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Elhassani, M., Chillali, A., Mouhib, A..  2019.  Elliptic curve and Lattice cryptosystem. 2019 International Conference on Intelligent Systems and Advanced Computing Sciences (ISACS). :1—4.

In this work, we will present a new hybrid cryptography method based on two hard problems: 1- The problem of the discrete logarithm on an elliptic curve defined on a finite local ring. 2- The closest vector problem in lattice and the conjugate problem on square matrices. At first, we will make the exchange of keys to the Diffie-Hellman. The encryption of a message is done with a bad basis of a lattice.

Long, Yihong, Cheng, Minyang.  2019.  Secret Sharing Based SM2 Digital Signature Generation using Homomorphic Encryption. 2019 15th International Conference on Computational Intelligence and Security (CIS). :252–256.
SM2 is an elliptic curve public key cryptography algorithm released by the State Cryptography Administration of China. It includes digital signature, data encryption and key exchange schemes. To meet specific application requirements, such as to protect the user's private key in software only implementation, and to facilitate secure cloud cryptography computing, secret sharing based SM2 signature generation schemes have been proposed in the literature. In this paper a new such kind of scheme based upon additively homomorphic encryption is proposed. The proposed scheme overcomes the drawback that the existing schemes have and is more secure. It is useful in various application scenarios.
Elhassani, Mustapha, Boulbot, Aziz, Chillali, Abdelhakim, Mouhib, Ali.  2019.  Fully homomorphic encryption scheme on a nonCommutative ring R. 2019 International Conference on Intelligent Systems and Advanced Computing Sciences (ISACS). :1–4.
This article is an introduction to a well known problem on the ring Fq[e] where e3=e2: Fully homomorphic encryption scheme. In this paper, we introduce a new diagram of encryption based on the conjugate problem on Fq[e] , (ESR(Fq[e])).
Tan, Li Xin, Wee, Jing Wei Shannen, Chan, Jun Rong, Soh, Wei Jie, Yap, Chern Nam.  2019.  Integrate Dragonfly Key Exchange (IETF - RFC 7664) into Arithmetic Circuit Homomorphic Encryption. 2019 IEEE 24th Pacific Rim International Symposium on Dependable Computing (PRDC). :85–851.
This is an extension of an ongoing research project on Fully Homomorphic Encryption. Arithmetic Circuit Homomorphic Encryption (ACHE) [1] was implemented based on (TFHE) Fast Fully Homomorphic Encryption over the Torus. Just like many Homomorphic Encryption methods, ACHE does not integrate with any authentication method. Thus, this was an issue that this paper attempts to resolve. This paper will focus on the implementation method of integrating RFC7664 [2] into ACHE. Next, the paper will further discuss latency incurred due to key generation, the latency of transmission of public and private keys. Last but not least, the paper will also discuss the key size generated and its significance.
Das, Bablu Kumar, Garg, Ritu.  2019.  Security of Cloud Storage based on Extended Hill Cipher and Homomorphic Encryption. 2019 International Conference on Communication and Electronics Systems (ICCES). :515–520.
Cloud computing is one of the emerging area in the business world that help to access resources at low expense with high privacy. Security is a standout amongst the most imperative difficulties in cloud network for cloud providers and their customers. In order to ensure security in cloud, we proposed a framework using different encryption algorithm namely Extended hill cipher and homomorphic encryption. Firstly user data/information is isolated into two parts which is static and dynamic data (critical data). Extended hill cipher encryption is applied over more important dynamic part where we are encrypting the string using matrix multiplication. While homomorphic encryption is applied over static data in which it accepts n number of strings as information, encode each string independently and lastly combine all the strings. The test results clearly manifests that the proposed model provides better information security.
Khan, Saif Ali, Aggarwal, R. K, Kulkarni, Shashidhar.  2019.  Enhanced Homomorphic Encryption Scheme with PSO for Encryption of Cloud Data. 2019 5th International Conference on Advanced Computing Communication Systems (ICACCS). :395–400.
Cloud computing can be described as a distributed design that is accessible to different forms of security intrusions. An encoding technique named homomorphic encoding is used for the encoding of entities which are utilized for the accession of data from cloud server. The main problems of homomorphic encoding scheme are key organization and key allocation. Because of these issues, effectiveness of homomorphic encryption approach decreases. The encoding procedure requires the generation of input, and for this, an approach named Particle swarm optimization is implemented in the presented research study. PSO algorithms are nature encouraged meta-heuristic algorithms. These algorithms are inhabitant reliant. In these algorithms, societal activities of birds and fishes are utilized as an encouragement for the development of a technical mechanism. Relying on the superiority of computations, the results are modified with the help of algorithms which are taken from arbitrarily allocated pattern of particles. With the movement of particles around the searching area, the spontaneity is performed by utilizing a pattern of arithmetical terminology. For the generation of permanent number key for encoding, optimized PSO approach is utilized. MATLAB program is used for the implementation of PSO relied homomorphic algorithm. The investigating outcomes depicts that this technique proves very beneficial on the requisites of resource exploitation and finishing time. PSO relied homomorphic algorithm is more applicable in terms of completion time and resource utilization in comparison with homomorphic algorithm.
Wade, Mamadou I., Chouikha, Mohamed, Gill, Tepper, Patterson, Wayne, Washington, Talitha M., Zeng, Jianchao.  2019.  Distributed Image Encryption Based On a Homomorphic Cryptographic Approach. 2019 IEEE 10th Annual Ubiquitous Computing, Electronics Mobile Communication Conference (UEMCON). :0686–0696.
The objective of this research is to develop a novel image encryption method that can be used to considerably increase the security of encrypted images. To solve this image security problem, we propose a distributed homomorphic image encryption scheme where the images of interest are those in the visible electromagnetic spectrum. In our encryption phase, a red green blue (RGB) image is first separated into its constituent channel images, and then the numerical intensity value of a pixel from each channel is written as a sum of smaller pixel intensity sub-values, leading to having several component images for each of the R, G, and B-channel images. A homomorphic encryption function is used to separately encrypted each of the pixel intensity sub-values in each component image using an encryption key, leading to a distributed image encryption approach. Each of the encrypted component images can be compressed before transmission and/or storage. In our decryption phase, each encrypted component image is decompressed if necessary, and then the homomorphic property of the encryption function is used to transform the product of individually encrypted pixel intensity sub-values in each encrypted component images, to the encryption of their sum, before applying the corresponding decryption function with a decryption key to recover the original pixel's intensity values for each channel image, and then recovering the original RGB image. Furthermore, a special case of an RGB image encryption and decryption where a pixel's intensity value from each channel is written as a sum of only two sub-values is implemented and simulated with a software. The resulting cipher-images are subject to a range of security tests and analyses. Results from these tests shown that our proposed homomorphic image encryption scheme is robust and can resist security attacks, as well as increases the security of the associated encrypted images. Our proposed homomorphic image encryption scheme has produced highly secure encrypted images.
Zhang, Yang, Chen, Pengfei, Hao, Long.  2019.  Research on Privacy Protection with Weak Security Network Coding for Mobile Computing. 2019 Seventh International Conference on Advanced Cloud and Big Data (CBD). :174—179.

