CLExtract: Recovering Highly Corrupted DVB/GSE Satellite Stream with Contrastive Learning ...

• Main Authors: Lin, Minghao, Cheng, Minghao, Luo, Dongsheng, Chen, Yueqi
• Format: Article in Journal/Newspaper
• Language: unknown
• Published: arXiv 2023
• Subjects: Systems and Control eess.SY; FOS Electrical engineering, electronic engineering, information engineering; North Atlantic
• Online Access: https://dx.doi.org/10.48550/arxiv.2310.08210; https://arxiv.org/abs/2310.08210

Since satellite systems are playing an increasingly important role in our civilization, their security and privacy weaknesses are more and more concerned. For example, prior work demonstrates that the communication channel between maritime VSAT and ground segment can be eavesdropped on using consumer-grade equipment. The stream decoder GSExtract developed in this prior work performs well for most packets but shows incapacity for corrupted streams. We discovered that such stream corruption commonly exists in not only Europe and North Atlantic areas but also Asian areas. In our experiment, using GSExtract, we are only able to decode 2.1\% satellite streams we eavesdropped on in Asia. Therefore, in this work, we propose to use a contrastive learning technique with data augmentation to decode and recover such highly corrupted streams. Rather than rely on critical information in corrupted streams to search for headers and perform decoding, contrastive learning directly learns the features of packet headers at ... : SpaceSec'23, 11 pages, 14 figures ...