# Analysis and Research on Secondary LT Coding Anti-Eavesdropping Scheme Based on LT Code Degree-1
In addition, the literature [13] on Industrial Wireless Sensor Networks (IWSNs) suggests a secure cooperative transmission strategy for IWSNs based on fountain codes, which combines cooperative jamming in the physical layer with fountain coding in the application layer, and designs a cooperative jamming method based on constellation rotation, so that the quality of the signals received by the eavesdropper deteriorates and the secrecy of the transmission is guaranteed. The literature [14] also proposes a recursive finite feedback online fountain code for the Underwater Acoustic Network system (UANs) that can lower bandwidth and energy consumption and restrict the number of feedback packets by decoding the progress threshold. This UANs data transmission mechanism improves in terms of overhead, computational complexity, and efficiency. This is because digital fountain codes, which are more suited for wireless deletion channels because of their low decoding overhead, may efficiently conserve network resources and cut down on transmission delay. The Luby Transform (LT) code was first presented by [PERSON] [15] in 2002, and it enhances LT code performance by increasing the likelihood that degree-1 coded packets with robust soliton distribution will be encountered during the decoding iterations. Later, a Shift-LT code (SLT code) was put forth in the literature [16], where the source side uses feedback data to modify the RSD degree distribution, which significantly reduces the compiled code complexity, memory usage, and overall energy consumption. Next, the literature [17] introduces a feedback LT coding scheme that, by adjusting the variable nodal degree, reduces the encoding time and average overhead, accelerates the convergence of the symbol BER curve, and significantly enhances the anti-eavesdropping effect. According to the literature [18], this fountain coding scheme can achieve a high intermediate decoding rate by using feedback information to predict the decoder state and dynamically adjusting the non-uniform symbol selection distribution. The literature [19; 20] suggested modifying the LT code degree-1 and Online Fountain Codes without a build-up phase, respectively, by modifying the quantity of degree-1 coded symbols, doing away with the stacking phase, enhancing Belief Propagation (BP) decoding performance, and making sure that the received coded symbols are recovered as soon as possible. The degree distribution of the robust soliton distribution is then optimized in literature [21], and it is suggested to reorder the degree distribution from large to small in order to delay the emergence of degree-1 symbols. As a result, the decoding process is delayed, which is helpful for increasing the untranslated rate of the eavesdropper. According to the literature [22], an anti-eavesdropping method for the SLT-LT joint code is based on a collection of random symbols. The sender chooses a group of random symbols to send to the legitimate receiver as known symbols and cascades these random symbols with the message symbols to form the source symbols for cascade coding, which increases the eavesdropper's untranslated rate. The literature [23] devised an anti-eavesdropping channel coding method for the degree-1 symbols of LT code to LT coding again, so as to further improve the untranslated rate of eavesdroppers. The communication information transfer rate can be efficiently increased thanks to the decreased decoding overhead. In this paper, the secondary LT coding anti-eavesdropping scheme for LT code degree-1 is analyzed theoretically from the security capacity, complexity, and decoding overhead. From the experimental results, it can be seen that this scheme can effectively reduce the coding complexity, and when used in the case of longer source symbols, it can effectively reduce the decoding overhead and improve the efficiency of the eavesdropper's untranslated rate.