With the rapid development of the contemporary society, wide use of smart phone and vehicle sensing devices brings a huge influence on the extensive data collection. Network coding can only provide weak security privacy protection. Aiming at weak secure feature of network coding, this paper proposes an information transfer mechanism, Weak Security Network Coding with Homomorphic Encryption (HE-WSNC), and it is integrated into routing policy. In this mechanism, a movement model is designed, which allows information transmission process under Wi-Fi and Bluetooth environment rather than consuming 4G data flow. Not only does this application reduce the cost, but also improve reliability of data transmission. Moreover, it attracts more users to participate.

Boussaha, Ryma, Challal, Yacine, Bouabdallah, Abdelmadjid.  2018.  Authenticated Network Coding for Software-Defined Named Data Networking. 2018 IEEE 32nd International Conference on Advanced Information Networking and Applications (AINA). :1115–1122.
Named Data Networking (or NDN) represents a potential new approach to the current host based Internet architecture which prioritize content over the communication between end nodes. NDN relies on caching functionalities and local data storage, such as a content request could be satisfied by any node holding a copy of the content in its storage. Due to the fact that users in the same network domain can share their cached content with each other and in order to reduce the transmission cost for obtaining the desired content, a cooperative network coding mechanism is proposed in this paper. We first formulate our optimal coding and homomorphic signature scheme as a MIP problem and we show how to leverage Software Defined Networking to provide seamless implementation of the proposed solution. Evaluation results demonstrate the efficiency of the proposed coding scheme which achieves better performance than conventional NDN with random coding especially in terms of transmission cost and security.
Nguyen-Van, Thanh, Nguyen-Anh, Tuan, Le, Tien-Dat, Nguyen-Ho, Minh-Phuoc, Nguyen-Van, Tuong, Le, Nhat-Quang, Nguyen-An, Khuong.  2019.  Scalable Distributed Random Number Generation Based on Homomorphic Encryption. 2019 IEEE International Conference on Blockchain (Blockchain). :572–579.

