Lightweight encryption hijacking attack detection system based on deep learning

A deep learning and attack detection technology, applied in transmission systems, digital transmission systems, instruments, etc., can solve problems such as economic losses, and achieve high classification accuracy, good heterogeneity, anti-spoofing, and good heterogeneity.

Pending Publication Date: 2022-03-08
SHANGHAI JIAO TONG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Even on August 26, 2021, Tencent Security Threat Intelligence Center detected that attackers injected mining scripts into thousands of hosts, causing serious economic losses

Method used

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  • Lightweight encryption hijacking attack detection system based on deep learning
  • Lightweight encryption hijacking attack detection system based on deep learning

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Embodiment Construction

[0074] The following describes several preferred embodiments of the present invention with reference to the accompanying drawings, so as to make the technical content clearer and easier to understand. The present invention can be embodied in many different forms of embodiments, and the protection scope of the present invention is not limited to the embodiments mentioned herein.

[0075] In the drawings, components with the same structure are denoted by the same numerals, and components with similar structures or functions are denoted by similar numerals. The size and thickness of each component shown in the drawings are shown arbitrarily, and the present invention does not limit the size and thickness of each component. In order to make the illustration clearer, the thickness of parts is appropriately exaggerated in some places in the drawings.

[0076] The present invention proposes a browser mining detection system, which includes a training deep learning detection module a...

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Abstract

The invention discloses a lightweight encryption hijacking attack detection system based on deep learning, and relates to the field of computer network security. Comprising two parts of model training and deployment detection. Aiming at the defects of an existing detection system, a deep learning technology is used for carrying out classification detection on a mining program converted into an image. According to the method, the malicious code vectorization technology is used, the semantic features of the mining program are added into the picture, and higher classification precision is achieved. Meanwhile, good isomerism is guaranteed, and mining programs written by two mainstream languages (JavaScript and WebAssessment) can be detected at the same time. The method can be deployed to a campus or enterprise gateway to monitor and detect daily traffic. And adding the detected domain name on which the malicious mining script is mounted into a blacklist database. The detection system provided by the invention plays a crucial role in network defense of campuses and enterprises, and has positive significance in real-time detection and defense of encryption hijacking attacks.

Description

technical field [0001] The invention relates to the field of computer network security, in particular to a lightweight encryption hijacking attack detection system based on deep learning. Background technique [0002] Cryptocurrency is a trading medium that uses the principles of cryptography to ensure transaction security and control the creation of trading units. Cryptocurrency is a type of digital currency (or virtual currency). Bitcoin (BTC), one of the cryptocurrencies, was first proposed by Satoshi Nakamoto in 2008 and officially born in January 2009, becoming the world's first decentralized cryptocurrency. As the earliest cryptocurrency, cryptocurrency is based on a decentralized consensus mechanism, as opposed to a banking and financial system that relies on a centralized regulatory system. At the same time, the biggest difference between Bitcoin and traditional currencies is that it does not rely on monetary institutions to issue, but is calculated by algorithms, ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04L9/40G06K9/62
CPCH04L63/1425H04L63/1441G06F18/214
Inventor 邹福泰贺皓涵王梓帆吴越昌洵成
Owner SHANGHAI JIAO TONG UNIV
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