How XDR Extends Your Security Capabilities

Endpoint detection and response (EDR) has evolved: extended detection and response (XDR) takes a more holistic, streamlined approach to threat detection and response.

XDR combines data ingestion, analysis, and prevention and remediation processes across your entire security stack, providing your IT teams with the necessary visibility to detect threats as well as automate workflows.

Eliminate Security Siloes

XDR pulls data from endpoints, cloud workloads, networks and email and then correlates and analyzes it using advanced automation and artificial intelligence (AI), which allows it to prioritize data and deliver insight through a single pane of glass.

Not only does XDR consolidate data from disparate sources, but it also coordinates siloed security tools so that your IT team doesn’t have to spread their attention across different consoles to conduct their security analysis, investigation and remediation.

XDR can help you reduce vendor sprawl while integrating the tools you do have to gain better visibility into your environment, whether it’s a private cloud or hybrid environment, including your public cloud instances. By coupling this integration with automation, XDR helps you respond faster to security incidents and effectively mitigate them to reduce the impact of any attack.

Like many security platforms, XDR can be purchased as a managed service, which opens access to expertise in threat hunting, intelligence, and analytics via a managed services provider.

Combine XDR with SIEM and SOAR

XDR doesn’t replace Security Information and Event Management (SIEM) or security orchestration, automation, and response (SOAR).

SIEM gives you a single, streamlined view of your data along with your operational capabilities and security at activities to you can better detect, investigate, and mitigate threats by ingesting as much data as possible. It gives you the ability to analyze data from network applications and hardware, and cloud and software-as-a-service (SaaS) solutions.

SOAR software manages threats and vulnerabilities, responds to security incidents, and automates security operations. The aim of SOAR is to collect as much data as possible and automate as much as possible by leveraging machine learning technology.

SIEM is primarily a log collection tool intended to support compliance, data storage and analysis –security analytics capabilities tend to be bolted on. SOAR incorporates orchestration, automation, and response capabilities to the SIEM and enables disparate security tools to coordinate with one another, but it doesn’t solve the big data analytics challenge, and it can’t protect data or systems on its own.

XDR fills the gap left by SIEM and SOAR by taking a different approach that’s based on endpoint data and optimization and applying advanced analysis capabilities that allow you to focus on high priority events and respond rapidly.

SIEM and SOAR are complementary and can’t be fully replaced by XDR. SIEM has other uses outside of threat detection, including compliance, log management and non-threat related data analysis and management. XDR can’t replace SOAR’s orchestration capabilities.

Assess, Protect and Respond

Adopting an XDR platform in combination with SIEM and SORA provides better threat visibility, optimizes and automates security operations, and enables your busy IT teams to focus strategic objectives rather than being bogged down by manual security tasks. A managed services provider can help you implement XDR along with SIEM and SOAR so you’re in a better position to assess and protect your data and respond quickly and effectively to cybersecurity threats.

There are many ways artificial intelligence (AI) and machine learning already impact cybersecurity. You can expect that trend to continue in 2024 – both as tools for data protection as well as a threat.

Balancing Cybersecurity Innovation Amid Evolving Threat Landscapes

Even as you implement AI and machine learning into your cybersecurity strategy through the adoption of tools like Security Orchestration, Automation, and Response (SOAR), Security Information and Event Management (SIEM) and Managed Detection and Response (MDR), so are threat actors. They will continue to update and evolve their own methodologies and tools to compromise their targets by applying AI and machine learning to how they use ransomware, malware and deepfakes.

With small and medium-sized businesses just much at risk as their large enterprise counterparts, SMBs must take advantage of AI and machine learning as mush possible. AI-directed attacks are expected to rise in 2024 in the form of deepfake technologies that make phishing and impersonation more effective, as well as evolving ransomware and malware.

Deepfake social engineering techniques

Deepfake technologies that leverage AI are especially worrisome, as they can create fake content that spurs employees and organizations to work against their best interests. Hackers can use deepfakes to create massive changes with serious financial consequences, including altering stock prices.

Deepfake social engineering techniques will only improve with the use of AI, increasing the likelihood of data breaches through unauthorized access to systems and more authentic looking phishing messages that are more personalized, and hence, more effective.

Countering Cyber Threats and Harnessing Innovation in 2024

If hackers are keen on leveraging AI and machine learning to defeat your cybersecurity, you must be ready to combat them in equal measure – just as AI and machine learning will create new challenges in 2024, they can also help you bolster your cybersecurity. While regulations are being developed to foster ethical use of AI, threat actors are not likely to follow them.

AI will also affect your cyber insurance as your providers will use it to assess your resilience against cyberattacks and adjust your premium payments accordingly. AI presents an opportunity for you to improve your cybersecurity to keep those insurance costs under control.

Conclusion

There’s a lot of doom being predicted around the growing use of AI and machine learning. And while it does pose a risk to your organization and its sensitive data, you can use it to bolster your cybersecurity even as threat actors leverage AI to up the ante. A managed service provider with a focus on security can help you use AI and machine learning to protect your organization as we head into 2024.

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