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Build a dual system security framework of zero trust inference and trusted inference.
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Intelligent Intranet Threat Analysis System

Comprehensive big data mechanism | Rich pre-defined analysis rules | Vertical analysis technology | Visual analytic modeling

Demand Background

Global APT attack activities remain highly active, the publicly disclosed attack activities involve APT organizations 141 in the worldwide, and this number is still growing. The attack targets are concentrated in government, education, finance, scientific research and other important national industry sectors. At the same time, according to the relevant organizations of the internal threat survey report shows that 90% of enterprises believe that their internal is easy to be attacked, 53% of enterprises have been attacked less than 5 times in 12 months, 47% of the attacks are from the internal failure of the host of the malicious operation. It is obvious that the current situation of intranet threat is serious.

Activity & Announcement

TopITA Introduction

Topsec Intelligent Intranet Threat Analysis System is based on big data architecture and adopts artificial intelligence design concepts, with the core objective of discovering intranet failure and internal irregularities, comprehensively collects data from behavioral observation points of endpoints, business systems, and network traffic, integrates correlation analysis, entity security anomalous behavior analysis, AI analysis to form a vertical analysis system. In addition, based on trapping analysis, traffic analysis, endpoint detection response and other technical support, through constructing behavioral models and comprehensive scoring mechanisms, it captures subtle behavioral anomalies in the intranet, sketches out identity/asset behavioral contours, and then uses vertical and deep analysis to determine cyclical behaviors, discover intranet lapses and internal violations, and ultimately unearth lurking intranet high-level threats.

Product Advantages
Comprehensive big data mechanism

With built-in comprehensive big data analysis mechanism, it adopts distributed computing, distributed storage, data warehouse, distributed messaging system and other components. It ensures high-performance processing capability and powerful scalability by distributed messaging system and microsecond real-time streaming analysis engine, ensures second-level response capability for big data interaction by full-text search engine, and provides intelligent analysis capability by machine learning engine.

Rich pre-defined analysis rules

A variety of pre-defined threat analysis rules, including: attack analysis, intranet failure, data leakage, privilege abuse, business anomalies, anomalous access, etc. The construction of threat analysis rules applies multiple Al algorithms, such as: time-series analysis, CART, LSTM, K-means clustering, Ngram ranking, etc.

Vertical analysis technology

The product carries three analysis engines: correlation analysis engine for custom modeling based on the multivariate group arithmetic base; behavioral analysis for deep learning of massive data to observe and statistics; and deep analysis engine for in-depth mining and analysis of cybersecurity threat behaviors that do not conform to simple laws of logical relationships. Through the three analysis engines, it conducts comprehensive in-depth analysis of network security threat behavior.

Visual analytic modeling

The product provides visual analysis modeling capability, completes the construction of behavioral warehouse through behavioral index modeling technology, transforms analytical capability into scenario, completes the construction of analytical model by assembling analytical modules into analytical scenarios through visual, drag-and-drop methods, and realizes simple and flexible customization of analytical model.

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