Security Agent Context Feedback for Threat Detection Decisions
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Solution Overview
Problem
Existing security systems lack sufficient context to effectively detect and respond to the growing variety of malicious activities, leading to inefficiencies in threat detection and potential false positives.
Innovation Solution
A security server collects and collates event reports from multiple computing devices to extract context information, which is used by a security agent to make informed decisions about protective actions based on historical data and organizational learning, enhancing behavioral threat protection and analytics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple layers of security apparatus and software are deployed to detect and repel security threats, then the detection capability against malicious software and network intrusions is improved, but the system complexity and resource consumption increase
Solution Approach 1:
A security server acts as an intermediary between multiple computing devices and security agents. The server collects event reports from devices, analyzes them centrally, and provides contextual information to agents. This intermediary approach consolidates complex analysis functions at the server level while keeping client-side agents relatively simple, resolving the contradiction between comprehensive security detection and system complexity.
Solution Approach 2:
The security server performs multiple functions including collecting event reports from various devices, analyzing events across the entire organization, generating contextual profiles, and distributing security guidance to multiple agents. This multi-functional centralized system improves overall security detection capability without requiring each individual device to implement complex security apparatus, thus addressing the contradiction between reliability and device complexity.
2Measurement precision
If security systems rely on limited local context information, then the response speed of security agents is maintained, but the accuracy of threat detection and decision-making deteriorates
Solution Approach 1:
The security server continuously collects event reports from computing devices, analyzes patterns, and feeds back contextual information to security agents. This feedback loop enables agents to make accurate threat detection decisions by incorporating organizational-wide context without sacrificing response speed, as the server pre-processes and distributes relevant contextual data proactively.
Solution Approach 2:
The security server performs preliminary analysis of event reports and generates contextual profiles in advance, before security agents need to make detection decisions. By pre-processing and distributing contextual information ahead of time, the system enables fast local decision-making with high accuracy, resolving the contradiction between response speed and detection accuracy.
3Reliability
If security agents make decisions based solely on local event data, then the operational speed is maintained, but the reliability of protective actions deteriorates due to insufficient context
Solution Approach 1:
The security server as an intermediary consolidates information gathering and analysis functions, collecting event reports from multiple devices and synthesizing organizational context centrally. This eliminates the need for individual agents to spend time gathering local context, as the server provides pre-synthesized contextual information, thereby improving protective action reliability without time loss.
Solution Approach 2:
The security server performs preliminary contextual analysis and generates security profiles in advance, distributing this prepared information to agents before they need to make protective decisions. This preliminary action ensures agents have reliable contextual information ready when needed, improving decision reliability without incurring time delays during critical security events.
Data Source
AI summary
A method, including collecting, by a security server, reports from multiple computing devices of events belonging to a set of specified event types occurring in execution of software processes on the devices, and collating the reports in the server to extract context information with respect to each of the events. Upon detecting an event occurring in execution of a process on a given device and matching one of the types, a software agent executing on the given device extracts, one or more features from the detected event, and conveys a query with respect to the detected event from the agent to the server. Upon receiving, from the server in response to the query, the context information with respect to the detected event, the agent decides to initiate a protective action on the given device based on the received context information and the one or more features extracted by the agent.