Anti-Phishing System Using Marked Dummy Responses
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Solution Overview
Problem
Phishing attacks, which involve fraudulent emails mimicking legitimate sources to obtain sensitive information, pose significant risks to companies by damaging brand equity, increasing operational costs, and compromising customer trust, as existing technologies are inadequate in effectively detecting and preventing such scams.
Innovation Solution
A system and method that responds to Phishing attacks by sending mimic responses designed to entrap and detect fraudsters, using techniques like 'honey pots' and content filtering, and employing a central server to monitor and counteract fraudulent activities, including the use of dummy responses and marked data to dilute the quality of data obtained by attackers, thereby reducing the impact and facilitating the detection of originators.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If existing detection technologies are used, then some fraudulent emails can be detected, but the detection effectiveness is inadequate and many phishing attacks succeed
Solution Approach 1:
The system performs preliminary actions by sending dummy responses to fraudulent email addresses before real victims can be harmed. These dummy responses contain marked data that will be tracked if used, allowing the system to detect and prevent phishing attacks proactively rather than reactively
Solution Approach 2:
The system introduces an intermediary layer between phishing attacks and victims by using dummy responses with marked data as mediators. This intermediary data allows the system to monitor and detect fraudulent activities without directly exposing real victims to harm
2Measurement precision
If more comprehensive monitoring and tracking is implemented, then fraud detection capability improves, but the system becomes more complex and resource-intensive
Solution Approach 1:
The system creates simplified copies of real user responses using dummy data that mimics legitimate email reply patterns. These copied responses are easier to generate and track than monitoring all actual user communications, reducing system complexity while maintaining detection precision
Solution Approach 2:
The system changes parameters by using marked data with unique identifiers in dummy responses. This allows automated tracking and detection without requiring complex analysis of communication content, simplifying the monitoring system while improving detection precision
3Loss of information
If dummy responses with marked data are sent to fraudsters, then the value of stolen data is reduced, but the risk of exposing the detection system increases
Solution Approach 1:
The system converts the harm of data theft into a benefit by using marked dummy data that appears valuable to fraudsters but is actually traceable. When fraudsters attempt to use this marked data, it reveals their identities and methods, turning their harmful actions into detection opportunities
Solution Approach 2:
The system uses cheap, disposable dummy responses with marked data instead of protecting valuable real user information. These dummy responses can be freely distributed without risk, and once used or traced, they serve their purpose of identifying fraudsters without long-term security concerns
Data Source
AI summary
A system and method may respond to a fraudulent attack, such as a Phishing attack. The system and method may send a number of responses to party committing fraud, the responses designed to mimic the responses to a Phishing attack. The responses may include codes or marked information designed to entrap or detect the party committing fraud.