A data-driven approach to security orchestration can enable security leaders to swiftly make the right decisions and implement the appropriate measures, with the added benefit of minimizing the impact on their budget.
Incorporating security orchestration and automation capabilities in solution categories outside of SOAR platforms has been one of the most significant advancements in cybersecurity technology and tools over the past few years. Endpoint Detection and Response (EDR) solutions have expanded to include orchestration and automation capabilities to accelerate threat detection and response, while SIEM vendors have acquired standalone SOAR platforms.
Even though many use the terms orchestration and automation interchangeably, they are quite different. By automating processes, security activities can be carried out more effectively. Contrarily, orchestration aims to integrate many systems in the Security Operations Center (SOC) so that security teams can identify, address, and respond to threats across the enterprise infrastructure.
Flexible Path for Orchestration
To create layers of defense, most businesses have complex security infrastructures that are both on-premises and in the cloud. These infrastructures typically include IPS/IDS, firewalls, routers, email and web security, and Endpoint Detection and Response (EDR) solutions. They have SIEMs and other tools that store internal threat and event data, as well as a variety of external threat intelligence feeds and sources. An orchestration platform with an extensible, open architecture enables robust integration and interoperability with the current tools and new security measures to address evolving threats.
Data-Driven Decision Making
However, the financial ramifications of how some of the tools that organizations connect to are licensed become increasingly critical as more security teams follow the route of automation and integration. Businesses may be charged extra depending on how much storage they utilize and the more data they transfer to specific systems. Additionally, some of their services may follow a “pay by usage” strategy. Businesses may be granted a certain number of lookups each day, and each lookup deducts from the overall limitation. When that limit is reached, further charges are levied.
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Actions are taken based on events that aren’t relevant or high priority if companies are driving orchestration and automation with a process-driven approach without considering the data being analyzed. Few security teams consider the financial costs of keeping unneeded data on hand or frequently querying their systems without a valid reason.
Automation and orchestration should only be triggered on processes that are important to improve decision-making and help companies avoid these unforeseen financial repercussions.
Businesses can ensure they are using license capacity for events that actually matter by adopting a data-driven strategy, where they contextualize first to ensure each activity they are automating has value.
Security teams can access the depth of all available data to gain a complete picture of what is happening with the help of a platform that aggregates, normalizes, and connects internal and external data. This entails putting data into context by adding additional intelligence, including internal observations of network and file activities. With the knowledge that they aren’t making pointless requests or using unnecessary storage when they look for related artifacts in other tools across the organization, they can now pivot to external data sources to learn more about campaigns, competitors, and their Tactics, Techniques, and Procedures (TTP).
Security teams can orchestrate a comprehensive and coordinated response with the scope of malicious activity and all impacted systems identified and confirmed. They can perform the right actions across multiple systems and send associated data out to the right tools across their defensive grid immediately and automatically to accelerate the response. Blocking threats, updating policies, and addressing vulnerabilities happen faster. A data-driven strategy also leverages bi-directional integration to transfer data from the response to central storage for learning and development.
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