The recent large-scale cyberattacks have shown that any organization, regardless of size or industry, may be targeted at any time. Despite deploying multiple tools, security teams struggle to pinpoint relevant threats, wasting time sifting through incoming data and false positives and cannot act swiftly to real threats facing their business.
A recent Dark Reading study revealed that while many organizations have improved their threat detection capabilities over the last few years, they lack threat visibility and are still reliant on too many manual processes. These shortcomings in combating cyber threats result in alert fatigue, smoldering fires, and siloed threat intelligence.
The question then becomes:
“How can my organization optimize its threat detection system?”
Threat Detection as Process
There are multiple ways to detect a potential threat. These can include global threat intelligence, human expertise in threat identification, and advanced tools for identifying malicious activity. While all are essential elements, they need to working effectively to create an optimized security program. Too often, the security process goes in one direction, from threat intelligence gathering to analysis and monitoring by the security operations center (SOC) and then on to security engineering to prioritize remediation.
Creating a collaborative system with feedback loops between security teams and other key stakeholders is a much more effective way to avoid siloed intelligence and rapidly identify relevant threats. In this security ecosystem approach, the threat intel team automates intelligence gathering, prioritizes against intelligence initiatives, and incorporates any new requirements coming from security engineering. The SOC then monitors and prioritizes the continually updating threat requirements to help the threat team find relevant attacks. Security engineering prioritizes remediation and then feeds the revised intelligence requirements back to the SOC, reflecting any changes in vulnerabilities.
Intelligence-Powered Threat Detection
Implementing an effective collaborative system with two-way fluid communication requires intelligence-powered threat detection. Detection enables intelligent orchestration through your security organization and ensures that the global intelligence is relevant. Machine learning is leveraged to make sure severity scoring is conducted quickly and effectively. An intelligence-driven platform can process millions of indicators of compromise (IoCs) and billions of internal log entries, operationalizing threat data and automatically showing security teams what is relevant to them and which data are actionable intelligence. The identified indicators of interest can then be fed directly to the endpoints and firewalls for blocking.
Extended Detection and Response or XDR
Extended detection and response or XDR is a security framework that unifies threat detection and response into a single platform. It collects and correlates data automatically from disparate security components installed in a customer's environment. XDR can provide better security than isolated tools by reducing the complexity of security configuration and incident response.
For example, you can extinguish smoldering fires using XDR, as big data support on the backend enables quick indexing and searches going back years. Alert fatigue is relieved by the automated updating of IRs and allowing threat intelligence teams to focus on relevant IoCs. And, because it bridges different tools and systems, XDR can also facilitate feedback loops between cybersecurity teams and stakeholders.
Vendor-agnostic XDR platforms weave together vendor security tools and infrastructure silos, providing cohesive response capabilities. This cohesiveness is crucial, as most organizations have different vendors at the network, the endpoint, or identity management. A threat detection tool that integrates with legacy solutions will provide an integrated response, saving time and increasing efficacy.
Threat Detection Capabilities
With an intelligence-powered security process in place that provides continual feedback, various threat detection capabilities can be used to uncover previously unknown security threats.
Big Data Analytics – With big data analytics, organizations can capture current and historical event logs, asset data, IOCs, and active threat intelligence to transform billions of alerts into one decisive verdict. With access to integrated security telemetry (including SIEM, EDR, messaging apps, network data, etc.) along with layered threat detection from across the organization, relevant threats can be pinpointed to provide analysts with the actionable intelligence required to investigate the root cause or precise confirmation of an attack, to respond immediately.
User Behavior Analytics – Leveraging machine learning, user behavior is analyzed to develop a baseline of normal behavior. This process allows outliers to be identified for investigation, finding any bread crumbs of activity that a threat actor may leave behind.
Deception Technology – Honeypots, honey tokens, and credential lures are popular deception technologies used to trap attackers. When the bait is taken, an alert is generated, and the security team can investigate.
MITRE ATT&CK Framework – Map threat detections to the Mitre ATT&CK framework to help you understand—and stay ahead of—adversaries. This global knowledge base provides understanding for threats across their entire lifecycle. The framework is differentiated by focusing on tactics, techniques, and procedures (TTPs) that threat actors use to operate in the real world, rather than just on typical indicators like IP addresses, file hashes, registry keys, and so on. MITRE ATT&CK offers a rigorous and holistic method for understanding the types of adversaries operating in the wild and their most observed behaviors and defining and classifying those behaviors with a common taxonomy. This is an advantage that brings a much-needed level of organization to the chaotic threat landscape organizations face.
Threat Hunting – To root out advanced threats that have already penetrated the network and are lurking, as yet undetected, a threat hunt can be a helpful technique. Hunts are executed using various methods, such as:
Matching new tactics, techniques, and procedures (TTPs) with behaviors in an organization's environment
Using tactical threat intelligence to catalog known IoCs and indicators of attack (IoAs) and uncovering hidden attacks or ongoing malicious behaviors
Robust data analysis and machine learning are used to detect abnormal behaviors that could be signs of stealthy threats.
Optimizing Threat Detection
While no threat detection system is unassailable, utilizing the right combination of technology and human expertise can help create an advanced threat protection system that is both thorough and flexible. Critical components of an effective security program include continual feedback between teams, intelligence-powered detection, and a cohesive technology platform.
Read The State of Threat Detection whitepaper to learn more about the tools enterprises use to assess their threat detection capabilities and identify the challenges that could be hindering their success rate.
Watch the Intelligence Power Threat Detection video and come away with a deeper understanding of how to mitigate cybersecurity risk through threat detection.
Topics:Cyber Threat Intelligence