Security Awareness Workflow Recommendations for New Threat Response
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Solution Overview
Problem
Existing cybersecurity tools struggle to detect and mitigate social engineering threats, relying heavily on employee awareness and training, which can be ineffective against new and unknown threats, leading to increased cybersecurity incidents and costs.
Innovation Solution
A crowdsourced security awareness workflow recommendation model that assesses the effectiveness of security awareness training and provides tailored workflows based on user actions and metrics, recommending configurations to enhance employee response to potential threats.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If organizations rely on traditional cybersecurity tools (antivirus, anti-ransomware, anti-phishing) to detect and intercept known attacks, then known threats can be effectively mitigated, but new and unknown social engineering threats cannot be detected
Solution Approach 1:
The system implements continuous feedback loops where user responses to security awareness workflows are collected, measured, and used to automatically adjust and optimize future workflow configurations. Effectiveness metrics are tracked over time and fed back into the system to improve detection and response to evolving threats
Solution Approach 2:
The security awareness workflow system transitions from static, pre-defined training programs to dynamic, adaptive workflows that automatically adjust based on real-time effectiveness metrics, user behavior patterns, and emerging threat landscapes. The system continuously evolves its approach to match new social engineering techniques
2Ease of operation
If organizations conduct security awareness training through in-house teams or third parties, then users can be educated on detecting and reporting threats, but the training may be ineffective against new and unknown attacks
Solution Approach 1:
The system enables users to actively participate in their own security awareness development by responding to simulated phishing attacks and security scenarios. Users receive personalized feedback and automated training recommendations based on their individual performance, allowing them to self-improve their threat detection skills
Solution Approach 2:
The system conducts simulated phishing attacks and security awareness workflows in advance of real threats, allowing users to practice and learn from controlled scenarios before encountering actual attacks. This preliminary training prepares users to recognize and respond to new threat patterns
3Reliability
If organizations implement comprehensive security awareness training programs, then user awareness can be improved, but the complexity of designing and managing effective workflows increases
Solution Approach 1:
The system replaces manual workflow design and management with automated machine learning algorithms that generate, optimize, and adjust security awareness workflows automatically. Effectiveness metrics are calculated and used to drive automated improvements, eliminating the need for complex manual intervention
Solution Approach 2:
The security awareness platform serves multiple functions simultaneously: it delivers training content, conducts simulated phishing attacks, measures effectiveness metrics, generates recommendations, and automatically optimizes workflows. This multi-functional approach consolidates complexity into a unified system
4Ease of operation
If organizations use simulated phishing attacks and computer-based training, then users can be educated on threat recognition, but the training may not translate to effective response in real attack scenarios
Solution Approach 1:
The system provides immediate feedback to users after they interact with simulated phishing attacks, showing them the correct response and explaining the reasoning. This feedback loop reinforces learning and helps users translate training into effective real-world responses
Solution Approach 2:
The system employs multiple simulated phishing attacks and repeated training scenarios, exposing users to threats frequently and from different angles. This excessive exposure ensures users encounter enough variations to build robust recognition and response skills that transfer to real attacks
Data Source
AI summary
Systems and methods are described for recommendation of one or more security awareness workflows are described. One or more security awareness workflows may be deployed to deliver one or more remedial responses to one or more users in response to detection of one or more actions of the one or more users. An effectiveness of the one or more security awareness workflows are assessed and based at least on the assessment, one or more effectiveness metrics for the one or more security awareness workflows are determined. The one or more effectiveness metrics may represent the effectiveness of the one or more security awareness workflows. Based at least on the one or more effectiveness metrics, a recommendation of one or more security awareness workflow configurations may be identified.