Generating a secure source of publicly-verifiable randomness could be the single most fundamental technical challenge on a distributed network, especially in the blockchain context. Many current proposals face serious problems of scalability and security issues. We present a protocol which can be implemented on a blockchain that ensures unpredictable, tamper-resistant, scalable and publicly-verifiable outcomes. The main building blocks of our protocol are homomorphic encryption (HE) and verifiable random functions (VRF). The use of homomorphic encryption enables mathematical operations to be performed on encrypted data, to ensure no one knows the outcome prior to being generated. The protocol requires O(n) elliptic curve multiplications and additions as well as O(n) signature signing and verification operations, which permits great scalability. We present a comparison between recent approaches to the generation of random beacons.

Baranov, Nikita, Bashkin, Mikhail, Bashkin, Vladimir.  2019.  Self-Healing Anonymous Routing in Unstable Sensor Networks. 2019 7th International Conference on Future Internet of Things and Cloud (FiCloud). :88–95.
A lightweight decentralized adaptive anonymous routing scheme is presented that combines onion routing for the initial global route request and threshold-based secret sharing for the subsequent local route tuning/healing. The encrypted propagation of the partial routes information allows to handle minor network topology changes locally, without new route requests and with a limited deanonymization of participants. The intermediate node can discover/decrypt the local routing data only together with its designated neigbour (threshold-based secret sharing is used) and only in the event of a topology change.
Nateghizad, Majid, Veugen, Thijs, Erkin, Zekeriya, Lagendijk, Reginald L..  2018.  Secure Equality Testing Protocols in the Two-Party Setting. Proceedings of the 13th International Conference on Availability, Reliability and Security. :3:1-3:10.

Protocols for securely testing the equality of two encrypted integers are common building blocks for a number of proposals in the literature that aim for privacy preservation. Being used repeatedly in many cryptographic protocols, designing efficient equality testing protocols is important in terms of computation and communication overhead. In this work, we consider a scenario with two parties where party A has two integers encrypted using an additively homomorphic scheme and party B has the decryption key. Party A would like to obtain an encrypted bit that shows whether the integers are equal or not but nothing more. We propose three secure equality testing protocols, which are more efficient in terms of communication, computation or both compared to the existing work. To support our claims, we present experimental results, which show that our protocols achieve up to 99% computation-wise improvement compared to the state-of-the-art protocols in a fair experimental set-up.

