Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Emir Ozturk"'
Publikováno v:
IEEE Access, Vol 12, Pp 14248-14259 (2024)
In this study, a steganography method based on BERT transformer model is proposed for hiding text data in cover text. The aim is to hide information by replacing specific words within the text using BERT’s masked language modeling (MLM) feature. In
Externí odkaz:
https://doaj.org/article/bf6dd50624b44765a1d534ddb0526317
Autor:
Emir Öztürk, Altan Mesut
Publikováno v:
PeerJ Computer Science, Vol 10, p e2423 (2024)
Learning-based data compression methods have gained significant attention in recent years. Although these methods achieve higher compression ratios compared to traditional techniques, their slow processing times make them less suitable for compressin
Externí odkaz:
https://doaj.org/article/2477bac0dde44ec69bab2f82083e2a26
Autor:
Emir Öztürk
Publikováno v:
SoftwareX, Vol 27, Iss , Pp 101847- (2024)
This study introduces XCompress, a Python-based tool for effectively utilizing various compression algorithms. XCompress offers manual, brute force, and Large Language Model (LLM) methods to determine the most suitable algorithm based on the type of
Externí odkaz:
https://doaj.org/article/74150f27180e44a7ae66950157baf2d0
Publikováno v:
2017 International Conference on Computer Science and Engineering (UBMK).
In this article, we present a novel word-based lossless compression algorithm for text files which uses a semi-static model. We named our algorithm as Multi-stream Word-based Compression Algorithm (MWCA), because it stores the compressed forms of the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6cdce079aeda68fe69ecdcf4fae4fb14
https://doi.org/10.1109/ubmk.2017.8093552
https://doi.org/10.1109/ubmk.2017.8093552