عنوان البحث(Papers / Research Title)
Text Steganography in Font Color of MS Excel Sheet
الناشر \ المحرر \ الكاتب (Author / Editor / Publisher)
رفاه محمد كاظم المطيري
Citation Information
رفاه,محمد,كاظم,المطيري ,Text Steganography in Font Color of MS Excel Sheet , Time 03/03/2019 18:32:44 : كلية الفنون الجميلة
وصف الابستركت (Abstract)
Text Steganography in Font Color of MS Excel Sheet
الوصف الكامل (Full Abstract)
One of the ways to maintain the security of data transfer over the network is to encrypt the data before sending it, for the purpose of increasing data privacy and its importance. Steganography, is used to hide encrypted data in various documents, the art of concealment is embedded Secret Messages (SM) to be passed confidentially within a file without influence on the properties of the file and this can t be anyone s hand is to know that there is confidential data encapsulated by transport data. Previous research used the Excel file to hide data in different ways, but the data masking and packaging by changing the color content writing is what distinguishes our research and make it alone in this area. The Microsoft Excel file size is being used to hide data remains constant in spite of the file containing the confidential data. The secret for the survival of file size unchanged despite the addition of encrypted data, is that confidential data is embedding in the value of the color pallet of the font format used in the cells, leading to the font color change slightly. The main advantage for scathing the Code Message (CM) upon the Cover Excel File (CEF) is making the brute force more confusing and has no possible to visualize the hiding message in normal circumstance, it is somehow rather than embedding it into either MS Word or PPT while the latter done sequentially, in this approach: each Full cell can hide a character with coding process (from 4 bits to 8 bits) In this study, we have had advantages through applying a new approach of Text to Excel hiding techniques, likewise both the conductivity ratio, and the degree of disappearances are indicated perfectly. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from Permissions@acm.org. DATA 18, October 1–2, 2018, Madrid, Spain © 2018 Association for Computing Machinery. ACM ISBN 978-1-4503-6536-9/18/10…$15.00 https://doi.org/10.1145/3279996.3280006
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