Cyber security executes a useful function in the information technology sector. Recently, keeping the data in the secured area has grown one of the most rebuts recently. In the cyber security field the first thought t...
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softwaresecurity is a concern due to software's pervasiveness and how rapid software's are developed. Although studies have emphasized the importance of addressing security requirements during the early phase...
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The emergence of the Internet of Things (IoT) has led to an increase in data streams, requiring new network architectures that can accommodate the mass number of connected devices. However, the heterogeneity and secur...
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With the rapid development of computernetworks, a vast amount of information is transmitted and stored within them. However, each node within these networks could potentially be a source of information leakage. In or...
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Image steganography and image steganalysis is one of the research hotspots in the field of information security, the abuse of steganography causes many security risks. As an attack method of image steganography, the m...
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ISBN:
(纸本)9798350349184;9798350349191
Image steganography and image steganalysis is one of the research hotspots in the field of information security, the abuse of steganography causes many security risks. As an attack method of image steganography, the main purpose of image steganalysis is to detect whether there is secret information in the image. Recent works have demonstrated the efficacy of CNN in the realm of image steganalysis. However, due to the limitation of convolution kernel size and lack of the ability to model long-range dependencies, CNN-based steganalysis methods face challenges with capturing the global features of steganographic images which are beneficial for image steganalysis. This paper proposes a multi-branch feature fusion network, called MFFNet, which effective extraction and fusion of different features of steganographic images to achieve better detection performance. Firstly, several residual attention blocks (RAB) are incorporated with spatial rich model filters (SRM) in the preprocessing phase to enhance the signal-to-noise ratio (SNR) of steganographic signals. Secondly, in the feature extraction phase, a three-branch parallel fusion module (TFM) is designed to fuse different branches to rich feature representations of steganographic images, where the global branch captures global features by a hardware-friendly (DFC) attention mechanism. Finally, the channel split mechanism is exploited to prevent feature redundancies and decrease the number of parameters. The experiments reflect that the proposed network outperforms several state-of-the-art image steganalysis methods.
In the era of artificial intelligence, intelligence improves the operational efficiency and service quality of the civil aviation industry, but at the same time, it also brings various networksecurity problems. In th...
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In the new era, computernetworksecurity issues have attracted more and more attention. How to use the latest technology to strengthen the network operating environment and prevent data information leakage has become...
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In the current social construction and development, the computernetworksecurity architecture design is composed of software and hardware, which refers to the communication transmission activities with transmission c...
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Facing the fierce competition in the construction market, the contractor's investigation and forecast of construction material prices is not only an important prerequisite for reasonable quotation and winning bids...
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In the paper, the penetration testing software aircrack-ng tool group was used to attack the wireless network, and the wireless network password of WPA/WPA2 encryption mode was cracked in the Kali-Linux virtual experi...
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