抗BGP中间人攻击的无证书签名方法

边界网关协议用于自治域之间交换网络可达信息,但面临中间人攻击威胁,因此提出一种改进的无证书多重签名方案并将其应用于边界网关协议.在该方案中域间路由须按照路由传递顺序对其进行签名,自治系统对多重签名验证成功才可接收路由,且自治系统的公私钥与可信中心交互生成,签名消息的长度固定,计算高效.通过安全性分析,证明基于无证书的有...

Prevention of Man-in-the-middle Attacks on BGP Using Certificateless Signatures

Digital images play an important role in information transmission, and image super-resolution technology can enrich image details. To address the problems of insufficient effective feature reuse of low-resolution images and excessive parameters in many networks, this study combines convolution kernels of different sizes and attention residual mechanism to construct the image super-resolution network. Three convolution layers of different scales are used to extract the image features, of which the second and third layers replace the large convolution kernels with small ones, and after the three-layer convolution fusion, the attention mechanism is introduced. Finally, the traditional Bicubic interpolation is used to directly provide low-frequency information for the network. By doing this, while reducing the number of parameters and mitigating the disappearance of gradients, the proposed network can make the effective high-frequency information gain greater weights and can enhance the nonlinear expression ability between the networks, which is conducive to the iterative convergence of network training. Experimental results show that the proposed network can enhance the image reconstruction ability to a certain extent.