Kee, Ruitao, Sie, Jovan, Wong, Rhys, Yap, Chern Nam.  2019.  Arithmetic Circuit Homomorphic Encryption and Multiprocessing Enhancements. 2019 International Conference on Cyber Security and Protection of Digital Services (Cyber Security). :1–5.
This is a feasibility study on homomorphic encryption using the TFHE library [1] in daily computing using cloud services. A basic set of arithmetic operations namely - addition, subtraction, multiplication and division were created from the logic gates provide. This research peeks into the impact of logic gates on these operations such as latency of the gates and the operation itself. Multiprocessing enhancement were done for multiplication operation using MPI and OpenMP to reduce latency.
Sharma, Mukesh Kumar, Somwanshi, Devendra.  2018.  Improvement in Homomorphic Encryption Algorithm with Elliptic Curve Cryptography and OTP Technique. 2018 3rd International Conference and Workshops on Recent Advances and Innovations in Engineering (ICRAIE). :1–6.
Cloud computing is a technology is where client require not to stress over the expense of equipment establishment and their support cost. Distributed computing is presently turned out to be most prominent innovation on account of its accessibility, ease and some different elements. Yet, there is a few issues in distributed computing, the principle one is security in light of the fact that each client store their valuable information on the system so they need their information ought to be shielded from any unapproved get to, any progressions that isn't done for client's benefit. To take care of the issue of Key administration, Key Sharing different plans have been proposed. The outsider examiner is the plan for key administration and key sharing. The primary preferred standpoint of this is the cloud supplier can encourage the administration which was accessible by the customary outsider evaluator and make it trustful. The outsider examining plan will be fizzled, if the outsider's security is endangered or of the outsider will be malignant. To take care of the issue, there is another modular for key sharing and key administration in completely Homomorphic Encryption conspire is outlined. In this paper we utilized the symmetric key understanding calculation named Diffie Hellman to make session key between two gatherings who need to impart and elliptic curve cryptography to create encryption keys rather than RSA and have utilized One Time Password (OTP) for confirming the clients.
Zhang, Zhenyong, Wu, Junfeng, Yau, David, Cheng, Peng, Chen, Jiming.  2018.  Secure Kalman Filter State Estimation by Partially Homomorphic Encryption. 2018 ACM/IEEE 9th International Conference on Cyber-Physical Systems (ICCPS). :345–346.
Recently, the security of state estimation has been attracting significant research attention due to the need for trustworthy situation awareness in emerging (e.g., industrial) cyber-physical systems. In this paper, we investigate secure estimation based on Kalman filtering (SEKF) using partially homomorphically encrypted data. The encryption will enhance the confidentiality not only of data transmitted in the communication network, but also key system information required by the estimator. We use a multiplicative homomorphic encryption scheme, but with a modified decryption algorithm. SEKF is able to conceal comprehensive information (i.e., system parameters, measurements, and state estimates) aggregated at the sink node of the estimator, while retaining the effectiveness of normal Kalman filtering. Therefore, even if an attacker has gained unauthorized access to the estimator and associated communication channels, he will not be able to obtain sufficient knowledge of the system state to guide the attack, e.g., ensure its stealthiness. We present an implementation structure of the SEKF to reduce the communication overhead compared with traditional secure multiparty computation (SMC) methods. Finally, we demonstrate the effectiveness of the SEKF on an IEEE 9-bus power system.
Morita, Kazunari, Yoshimura, Hiroki, Nishiyama, Masashi, Iwai, Yoshio.  2018.  Protecting Personal Information using Homomorphic Encryption for Person Re-identification. 2018 IEEE 7th Global Conference on Consumer Electronics (GCCE). :166–167.
We investigate how to protect features corresponding to personal information using homomorphic encryption when matching people in several camera views. Homomorphic encryption can compute a distance between features without decryption. Thus, our method is able to use a computing server on a public network while protecting personal information. To apply homomorphic encryption, our method uses linear quantization to represent each element of the feature as integers. Experimental results show that there is no significant difference in the accuracy of person re-identification with or without homomorphic encryption and linear quantization.
Hallman, Roger A., Laine, Kim, Dai, Wei, Gama, Nicolas, Malozemoff, Alex J., Polyakov, Yuriy, Carpov, Sergiu.  2018.  Building Applications with Homomorphic Encryption. Proceedings of the 2018 ACM SIGSAC Conference on Computer and Communications Security. :2160–2162.
In 2009, Craig Gentry introduced the first "fully" homomorphic encryption scheme allowing arbitrary circuits to be evaluated on encrypted data. Homomorphic encryption is a very powerful cryptographic primitive, though it has often been viewed by practitioners as too inefficient for practical applications. However, the performance of these encryption schemes has come a long way from that of Gentry's original work: there are now several well-maintained libraries implementing homomorphic encryption schemes and protocols demonstrating impressive performance results, alongside an ongoing standardization effort by the community. In this tutorial we survey the existing homomorphic encryption landscape, providing both a general overview of the state of the art, as well as a deeper dive into several of the existing libraries. We aim to provide a thorough introduction to homomorphic encryption accessible by the broader computer security community. Several of the presenters are core developers of well-known publicly available homomorphic encryption libraries, and organizers of the homomorphic encryption standardization effort \textbackslashtextbackslashhref This tutorial is targeted at application developers, security researchers, privacy engineers, graduate students, and anyone else interested in learning the basics of modern homomorphic encryption.The tutorial is divided into two parts: Part I is accessible by everyone comfortable with basic college-level math; Part II will cover more advanced topics, including descriptions of some of the different homomorphic encryption schemes and libraries, concrete example applications and code samples, and a deeper discussion on implementation challenges. Part II requires the audience to be familiar with modern C++.
