Dynamic Financial Account Security via Risk Thresholds
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Solution Overview
Problem
Financial accounts are vulnerable to cyber-attacks and fraudulent behavior due to user availability, location, and device control, necessitating improved security measures to prevent unauthorized access.
Innovation Solution
A method that analyzes financial accounts, assigns a risk threshold, monitors vulnerabilities using a vulnerability score, and prevents access when the risk threshold is exceeded, incorporating real-time user data and machine learning models to provide recommendations and restrict transactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional security measures (usernames, passwords, security questions) are applied to protect financial accounts, then basic account security is improved, but accounts remain vulnerable to cyber-attacks and fraudulent behavior due to user availability, location, and device control factors
Solution Approach 1:
The system dynamically changes security parameters by assigning risk thresholds to different financial accounts and adjusting access control based on real-time vulnerability scores. The vulnerability score is generated based on user data including availability, location, and device control factors, allowing the security level to adapt to current conditions rather than using static credentials
Solution Approach 2:
The system performs preliminary security assessment by analyzing user data and generating vulnerability scores before access is attempted. Risk thresholds are assigned to accounts in advance, and the system proactively prevents access when vulnerability scores exceed these thresholds, rather than reacting after a breach occurs
2Reliability
If dynamic vulnerability monitoring and risk threshold enforcement are implemented, then account security against cyber-attacks is improved, but system complexity increases due to real-time data analysis and machine learning model integration
Solution Approach 1:
The system performs self-assessment by automatically analyzing its own security vulnerability using machine learning models and user data. The vulnerability scoring mechanism is self-generated and self-adjusted based on monitored factors, reducing the need for external security management infrastructure
Solution Approach 2:
The security system integrates multiple functions into a unified platform: user data collection, vulnerability score generation, risk threshold assignment, and access control enforcement. This multi-functional approach consolidates what would otherwise require separate systems into a single integrated solution
Data Source
AI summary
A method, computer system, and a computer program product for account security is provided. The present invention may include analyzing one or more financial accounts of a user and assigning a risk threshold to each of the one or more financial accounts. The present invention may include monitoring a vulnerability of each of the one or more financial accounts, wherein the vulnerability is monitored using a vulnerability score, the vulnerability score being generated based on user data. The present invention may include determining the risk threshold has been exceeded for at least one financial account based on a comparison of the vulnerability score and the risk threshold of the at least one financial account. The present invention may include preventing access to the at least one financial account in which the risk threshold has been exceeded.