Text Message Hash Classification for Real-Time Threat Blocking
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for classifying malware in text messages are expensive and time-consuming, and there is a need for real-time detection and prevention of malicious and sensitive data transmission.
Innovation Solution
A system and method that utilizes a classification processor to parse and hash suspicious text messages, comparing the hashed data to known malicious and sensitive data stored in a blockchain network, allowing for real-time classification and blocking or deletion of such messages.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If traditional malware classification methods are used, then detection accuracy can be maintained, but the process becomes expensive and time-consuming
Solution Approach 1:
The system performs preliminary hashing of message data before full classification analysis. By converting message content to hash values and comparing against a database of known malicious hashes, the system quickly eliminates benign messages without requiring time-consuming deep analysis, while maintaining detection accuracy through subsequent detailed examination only of suspicious messages
Solution Approach 2:
The classification process is segmented into multiple stages: initial hash-based filtering, pattern matching against known threats, and detailed analysis only for messages that pass through earlier filters. This segmentation allows the system to process the majority of messages quickly while dedicating more resources only to potentially malicious messages
2Productivity
If real-time malware classification is implemented, then response speed improves, but system complexity increases
Solution Approach 1:
The system introduces hash values as an intermediary representation of message content. Instead of directly analyzing entire messages in real-time, the system converts messages to compact hash values for rapid comparison against a database of known malicious hashes, significantly reducing processing complexity while maintaining real-time classification capability
Solution Approach 2:
The system uses hash values as simplified copies of the original message content for comparison purposes. These hash copies enable rapid matching against threat databases without requiring the system to process the full complexity of original messages, thereby reducing computational burden while maintaining detection effectiveness
3Reliability
If hashed data is stored in blockchain network, then data security and storage capacity improve, but implementation complexity increases
Solution Approach 1:
The system extracts only the essential hash values from complete message data for storage in the blockchain network. By storing only these condensed representations rather than full message content, the system achieves enhanced security through blockchain's immutable ledger while minimizing storage requirements and reducing the complexity of data management
Data Source
AI summary
A method for classifying a suspicious text is disclosed. The method includes intercepting a suspicious text message having information data sent between a first and second user device. The method includes applying a hashing function to the information data to generate hashed information data, and storing the hashed information data in one or more of a plurality of network nodes in a blockchain network, where the plurality of network nodes form a distributed network configured to maintain a blockchain, and where each network node of the blockchain network comprises a blockchain processor configured to distribute the hashed information data among the plurality of network nodes. The method includes comparing the hashed information data to known hashed sensitive data stored in a database, and classifying the information data associated with the suspicious text message as containing sensitive data based on the comparison.