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4 results about "Evolving networks" patented technology

Evolving networks are networks that change as a function of time. They are a natural extension of network science since almost all real world networks evolve over time, either by adding or removing nodes or links over time. Often all of these processes occur simultaneously, such as in social networks where people make and lose friends over time, thereby creating and destroying edges, and some people become part of new social networks or leave their networks, changing the nodes in the network. Evolving network concepts build on established network theory and are now being introduced into studying networks in many diverse fields.

System and method for adaptive cyber threat detection using multi-layer behavioral analysis

The present invention discloses an adaptive cyber threat detection system and method implemented through a computing device configured to perform multi-layer behavioral analysis of network and system activities. The system receives network traffic data and system activity data, conditions the received data into structured behavioral event records, and generates multi-dimensional behavioral profiles associated with identities, devices, and temporal sequences. The behavioral profiles are compared against adaptive behavioral baseline profiles across multiple analytical layers to identify deviations indicative of anomalous behavior. Identified deviations are subjected to staged validation by correlating behavioral evidence across independent dimensions to confirm malicious activity. Upon confirmation, the system initiates appropriate security response actions based on determined threat severity and records detection outcomes in a secure event log. The adaptive behavioral baselines are continuously updated using validated non-malicious behavioral outcomes, enabling the system to dynamically adjust to evolving network conditions while maintaining accurate and reliable cyber threat detection.
Owner:KAMRUZZAMAN MD

Method and system for dynamic generation of environmental planning based on human-computer interaction and iterative feedback

The application provides an environmental protection planning dynamic generation method and system based on human-computer interaction and iterative feedback, first collects an initial environmental protection planning element set of a target area and constructs an initial correlation network, calculates edge correlation strength; receives interactive operation data through a human-computer interaction interface, updates the correlation network to obtain an updated network; collects a feedback data set within a preset interaction period and performs semantic labeling; inputs the feedback data with semantic labels into an element evolution model, drives correlation network node expansion and edge correlation relationship reconstruction, generates an evolved network and identifies element conflicts; according to the evolved network and a conflict analysis report, calls a planning scheme generation model to perform multi-objective constraint optimization, generates a dynamic environmental protection planning scheme and feeds back to the human-computer interaction interface, and simultaneously outputs a scheme evolution trajectory diagram. The application realizes dynamic generation and optimization of environmental protection planning, and improves the scientificity and feasibility of the planning.
Owner:SICHUAN JUNDONG ENVIRONMENTAL PROTECTION TECHNOLOGY CO LTD

Systems and methods for wireless network management

PendingUS20260189486A1Cloud systemsData modeling
Disclosed are computerized systems and methods for a decision intelligence (DI)-based framework that automatically and / or dynamically provides mechanisms for managing, optimizing and configuring a WiFi network at a location. The framework provides network management utilizing edge processing capabilities to bridge local WiFi and cloud systems. The framework implements comprehensive device typing through multi-layered analysis combining passive monitoring, deep packet inspection and hybrid deterministic-probabilistic classification methods. State synchronization between local and cloud networks can be achieved through hierarchical data modeling and differential synchronization algorithms. The framework can implement advanced features that include automated channel optimization, QoS management, and security monitoring. The framework incorporates self-healing capabilities using reinforcement learning techniques and maintains operational efficiency through intelligent resource management and workload distribution. The framework can operate autonomously while requiring minimal cloud connectivity, featuring extensible architecture through a plugin system that enables adaptation to evolving network requirements while maintaining stable operation of existing capabilities.
Owner:PLUME DESIGN INC