’t very useful for a retailer, but a tool that identifies credit card information or other payment card information (PCI) would be.

2. Protection

Protection builds on a successful prevention strategy by maintaining good cybersecurity hygiene and cyber resilience. Tools such as anti-malware and email security protect devices, servers, or other endpoints from malicious threats. Just make sure your tools aren’t heuristic or signature-based solutions given the limitations these solutions are against today’s highly adaptive threats. Instead, use artificial intelligence and machine learning (AI/ML) in anomaly detection to identify and stop attempted breaches. Large language models (LLMs) can also be used to accelerate model training for industry or organization-specific contexts.

3. Response

All the prevention and protection in the world isn’t much use without actionable insights to remediate the issue and get operations back up and running quickly. A good strategy around response helps identify and correlate behaviour around expanding attack surfaces, providing valuable context that security analysts can use to stop the attack, mitigate the impact and prevent it from happening in the future. Again, automation is key. A solution that automatically resolves issues or provides an avenue for immediate action is better suited for shortening the time to resolution and mitigating business impact. To effectively combat these emerging threats, organizations must prioritize a multi-layered approach. This includes rigorous user education to enhance prevention, leveraging advanced tools for protection that go beyond signature-based solutions, and employing AI/ML technologies for anomaly detection. Response strategies should be agile and automated, providing swift action to remediate issues and minimize operational downtime. Disclaimer: The views and opinions expressed in this guest post are solely those of the author(s) and do not necessarily reflect the official policy or position of The Cyber Express. Any content provided by the author is of their opinion and is not intended to malign any religion, ethnic group, club, organization, company, individual, or anyone or anything.