Message Trans-Denotation for Buffer Overflow Defense
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Solution Overview
Problem
Existing computer systems face challenges in defending against attacks that exploit buffer overflow vulnerabilities and inappropriately using relational databases, as well as in efficiently processing and securing messages to prevent unauthorized access and ensure secure data transmission.
Innovation Solution
The method involves classifying computer messages using Efficient Grammatical Clustering (EGC) and applying message templates for trans-denotation, which changes the message's denotational semantics to improve security, performance, and data integrity by ensuring messages are syntactically valid and grammatically correct before processing, thereby preventing sensitive information exposure and unauthorized access.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional message processing methods are used, then processing speed is fast, but security against buffer overflow vulnerabilities and unauthorized access is weak
Solution Approach 1:
The patent applies preliminary action by performing message classification and template matching before the message is processed by the target system. The message is analyzed, classified into a cluster, and trans-denotated against malicious patterns in advance, preventing security issues before they occur during execution.
Solution Approach 2:
The patent introduces an intermediary message processing layer that sits between the message source and the target system. This intermediary classifies messages using EGC, performs trans-denotation to identify malicious content, and filters or transforms messages before they reach the vulnerable system, thus protecting against buffer overflow and unauthorized access.
2Reliability
If message classification and template matching are performed for every message, then security is improved, but computational overhead increases
Solution Approach 1:
The patent applies partial action by performing full message classification and template matching only when necessary. The system uses efficient grammatical clustering to quickly categorize messages, and only performs detailed trans-denotation analysis on messages that require security verification, rather than analyzing every single message in depth.
Solution Approach 2:
The patent changes the parameter of message analysis depth dynamically. For common, benign message types, it uses lighter verification methods, while for suspicious or unusual messages, it applies full template matching and trans-denotation analysis, thus adapting computational resources to actual security needs.
3Loss of information
If all message details are transmitted, then data completeness is maintained, but exposure of sensitive information increases
Solution Approach 1:
The patent extracts and removes sensitive information from messages before transmission or storage. By analyzing message content against templates that identify sensitive data patterns, the system extracts only the necessary information for processing while removing or masking sensitive details, thus maintaining functional completeness while reducing exposure risk.
Solution Approach 2:
The patent applies preliminary anti-action by identifying and protecting against sensitive information exposure before it occurs. The trans-denotation process proactively detects patterns that indicate sensitive data in messages and takes preventive measures such as masking, encryption, or removal of such information before the message is fully processed or stored.
Data Source
AI summary
Embodiments of the invention provide a method, computer program and apparatus for processing a computer message, the method comprising: upon receipt of a computer message at a computer, classifying the computer message and assigning it a message cluster identification in dependence thereon; and, utilizing a message template to trans-denotate the message, wherein the message template is selected in dependence on the message cluster identification.