• Electronics and Telecommunications Trends
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• v.38 no.5
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• pp.71-80
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• 2023

With the rapid advancement of the Internet, the use of encrypted traffic has surged in order to protect data during transmission. Simultaneously, network attacks have also begun to leverage encrypted traffic, leading to active research in the field of encrypted traffic analysis to overcome the limitations of traditional detection methods. In this paper, we provide an overview of the encrypted traffic analysis field, covering the analysis process, domains, models, evaluation methods, and research trends. Specifically, it focuses on the research trends in the field of anomaly detection in encrypted network traffic analysis. Furthermore, considerations for model development in encrypted traffic analysis are discussed, including traffic dataset composition, selection of traffic representation methods, creation of analysis models, and mitigation of AI model attacks. In the future, the volume of encrypted network traffic will continue to increase, particularly with a higher proportion of attack traffic utilizing encryption. Research on attack detection in such an environment must be consistently conducted to address these challenges.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.3
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• pp.50-55
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• 2021

In this paper, we proposed a technique for hiding the double-encrypted confidential data in the image using the pixel value of the image and the spatial encryption technique. The proposed technique inserts encrypted confidential data into the LSB of an image pixel in order to maintain high image quality. The stego-image generated by hiding the encrypted confidential data has very good quality and is visually indistinguishable from the original cover image, so that it is impossible to recognize whether the confidential data is hidden in the stego-image. It is possible to extract the original confidential data from the stego-image without loss. By conducting an experiment on the proposed technique, it was confirmed that the proposed technique is an effective technique for the practical application of data hiding. The proposed technique can be used in applications such as military and intellectual property protection that require high security.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.11
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• pp.1329-1340
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• 2016

Recently, Zhang proposed a scheme to hide information in encrypted images using synchronous stream ciphers. After the receiver decrypts the encrypted image and extracts data by calculating the spatial correlation property value using the fluctuation function which is designed to calculate spacial correlation between adjacent pixels in a decrypted image. Then, Hong improved the Zhang's data hiding scheme by introducing the side match technique. In this paper, a novel fluctuation function is proposed to reduce the recovery errors which arise during extracting hidden data. Then, we also demonstrated that the proposed fluctuation function outperforms the previous functions through computer simulations for sample images.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.3
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• pp.1051-1077
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• 2021

The secure communication of information is a major concern over the internet. The information must be protected before transmitting over a communication channel to avoid security violations. In this paper, a new hybrid method called compressed encrypted data embedding (CEDE) is proposed. In CEDE, the secret information is first compressed with Lempel Ziv Welch (LZW) compression algorithm. Then, the compressed secret information is encrypted using the Advanced Encryption Standard (AES) symmetric block cipher. In the last step, the encrypted information is embedded into an image of size 512 × 512 pixels by using image steganography. In the steganographic technique, the compressed and encrypted secret data bits are divided into pairs of two bits and pixels of the cover image are also arranged in four pairs. The four pairs of secret data are compared with the respective four pairs of each cover pixel which leads to sixteen possibilities of matching in between secret data pairs and pairs of cover pixels. The least significant bits (LSBs) of current and imminent pixels are modified according to the matching case number. The proposed technique provides double-folded security and the results show that stego image carries a high capacity of secret data with adequate peak signal to noise ratio (PSNR) and lower mean square error (MSE) when compared with existing methods in the literature.

• Electronics and Telecommunications Trends
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• v.33 no.1
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• pp.68-77
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• 2018

Data deduplication is a common used technology in backup systems and cloud storage to reduce storage costs and network traffic. To preserve data privacy from servers or malicious attackers, there has been a growing demand in recent years for individuals and companies to encrypt data and store encrypted data on a server. In this study, we introduce two cryptographic primitives, Convergent Encryption and Message-Locked Encryption, which enable deduplication of encrypted data between clients and a storage server. We analyze the security of these schemes in terms of dictionary and poison attacks. In addition, we introduce deduplication systems that can be implemented in real cloud storage, which is a practical application environment, and describes the proof of ownership on client-side deduplication.

• Journal of Korea Multimedia Society
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• v.18 no.11
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• pp.1332-1341
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• 2015

This paper proposes a novel reversible secret sharing scheme using AES algorithm in encrypted images. In the proposed scheme, a role of the dealer is divided into an image provider and a data hider. The image provider encrypts the cover image with a shared secret key and sends it to the dealer. The dealer embeds the secret data into the encrypted image and transmits encrypted shadow images to the corresponding participants. We utilize Galois polynomial arithmetic operation over 2⁸ and the coefficient of the higher-order term is fixed to one in order to prevent the overflow. In experimental results, we demonstrate that the PSNR is sustained close to 44dB and the embedding capacity is 524,288 bits.

• ETRI Journal
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• v.36 no.2
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• pp.325-328
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• 2014

A modified version of Zhang's reversible data hiding method in encrypted images is proposed in this letter. To make full use of spatial correlation in natural images, the former idea of block division is thoroughly abandoned, whereas the random diffusion strategy is used. Additionally, the fluctuation measurement of pixels containing embedded data is improved by accurate prediction. The experiment results reveal that our proposed method is superior to both Zhang's method and the later improved version proposed by Hong and others.

• ETRI Journal
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• v.38 no.1
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• pp.159-163
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• 2016

Block compressed sensing (BCS) is widely used in image sampling and is an efficient, effective technique. Through the use of BCS, an image can be simultaneously compressed and encrypted. In this paper, a novel reversible data hiding (RDH) method is proposed to embed additional data into BCS images. The proposed method is the first RDH method of its kind for BCS images. Results demonstrate that our approach performs better compared with other state-of-the-art RDH methods on encrypted images.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.11
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• pp.5692-5716
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• 2019

One of the best means to safeguard the confidentiality, security, and privacy of an image within the IoT-Cloud is through encryption. However, looking through encrypted data is a difficult process. Several techniques for searching encrypted data have been devised, but certain security solutions may not be used in IoT-Cloud because such solutions are not lightweight. We propose a lightweight scheme that can perform a content-based search of encrypted images, namely EEIRI. In this scheme, the images are represented using local features. We develop and validate a secure scheme for measuring the Euclidean distance between two descriptor sets. To improve the search efficiency, we employ the k-means clustering technique to construct a searchable tree-based index. Our index construction process ensures the privacy of the stored data and search requests. When compared with more familiar techniques of searching images over plaintexts, EEIRI is considered to be more efficient, demonstrating a higher search cost of 7% and a decrease in search accuracy of 1.7%. Numerous empirical investigations are carried out in relation to real image collections so as to evidence our work.

• Journal of KIISE
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• v.43 no.12
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• pp.1437-1457
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• 2016

In outsourced databases, the cloud provides an authorized user with querying services on the outsourced database. However, sensitive data, such as financial or medical records, should be encrypted before being outsourced to the cloud. Meanwhile, k-Nearest Neighbor (kNN) query is the typical query type which is widely used in many fields and the result of the kNN query is closely related to the interest and preference of the user. Therefore, studies on secure kNN query processing algorithms that preserve both the data privacy and the query privacy have been proposed. However, existing algorithms either suffer from high computation cost or leak data access patterns because retrieved index nodes and query results are disclosed. To solve these problems, in this paper we propose a new kNN query processing algorithm on the encrypted database. Our algorithm preserves both data privacy and query privacy. It also hides data access patterns while supporting efficient query processing. To achieve this, we devise an encrypted index search scheme which can perform data filtering without revealing data access patterns. Through the performance analysis, we verify that our proposed algorithm shows better performance than the existing algorithms in terms of query processing times.