Cross-Platform Threat Detection Using Multi-Event Security Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional defense mechanisms for enterprise platforms are platform-specific and ineffective against novel security threats, allowing attackers to exploit gaps between different platforms used by employees.
Innovation Solution
A cross-platform security threat detection system that performs independent abnormality and risk analysis, ingesting and standardizing data from multiple platforms, enriching it with user-level and threat intelligence, and using machine learning to identify potential threats through multi-event analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If platform-specific defense mechanisms are used, then each platform can be defended individually, but security gaps exist between platforms that attackers can exploit
Solution Approach 1:
The patent combines multiple platform-specific security mechanisms into a unified cross-platform security system. The system ingests events from multiple platforms (email, messaging, cloud infrastructure, SaaS) and performs centralized analysis to detect security threats that span across platform boundaries, eliminating the gaps between siloed defenses.
Solution Approach 2:
The security system is designed to be universal across multiple platforms. It can ingest and analyze events from diverse platforms including email services, messaging applications, cloud infrastructure, and SaaS applications using a common analysis framework that performs abnormality detection and risk analysis regardless of the source platform.
2Ease of manufacture
If conventional platform-specific defense mechanisms are used, then implementation is simpler for each individual platform, but they are ineffective against novel cross-platform threats
Solution Approach 1:
The system performs preliminary abnormality analysis on individual events from each platform before conducting cross-platform risk analysis. This two-stage approach allows the system to pre-process and flag suspicious events using platform-agnostic criteria, then correlate them across platforms to detect novel threats that single-platform mechanisms would miss.
3Measurement precision
If data from multiple platforms is ingested and analyzed, then cross-platform threat detection accuracy improves, but system complexity increases
Solution Approach 1:
The system segments the threat detection process into distinct modules: event ingestion from multiple platforms, standardization of events to a common format, abnormality analysis of individual events, risk analysis correlating events across platforms, and threat detection. This segmentation allows each module to handle specific tasks independently, managing complexity while achieving accurate cross-platform threat detection.
Solution Approach 2:
The system introduces an intermediary layer that standardizes events from different platforms into a common format before analysis. This intermediary standardization layer translates platform-specific event structures into a unified representation, enabling cross-platform correlation without requiring complex platform-specific handling logic throughout the entire system.
Data Source
AI summary
In various embodiments, a process for cross-platform security threat detection includes determining that a specific event in a plurality of events from a plurality of different digital service platforms meets a criterion for multievent analysis. The process includes identifying, among the plurality of events, a group of cross-platform events related to the specific event; and analyzing at least the group of cross-platform events to detect a potential security threat. The process includes providing a security threat analysis result associated with the identified group of cross-platform events.