Cloud Resource Session Monitoring for Browser Anomaly Detection
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Solution Overview
Problem
The increased vulnerability of communications networks to cyberattacks due to the proliferation of personal user equipment (BYOD) and cloud-based services complicates the protection of enterprise data, necessitating enhanced cyber security measures for authorized access and data integrity.
Innovation Solution
A cyber secure communications system, CyberSafe, is implemented with a cloud-based data and processing security hub and a secure web browser (SWB) in an isolated secure environment (CISE) to monitor and control data ingress and egress, enforce security policies, and provide real-time anomaly detection and risk assessment for authorized users.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If personal user equipment (BYOD) and cloud-based services are proliferated to enable remote work and access to enterprise data, then ease of operation and accessibility are improved, but vulnerability to cyberattacks and security risks increase
Solution Approach 1:
The patent introduces a cloud-based security hub as an intermediary between user equipment and enterprise data resources. This hub mediates all access requests, performing authentication, authorization, and continuous monitoring. The hub acts as a secure gateway that enables remote access while maintaining security controls, thus resolving the contradiction between accessibility and security vulnerability
Solution Approach 2:
The system segments the enterprise data environment into isolated cloud-based resources that can be selectively accessed. Instead of providing direct access to the entire enterprise network, the patent divides data into discrete, controllable resources that are presented through the security hub. This segmentation limits the attack surface and contains potential security breaches, addressing the vulnerability issue while maintaining accessibility
2Reliability
If comprehensive security monitoring and control measures are implemented to protect enterprise data, then security protection is improved, but system complexity increases
Solution Approach 1:
The patent merges multiple security functions (authentication, authorization, monitoring, anomaly detection, and data protection) into a single cloud-based security hub. By consolidating these functions in one centralized system rather than distributing them across multiple components, the patent achieves comprehensive security protection while managing system complexity through unified architecture
Solution Approach 2:
The security hub implements automated anomaly detection and response capabilities that operate without constant human intervention. The system automatically monitors user interactions, detects suspicious patterns, and responds to threats, reducing the operational complexity of managing comprehensive security monitoring while maintaining high reliability
3Measurement precision
If real-time monitoring of user interactions is performed to detect anomalies and prevent data leakage, then security detection capability is improved, but loss of time and processing overhead increase
Solution Approach 1:
The patent implements continuous feedback loops where the security hub monitors user interactions in real-time, compares them against established baselines and security policies, and immediately responds to anomalies. This feedback mechanism enables precise anomaly detection while maintaining efficient processing through automated decision-making algorithms that quickly evaluate and respond to security events
Data Source
AI summary
A method for providing secure access to cloud computing resources comprising: monitoring communications in sessions between a cloud computing resource, CCaaS, of cloud computing resources and users using web browsers comprised in user equipment, UE, to access the CCaaS; processing the monitored communications to accumulate data for at least one component or any combination of more than one of a set, CCaaS-KPI, of key performance indicators, KPIs, that characterize operation of the CCaaS during the sessions, a set, UE-KPI, of key performance indicators characterizing operation of the user equipment, UE, during the sessions, a set, U-KPI, characterizing actions of users accessing the CCaaS during the sessions, and/or a set, SMETA, of session metadata components that provide indexing and descriptive data for the sessions; processing the accumulated data to determine patterns characterizing normal interaction of users with the CCaaS; and using the normal patterns to detect an anomaly in a user session in which the user engages with the CCaaS.