Threat Detection System Using Multi-Source Web Data Acquisition
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Solution Overview
Problem
Conventional threat detection systems are limited in acquiring data from the deep web and lack efficiency due to restricted data acquisition capabilities, which impede effective threat detection.
Innovation Solution
A system and method that includes a processing subsystem with a reconnaissance module to acquire data from internal and external sources, such as firewalls, routers, security solutions, deep web, dark web, and surface web, using threat analysis methods like correlation, behavioral, and contextual analysis, and presents detected threats in various forms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional systems are used for threat detection, then the system complexity is low, but the data acquisition capability is limited and cannot access deep web data
Solution Approach 1:
The system is divided into multiple specialized modules: deep web crawler module, surface web crawler module, data acquisition module, data processing module, and threat detection module. Each module handles specific tasks, allowing the system to access both deep web and surface web data while maintaining manageable complexity through functional segmentation.
Solution Approach 2:
The system integrates multiple web crawling capabilities (deep web and surface web) into a single unified platform that can acquire data from diverse sources simultaneously. This multi-functional approach enables comprehensive threat detection by combining data from different web layers without requiring separate systems.
2Adaptability or versatility
If newer systems with advanced crawlers are used to acquire deep web data, then the data acquisition capability improves, but the system complexity increases due to additional security protocols
Solution Approach 1:
The system employs proxy servers and anonymization techniques as intermediaries between the crawler and deep web resources. These intermediaries handle the complex security protocols and anonymity requirements, shielding the core system from complexity while enabling deep web access.
Solution Approach 2:
The system creates multiple instances of crawlers with different configurations and identities to access deep web resources. By using copied crawler instances with varied parameters, the system maintains anonymity and bypasses security restrictions without requiring a single overly complex security infrastructure.
3Productivity
If data acquisition is limited to single source (deep web or internal source), then the system complexity is reduced, but the threat detection efficiency decreases
Solution Approach 1:
The system merges data from multiple sources including deep web, surface web, and internal organizational sources into a unified data processing pipeline. By combining these diverse data streams, the system achieves comprehensive threat detection while using integrated processing logic to manage the complexity of multi-source data handling.
Solution Approach 2:
The data processing module is designed to handle multiple data types and sources through a universal processing framework. This multi-functional capability allows the system to process deep web data, surface web data, and internal data sources using the same core algorithms, improving threat detection efficiency without proportionally increasing complexity.
Data Source
AI summary
System and method for data analysis and detection of threat are provided. The system includes a processing subsystem. The processing subsystem includes a reconnaissance module configured to acquire data from one or more internal sources and one or more external sources. The data from the one or more internal sources includes the data from at least one of a firewall, a router and a security solution. The data from the one or more external sources includes the data from at least one of a deep web, a dark web and a surface web. The processing subsystem also includes an analysis module configured to analyse the data by using at least one threat analysis method for detection of threat and a dissemination module configured to present detected threat in one or more forms. The system also includes a memory configured to store data acquired from the one or more sources.