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All Journal International Journal of Electrical and Computer Engineering TELKOMNIKA (Telecommunication Computing Electronics and Control)
Ahmed Sabah Ahmed AL-Jumaili
University of Information Technology and Communications
Computer Science & IT Electrical & Electronics Engineering

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A combination of least significant bit and deflate compression for image steganography Huda Kadhim Tayyeh; Ahmed Sabah Ahmed AL-Jumaili
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 1: February 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i1.pp358-364

Abstract

Steganography is one of the cryptography techniques where secret information can be hidden through multimedia files such as images and videos. Steganography can offer a way of exchanging secret and encrypted information in an untypical mechanism where communicating parties can only interpret the secret message. The literature has shown a great interest in the least significant bit (LSB) technique which aims at embedding the secret message bits into the most insignificant bits of the image pixels. Although LSB showed a stable performance of image steganography yet, many works should be done on the message part. This paper aims to propose a combination of LSB and Deflate compression algorithm for image steganography. The proposed Deflate algorithm utilized both LZ77 and Huffman coding. After compressing the message text, LSB has been applied to embed the text within the cover image. Using benchmark images, the proposed method demonstrated an outperformance over the state of the art. This can proof the efficacy of using Deflate as a data compression prior to the LSB embedding.
Classifying confidential data using SVM for efficient cloud query processing Huda Kadhim Tayyeh; Ahmed Sabah Ahmed Al-Jumaili
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 17, No 6: December 2019
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v17i6.13059

Abstract

Nowadays, organizations are widely using a cloud database engine from the cloud service providers. Privacy still is the main concern for these organizations where every organization is strictly looking forward more secure environment for their own data. Several studies have proposed different types of encryption methods to protect the data over the cloud. However, the daily transactions represented by queries for such databases makes encryption is inefficient solution. Therefore, recent studies presented a mechanism for classifying the data prior to migrate into the cloud. This would reduce the need of encryption which enhances the efficiency. Yet, most of the classification methods used in the literature were based on string-based matching approach. Such approach suffers of the exact match of terms where the partial matching would not be considered. This paper aims to take the advantage of N-gram representation along with Support Vector Machine classification. A real-time data will used in the experiment. After conducting the classification, the Advanced Encryption Standard algorithm will be used to encrypt the confidential data. Results showed that the proposed method outperformed the baseline encryption method. This emphasizes the usefulness of using the machine learning techniques for the process of classifying the data based on confidentiality.
Co-Authors Huda Kadhim Tayyeh