Akavia, Adi, Feldman, Dan, Shaul, Hayim.  2018.  Secure Search on Encrypted Data via Multi-Ring Sketch. Proceedings of the 2018 ACM SIGSAC Conference on Computer and Communications Security. :985–1001.
We consider the secure search problem of retrieving from an unsorted data cost=(x\_1,...,xm) an item (i,xi) matching a given lookup value l (for a generic matching criterion either hardcoded or given as part of the query), where both input and output are encrypted by a Fully Homomorphic Encryption (FHE). The secure search problem is central in applications of secure outsourcing to an untrusted party ("the cloud"). Prior secure search algorithms on FHE encrypted data are realized by polynomials of degree Ømega(m), evaluated in Ømega(log m) sequential homomorphic multiplication steps (ie., multiplicative depth) even using an unbounded number of parallel processors. This is too slow with current FHE implementations, especially as the size of the array grows. We present the first secure search algorithm that is realized by a polynomial of logarithmic degree, log3 m, evaluated in O(log log m) sequential homomorphic multiplication steps (ie., multiplicative depth) using m parallel processors. We implemented our algorithm in an open source library based on HElib and ran experiments on Amazon's EC2 cloud with up to 100 processors. Our experiments show that we can securely search in m= millions of entries in less than an hour on a standard EC2 64-cores machine. We achieve our result by: (1) Employing modern data summarization techniques known as sketching for returning as output (the encryption of) a short sketch C from which the matching item (i,xi) can be decoded in time polynomial in log m. (2) Designing for this purpose a novel sketch that returns the first strictly-positive entry in a (not necessarily sparse) array of non-negative integers; this sketch may be of independent interest. (3) Suggesting a multi-ring evaluation of FHE for degree reduction from linear to logarithmic.
Loyka, Kyle, Zhou, He, Khatri, Sunil P..  2018.  A Homomorphic Encryption Scheme Based on Affine Transforms. Proceedings of the 2018 on Great Lakes Symposium on VLSI. :51–56.
As more businesses and consumers move their information storage to the cloud, the need to protect sensitive data is higher than ever. Using encryption, data access can be restricted to only authorized users. However, with standard encryption schemes, modifying an encrypted file in the cloud requires a complete file download, decryption, modification, and upload. This is cumbersome and time-consuming. Recently, the concept of homomorphic computing has been proposed as a solution to this problem. Using homomorphic computation, operations may be performed directly on encrypted files without decryption, hence avoiding exposure of any sensitive user information in the cloud. This also conserves bandwidth and reduces processing time. In this paper, we present a homomorphic computation scheme that utilizes the affine cipher applied to the ASCII representation of data. To the best of the authors» knowledge, this is the first use of affine ciphers in homomorphic computing. Our scheme supports both string operations (encrypted string search and concatenation), as well as arithmetic operations (encrypted integer addition and subtraction). A design goal of our proposed homomorphism is that string data and integer data are treated identically, in order to enhance security.
Dong, Yao, Milanova, Ana, Dolby, Julian.  2018.  SecureMR: Secure Mapreduce Computation Using Homomorphic Encryption and Program Partitioning. Proceedings of the 5th Annual Symposium and Bootcamp on Hot Topics in the Science of Security. :4:1–4:13.
In cloud computing customers upload data and computation to cloud providers. As they upload their data to the cloud provider, they typically give up data confidentiality. We develop SecureMR, a system that analyzes and transforms MapReduce programs to operate over encrypted data. SecureMR makes use of partially homomorphic encryption and a trusted client. We evaluate SecureMR on a set of complex computation-intensive MapReduce benchmarks.
Chen, Hao, Huang, Zhicong, Laine, Kim, Rindal, Peter.  2018.  Labeled PSI from Fully Homomorphic Encryption with Malicious Security. Proceedings of the 2018 ACM SIGSAC Conference on Computer and Communications Security. :1223–1237.
Private Set Intersection (PSI) allows two parties, the sender and the receiver, to compute the intersection of their private sets without revealing extra information to each other. We are interested in the unbalanced PSI setting, where (1) the receiver's set is significantly smaller than the sender's, and (2) the receiver (with the smaller set) has a low-power device. Also, in a Labeled PSI setting, the sender holds a label per each item in its set, and the receiver obtains the labels from the items in the intersection. We build upon the unbalanced PSI protocol of Chen, Laine, and Rindal (CCS\textbackslashtextasciitilde2017) in several ways: we add efficient support for arbitrary length items, we construct and implement an unbalanced Labeled PSI protocol with small communication complexity, and also strengthen the security model using Oblivious Pseudo-Random Function (OPRF) in a pre-processing phase. Our protocols outperform previous ones: for an intersection of 220 and \$512\$ size sets of arbitrary length items our protocol has a total online running time of just \$1\$\textbackslashtextasciitildesecond (single thread), and a total communication cost of 4 MB. For a larger example, an intersection of 228 and 1024 size sets of arbitrary length items has an online running time of \$12\$ seconds (multi-threaded), with less than 18 MB of total communication.
Ugwuoke, Chibuike, Erkin, Zekeriya, Lagendijk, Reginald L..  2018.  Secure Fixed-Point Division for Homomorphically Encrypted Operands. Proceedings of the 13th International Conference on Availability, Reliability and Security. :33:1–33:10.

