SeSy: Linguistic Steganalysis Framework Integrating Semantic and Syntactic Features
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DOI: 10.1109/lsp.2021.3122901
Abstract: With the rapid development of natural language processing technology and linguistic steganography, linguistic steganalysis gains considerable interest in recent years. Current advanced methods dominantly focus on statistical features in semantic view yet ignore syntax structure… read more here.
Keywords: syntactic features; steganalysis; semantic syntactic; steganalysis framework ... See more keywords
Small-Scale Linguistic Steganalysis for Multi-Concealed Scenarios
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DOI: 10.1109/lsp.2021.3128372
Abstract: Recently, due to the considerable feature expression ability of neural networks, deep linguistic steganalysis methods have been greatly developed. However, there are still two issues that need to be ameliorated. First, the prevailing linguistic steganalysis… read more here.
Keywords: small scale; proposed method; steganalysis; steganalysis methods ... See more keywords
Aggregating Local and Global Text Features for Linguistic Steganalysis
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DOI: 10.1109/lsp.2022.3185946
Abstract: Existing linguistic steganalysis methods share a similar conceptual learning paradigm: namely, learning specific features derived from a word and its surrounding words, then passing them to the classifier. However, these features are unable to deal… read more here.
Keywords: text features; aggregating local; local global; steganalysis ... See more keywords
Linguistic Steganalysis Merging Semantic and Statistical Features
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Signal Processing Letters"
DOI: 10.1109/lsp.2022.3212630
Abstract: With the rapid development of Natural Language Processing (NLP), more and more linguistic steganography methods have appeared in recent years, which may bring great challenges to the protection of cyberspace security. Due to the powerful… read more here.
Keywords: semantic statistical; dnn based; statistical features; steganalysis ... See more keywords
Linguistic Steganalysis by Enhancing and Integrating Local and Global Features
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Signal Processing Letters"
DOI: 10.1109/lsp.2023.3238283
Abstract: With the improvement of steganography, the difference of statistical distribution caused by information hiding is getting smaller and smaller, increasing the difficulty of steganalysis. The existing steganalysis models value different features equally, while the differences… read more here.
Keywords: local global; steganalysis; enhancing integrating; integrating local ... See more keywords