Application Research of File Fingerprint Identification Detection Based on a Network Security Protection System
| Autor: | Sheng Shen, Yingwei Li, Lina Yu, Chunwei Wang, Fang Hou, Huixian Chang |
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| Rok vydání: | 2020 |
| Předmět: |
Technology
Article Subject Computer Networks and Communications Computer science Network security Feature extraction TK5101-6720 02 engineering and technology Data loss computer.software_genre 030507 speech-language pathology & audiology 03 medical and health sciences Fingerprint 0202 electrical engineering electronic engineering information engineering Electrical and Electronic Engineering business.industry Hamming distance File format Telecommunication 020201 artificial intelligence & image processing Data mining 0305 other medical science business computer Information Systems |
| Zdroj: | Wireless Communications and Mobile Computing, Vol 2020 (2020) |
| ISSN: | 1530-8677 1530-8669 |
| Popis: | A DLP (data loss prevention) system usually arranges network monitors at the network boundary to perform network traffic capture, file parsing, and strategy matching procedures. Strategy matching is a key process to prevent corporate secret-related documents from leaking. This paper adopts the document fingerprint similarity detection method based on the SimHash principle and customizes the KbS (Keyword-based SimHash) fingerprint, PbS (Paragraph-based SimHash) fingerprint, and SoP (SimHash of Paragraph) fingerprint, three different feature extraction SimHash algorithms for strategy matching to detect. The parsed unstructured data is stored as a file type in.txt format, and then a file fingerprint is generated. Matching the established sensitive document library to calculate the Hamming distance between the fingerprints, the Hamming distance values under different modification degrees are summarized. The experimental results reveal that the hybrid algorithmic strategy matching rules with different levels and accuracy are established. This paper has a reference role for the leakage prevention research of enterprise sensitive data. |
| Databáze: | OpenAIRE |
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