"The pre processed UAVCAN dataset."

"The processing of this dataset involves the following steps. First, create a list of file paths that includes the paths of 10 binary files. Then, traverse the files one by one, check if each file exists, and if it does, read the file content. Next, for each line of data, use regular expressions to extract relevant information of the CAN message, including the label (either \"Normal\" or \"Attack\"), the CAN ID (convert the hexadecimal value to an integer), the data length (DLC), and the data payload (Payload, convert it to a list of integers). For cases where the DLC is less than 8, fill the empty positions with 0 (which can be changed to - 1). At the same time, perform a logarithmic transformation on the CAN ID to avoid overly large values. After that, combine the information of each CAN message into a feature vector and store it in a list. Finally, convert the processed data into a Pandas DataFrame, specify the column names, and save it as a CSV file. Ultimately, the datasets are merged and saved as the can_data.csv file, which contains all the processed CAN message information."

本数据集的处理流程如下：首先，构建包含10个二进制文件路径的文件列表。随后逐一遍历各文件，先验证文件是否存在，若存在则读取其内容。接下来，针对每一行数据，通过正则表达式提取控制器局域网（Controller Area Network, CAN）报文的相关信息，包括标签（取值仅为"Normal"或"Attack"）、CAN ID（将十六进制值转换为整数）、数据长度码（Data Length Code, DLC）以及数据有效载荷（Payload，转换为整数列表）。当数据长度码（DLC）小于8时，使用0填充空余位置（也可替换为-1）；同时对CAN ID进行对数变换，以避免数值过大。随后，将每条CAN报文的信息整合为特征向量，并存储至列表中。最后，将处理后的数据转换为Pandas DataFrame，指定列名后保存为CSV格式文件。最终将所有数据集合并，保存为can_data.csv文件，该文件包含所有经处理的CAN报文信息。