Phishing Detection Server Using Timestamp Verification
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Phishing attacks pose challenges due to users unknowingly providing security credentials, difficulty in identifying phishing sites with fixed algorithms, and users ignoring security warnings, making existing methods ineffective in preventing unauthorized transactions.
Innovation Solution
A phishing detection server component and method that aggregates password reuse event reports from client components to detect and prevent phishing attacks, using timestamp verification to mitigate false reports and identify potentially erroneous data, and employing learned statistics to validate the likelihood of password reuse events.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If fixed algorithms are used to identify phishing sites, then the detection method is simple to implement, but attackers can quickly adapt and evade detection
Solution Approach 1:
The patent implements dynamic detection by transitioning from fixed algorithms to adaptive machine learning models that continuously learn from new phishing patterns. The system updates its detection capabilities in real-time based on emerging attack vectors, ensuring both ease of implementation through automated learning and high reliability through adaptive pattern recognition.
Solution Approach 2:
The detection system performs self-improvement by automatically learning from new phishing attempts and updating its models without requiring manual reconfiguration. The machine learning components continuously train on new data, enabling the system to adapt to evolving attack methods while maintaining simple deployment and operation.
2Loss of information
If security warnings are provided to users, then awareness of security dangers is increased, but users tend to ignore warnings and continue clicking suspicious links
Solution Approach 1:
The patent implements feedback mechanisms that provide real-time alerts and warnings to users when phishing attempts are detected. The system continuously monitors user interactions and provides immediate feedback about suspicious activities, reinforcing security awareness while guiding users toward safe behaviors through actionable alerts and educational messages.
Solution Approach 2:
The system introduces an intermediary layer between users and phishing sites, providing automated analysis and warning messages that mediate user decisions. This intermediary component translates complex security risks into understandable warnings and can actively block suspicious content, making security protection more effective without relying solely on user judgment.
3Measurement precision
If password reuse event reports are aggregated from multiple clients, then phishing detection accuracy is improved, but the system becomes vulnerable to false reports and malicious attacks
Solution Approach 1:
The patent implements preliminary verification mechanisms that validate reports before they are incorporated into the detection system. The machine learning models pre-screen incoming reports for credibility, checking for patterns of false reporting and malicious activity before accepting data into the aggregation system, thereby maintaining high detection accuracy while filtering out harmful inputs.
Solution Approach 2:
The system converts malicious false reports into training data for improving detection accuracy. By analyzing patterns in false reports and malicious attacks, the machine learning models learn to distinguish between legitimate phishing indicators and fraudulent reports, ultimately strengthening the system's ability to detect real threats while becoming more resilient to attacks.
Data Source
AI summary
A phishing detection server component and method is provided. The component can be employed as part of a system to detect/phishing attacks. The phishing detection server component can receive password reuse event report(s), for example, from a protection component of client component(s).Due to the malicious nature of phishing in general, the phishing detection server component can be susceptible to attacks by phishers (e.g., by reverse engineering of the client component). For example, false report(s) of PREs can be received from phisher(s) in an attempt to overwhelm the server component, induce false positives and/or induce false negatives.Upon receipt of a PRE report, the phishing detection server component can first verify that the timestamp(s) are genuine (e.g., previously generated by the phishing detection server component). The report verification component can employ the timestamp(s) to verify veracity of the report (e.g., to minimize attacks by phishers).