Due to privacy threats associated with computation of outsourced data, processing data on the encrypted domain has become a viable alternative. Secure computation of encrypted data is relevant for analysing datasets in areas (such as genome processing, private data aggregation, cloud computations) that require basic arithmetic operations. Performing division operation over-all encrypted inputs has not been achieved using homomorphic schemes in non-interactive modes. In interactive protocols, the cost of obtaining an encrypted quotient (from encrypted values) is computationally expensive. To the best of our knowledge, existing homomorphic solutions on encrypted division are often relaxed to consider public or private divisor. We acknowledge that there are other techniques such as secret sharing and garbled circuits adopted to compute secure division, but we are interested in homomorphic solutions. We propose an efficient and interactive two-party protocol that computes the fixed-point quotient of two encrypted inputs, using an efficient and secure comparison protocol as a sub-protocol. Our proposal provides a computational advantage, with a linear complexity in the digit precision of the quotient. We provide proof of security in the universally composable framework and complexity analyses. We present experimental results for two cryptosystem implementations in order to compare performance. An efficient prototype of our protocol is implemented using additive homomorphic scheme (Paillier), whereas a non-efficient fully-homomorphic scheme (BGV) version is equally presented as a proof of concept and analyses of our proposal.

Kunihiro, Noboru, Lu, Wen-jie, Nishide, Takashi, Sakuma, Jun.  2018.  Outsourced Private Function Evaluation with Privacy Policy Enforcement. 2018 17th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/ 12th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE). :412–423.
We propose a novel framework for outsourced private function evaluation with privacy policy enforcement (OPFE-PPE). Suppose an evaluator evaluates a function with private data contributed by a data contributor, and a client obtains the result of the evaluation. OPFE-PPE enables a data contributor to enforce two different kinds of privacy policies to the process of function evaluation: evaluator policy and client policy. An evaluator policy restricts entities that can conduct function evaluation with the data. A client policy restricts entities that can obtain the result of function evaluation. We demonstrate our construction with three applications: personalized medication, genetic epidemiology, and prediction by machine learning. Experimental results show that the overhead caused by enforcing the two privacy policies is less than 10% compared to function evaluation by homomorphic encryption without any privacy policy enforcement.
Yagoub, Mohammed Amine, Laouid, Abdelkader, Kazar, Okba, Bounceur, Ahcène, Euler, Reinhardt, AlShaikh, Muath.  2018.  An Adaptive and Efficient Fully Homomorphic Encryption Technique. Proceedings of the 2Nd International Conference on Future Networks and Distributed Systems. :35:1–35:6.

The huge amount of generated data offers special advantages mainly in dynamic and scalable systems. In fact, the data generator entities need to share the generated data with each other which leads to the use of cloud services. A cloud server is considered as an untrusted entity that offers many advantages such as large storing space, computation speed... etc. Hence, there is a need to cope with how to protect the stored data in the cloud server by proposing adaptive solutions. The main objective is how to provide an encryption scheme allowing the user to maintains some functions such as addition, multiplication and to preserve the order on the encrypted cloud data. Many algorithms and techniques are designed to manipulate the stored encrypted cloud data. This paper presents an adaptive and efficient fully homomorphic encryption technique to protect the user's data stored in the cloud, where the cloud server executes simple operations.

Chen, D., Chen, W., Chen, J., Zheng, P., Huang, J..  2018.  Edge Detection and Image Segmentation on Encrypted Image with Homomorphic Encryption and Garbled Circuit. 2018 IEEE International Conference on Multimedia and Expo (ICME). :1-6.

Edge detection is one of the most important topics of image processing. In the scenario of cloud computing, performing edge detection may also consider privacy protection. In this paper, we propose an edge detection and image segmentation scheme on an encrypted image with Sobel edge detector. We implement Gaussian filtering and Sobel operator on the image in the encrypted domain with homomorphic property. By implementing an adaptive threshold decision algorithm in the encrypted domain, we obtain a threshold determined by the image distribution. With the technique of garbled circuit, we perform comparison in the encrypted domain and obtain the edge of the image without decrypting the image in advanced. We then propose an image segmentation scheme on the encrypted image based on the detected edges. Our experiments demonstrate the viability and effectiveness of the proposed encrypted image edge detection and segmentation.