Text Coverless Information Hiding Based on Word2vec

Long, Yi; Liu, Yuling

doi:10.1007/978-3-030-00015-8_40

Cited by 8 publications

(5 citation statements)

References 16 publications

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“…For example, in [26], word vector is used on encrypted cloud data to achieve lightweight efficient multi-keyword ranked search by finding the most similar query vector and document vector. Besides, in [27], the original keyword is substituted by a similar keyword in case the text retrieval fails. This replacement is achieved by finding word vectors with high similarity.…”

Section: Related Workmentioning

confidence: 99%

TEDL: A Text Encryption Method Based on Deep Learning

Wang

2021

Applied Sciences

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Recent years have seen an increasing emphasis on information security, and various encryption methods have been proposed. However, for symmetric encryption methods, the well-known encryption techniques still rely on the key space to guarantee security and suffer from frequent key updating. Aiming to solve those problems, this paper proposes a novel symmetry-key method for text encryption based on deep learning called TEDL, where the secret key includes hyperparameters in the deep learning model and the core step of encryption is transforming input data into weights trained under hyperparameters. Firstly, both communication parties establish a word vector table by training a deep learning model according to specified hyperparameters. Then, a self-update codebook is constructed on the word vector table with the SHA-256 function and other tricks. When communication starts, encryption and decryption are equivalent to indexing and inverted indexing on the codebook, respectively, thus achieving the transformation between plaintext and ciphertext. Results of experiments and relevant analyses show that TEDL performs well for security, efficiency, generality, and has a lower demand for the frequency of key redistribution. Especially, as a supplement to current encryption methods, the time-consuming process of constructing a codebook increases the difficulty of brute-force attacks, meanwhile, it does not degrade the efficiency of communications.

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Section: Related Workmentioning

confidence: 99%

TEDL: A Text Encryption Method Based on Deep Learning

Wang

2021

Applied Sciences

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“…For example, in [52], word vector is used on encrypted cloud data to achieve lightweight efficient multikeyword ranked search by finding the most similar query vector and document vector. Besides, in [25], the original keyword is substituted by a similar keyword in case the text retrieval fails. This replacement is achieved by finding word vectors with high similarity.…”

Section: Related Workmentioning

confidence: 99%

TEDL: A Text Encryption Method Based on Deep Learning

Li¹,

Wang

2020

Preprint

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Recent years have seen an increasing emphasis on information security, and various encryption methods have been proposed. However, for symmetric encryption methods, the well-known encryption techniques still rely on the key space to guarantee security and suffer from frequent key updating. Aiming to solve those problems, this paper proposes a novel text encryption method based on deep learning called TEDL, where the secret key includes hyperparameters in deep learning model and the core step of encryption is transforming input data into weights trained under hyperparameters. Firstly, both communication parties establish a word vector table by training a deep learning model according to specified hyperparameters. Then, a self-update codebook is constructed on the word vector table with the SHA-256 function and other tricks. When communication starts, encryption and decryption are equivalent to indexing and inverted indexing on the codebook, respectively, thus achieving the transformation between plaintext and ciphertext. Results of experiments and relevant analyses show that TEDL performs well for security, efficiency, generality, and has a lower demand for the frequency of key redistribution. Especially, as a supplement to current encryption methods, the time-consuming process of constructing a codebook increases the difficulty of brute-force attacks while not degrade the communication efficiency.

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“…Wu (2017a,2017b) extracted all parts of Chinese characters, and used part of speech to hide the number of keywords to improve the capacity of information hiding. Long et al (2018) proposed a method for text coverless information hiding based on word2vec (p.463). This method used word2vec to get similar keywords, that is, when the text retrieval fails, the similar keywords can be replaced with keywords, so that the hiding success rate can reach 100% and the hiding capacity can be slightly increased.…”

Section: Introductionmentioning

confidence: 99%

A Big Data Text Coverless Information Hiding Based on Topic Distribution and TF-IDF

Qin

Zhou

Tan

et al. 2021

International Journal of Digital Crime and Forensics

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Coverless information hiding has become a hot topic in recent years. The existing steganalysis tools are invalidated due to coverless steganography without any modification to the carrier. However, for the text coverless has relatively low hiding capacity, this paper proposed a big data text coverless information hiding method based on LDA (latent Dirichlet allocation) topic distribution and keyword TF-IDF (term frequency-inverse document frequency). Firstly, the sender and receiver build codebook, including word segmentation, word frequency and TF-IDF features, LDA topic model clustering. The sender then shreds the secret information, converts it into keyword ID through the keywords-index table, and searches the text containing the secret information keywords. Secondly, the searched text is taken as the index tag according to the topic distribution and TF-IDF features. At the same time, random numbers are introduced to control the keyword order of secret information.

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Text Coverless Information Hiding Based on Word2vec

Cited by 8 publications

References 16 publications

TEDL: A Text Encryption Method Based on Deep Learning

TEDL: A Text Encryption Method Based on Deep Learning

TEDL: A Text Encryption Method Based on Deep Learning

A Big Data Text Coverless Information Hiding Based on Topic Distribution and TF-IDF

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