Data Computing in Covert Domain
This paper proposes an idea of data computing in the covert domain (DCCD). We show that with information hiding some data computing tasks can be executed beneath the covers like images, audios, random data, etc. In the proposed framework, a sender hides h
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, Zichi Wang2
, and Xinpeng Zhang2
1 Shanghai Institute of Intelligent Electronics and Systems, School of Computer Science,
Fudan University, Shanghai 201203, People’s Republic of China [email protected] 2 Shanghai Institute for Advanced Communication and Data Science, Key Laboratory of Specialty Fiber Optics and Optical Access Networks, Joint International Research Laboratory of Specialty Fiber Optics and Advanced Communication, Shanghai University, Shanghai 200444, People’s Republic of China {wangzichi,xzhang}@shu.edu.cn
Abstract. This paper proposes an idea of data computing in the covert domain (DCCD). We show that with information hiding some data computing tasks can be executed beneath the covers like images, audios, random data, etc. In the proposed framework, a sender hides his source data into two covers and uploads them onto a server. The server executes computation within the stego and returns the covert computing result to a receiver. With the covert result, the receiver can extract the computing result of the source data. During the process, it is imperceptible for the server and the adversaries to obtain the source data as they are hidden in the cover. The transmission can be done over public channels. Meanwhile, since the computation is realized in the covert domain, the cloud cannot obtain the knowledge of the computing result. Therefore, the proposed idea is useful for secure computing. Keywords: Information hiding · Covert computation
1 Introduction With the development of big data and cloud computing, many security problems appear, e.g., privacy disclosure [1], data abuse [2], malicious attacks [3]. Therefore, many data protection algorithms have been proposed for data storage and computing. One important task of protection is to conceal the content of sensitive data. For example, during cloud computing the users always hope that the cloud can process the committed data without knowing its content [4]. Data encryption is one of the most effective and popular means of privacy protection [5]. However, protection by encryption would inevitably impact the utility of cloud computing. As present, the most popular approaches to achieve secure computation for cloud is signal processing in encrypted domain [6–9]. As shown in Fig. 1, a sender encrypts his source data (the sensitive information that cannot be exposed to the others) and uploads the encrypted versions to the cloud sever. The server executes computing within the encrypted data without knowing the content of source data and returns the computing © Springer Nature Singapore Pte Ltd. 2020 S. Yu et al. (Eds.): SPDE 2020, CCIS 1268, pp. 535–545, 2020. https://doi.org/10.1007/978-981-15-9129-7_37
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results to a receiver. Finally, the receiver decrypts the returned results to obtain the computation results of source data. Homomorphic encryption algorithms were proposed to achieve these goals. After encrypting the data into a ciphertext with tremendous bits, additive or multiplicative operations can be done in encrypted dom
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