Enhancing Steganographic Text Extraction: Evaluating the Impact of NLP Models on Accuracy and Semantic Coherence

arXiv:2402.18849v1 Announce Type: new
Abstract: This study discusses a new method combining image steganography technology with Natural Language Processing (NLP) large models, aimed at improving the accuracy and robustness of extracting steganographic text. Traditional Least Significant Bit (LSB) steganography techniques face challenges in accuracy and robustness of information extraction when dealing with complex character encoding, such as Chinese characters. To address this issue, this study proposes an innovative LSB-NLP hybrid framework. This framework integrates the advanced capabilities of NLP large …

abstract accuracy arxiv challenges cs.ai cs.cl cs.cv extraction face image impact language language processing large models least natural natural language natural language processing nlp nlp models processing robustness semantic steganography study technology text type