Backward Mining Technology Research On Continuous Attacks In Wide Time Domain

2018 IEEE SMARTWORLD, UBIQUITOUS INTELLIGENCE & COMPUTING, ADVANCED & TRUSTED COMPUTING, SCALABLE COMPUTING & COMMUNICATIONS, CLOUD & BIG DATA COMPUTING, INTERNET OF PEOPLE AND SMART CITY INNOVATION (SMARTWORLD/SCALCOM/UIC/ATC/CBDCOM/IOP/SCI)(2018)

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摘要
In the era of information-network, how to guardian users privacy and information security has become a hot topic. The services brought by big data and advanced information technology are expected to offer users a higher level of information security than that in the past. However, continuous attacks, especially in wide time domain, have seriously threatened company information security and users privacy. Therefore, it is essential to make full use of historical big data to implement attack traceback. In this paper, faced with severe issues, we propose a Tensor-Recall Convolutional Neural Network (TR-CNN) algorithm based on Deep Learning, which is suitable for training historical data. Then, we propose a new mechanism combined improved Deterministic Packet Marking(DPM) approach with backward mining approach in the users quality-oriented environment. Simulation results demonstrate that our strategy could achieve better performance.
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关键词
Attack Traceback, Backward Mining, Deep Learning, Big Data
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