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- W2810265387 abstract "Wireless attack refers to the malicious activity to generate a wireless jamming signal to interfere with the data transmission of legitimate users. If the jamming duration of a wireless attack is long, it can be easily detected; such attacks also consume more energy for generating the jamming signal. We propose a frame-selective jamming to attack shorter frames that are essential to data communication protocols such as media access control (MAC) acknowledgement frames. Once a wireless signal is detected, the proposed jammer predicts the duration of the signal using a deep learning technique and generates a jamming signal selectively if the duration is expected to be shorter than or equal to a certain threshold." @default.
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- W2810265387 date "2018-06-01" @default.
- W2810265387 modified "2023-10-01" @default.
- W2810265387 title "Frame-Selective Wireless Attack Using Deep-Learning-Based Length Prediction" @default.
- W2810265387 cites W2542732716 @default.
- W2810265387 doi "https://doi.org/10.1109/sahcn.2018.8397145" @default.
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