BackgroundWith the rapid development of cloud computing and mobile networking technologies, users tend to access their stored data from the remote cloud storage with mobile devices. The main advantage of cloud storage is its ubiquitous user accessibility and also its virtually unlimited data storage capabilities. Despite such benefits provided by the cloud, the major challenge that remains is the concern over the confidentiality and privacy of data while adopting the cloud storage services [1]. For instance, unencrypted user data stored at the remote cloud server can be vulnerable to external attacks initiated by unauthorized outsiders and internal attacks initiated by the untrustworthy cloud service providers (CSPs) [2]. There are several reports that confirm data breaches related to cloud servers, due to malicious attack, theft or internal errors [3]. This raises concern for many users/ AbstractEnsuring the cloud data security is a major concern for corporate cloud subscribers and in some cases for the private cloud users. Confidentiality of the stored data can be managed by encrypting the data at the client side before outsourcing it to the remote cloud storage server. However, once the data is encrypted, it will limit server's capability for keyword search since the data is encrypted and server simply cannot make a plaintext keyword search on encrypted data. But again we need the keyword search functionality for efficient retrieval of data. To maintain user's data confidentiality, the keyword search functionality should be able to perform over encrypted cloud data and additionally it should not leak any information about the searched keyword or the retrieved document. This is known as privacy preserving keyword search. This paper aims to study privacy preserving keyword search over encrypted cloud data. Also, we present our implementation of a privacy preserving data storage and retrieval system in cloud computing. For our implementation, we have chosen one of the symmetric key primitives due to its efficiency in mobile environments. The implemented scheme enables a user to store data securely in the cloud by encrypting it before outsourcing and also provides user capability to search over the encrypted data without revealing any information about the data or the query. Salam et al. Hum. Cent. Comput. Inf. Sci. (2015) et al. Hum. Cent. Comput. Inf. Sci. (2015) 5:19 organizations as the outsourced data might contain very sensitive personal organization/ information. RESEARCHPage 2 of 16 SalamSeveral researches have addressed the issue of ensuring confidentiality and privacy of cloud data without compromising the user functionality. Here, confidentiality refers to the secrecy of the stored data so that only the client can read the contents of the stored data. To solve the problem of confidentiality, data encryption schemes can come in handy to provide the users with some control over the secrecy of their stored data. This has been adopted by many recent researches which allow users to encrypt their data...

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Panoramic and periapical radiograph tools help dentists in diagnosing the most common dental diseases, such as dental caries. Generally, dental caries is manually diagnosed by dentists based on panoramic and periapical images. For several reasons, such as carelessness caused by heavy workload and inexperience, manual diagnosis may cause unnoticeable dental caries. Thus, computer-based intelligent vision systems supported by machine learning and image processing techniques are needed to prevent these negativities. This study proposed a novel approach for the automatic diagnosis of dental caries based on periapical images. The proposed procedure used a multi-input deep convolutional neural network ensemble (MI-DCNNE) model. Specifically, a score-based ensemble scheme was employed to increase the achievement of the proposed MI-DCNNE method. The inputs to the proposed approach were both raw periapical images and an enhanced form of it. The score fusion was carried out in the Softmax layer of the proposed multi-input CNN architecture. In the experimental works, a periapical image dataset (340 images) covering both caries and non-caries images were used for the performance evaluation of the proposed method. According to the results, it was seen that the proposed model is quite successful in the diagnosis of dental caries. The reported accuracy score is 99.13%. This result shows that the proposed MI-DCNNE model can effectively contribute to the classification of dental caries.

Grain-128AEAD is a lightweight authenticated encryption stream cipher and one of the finalists in the National Institute of Standards and Technology (NIST) Lightweight Cryptography (LWC) project. This paper provides an independent third-party analysis of Grain-128AEAD against fault attacks. We investigate the application of three differential fault attack models on Grain-128AEAD. All these attacks can recover the initial state of Grain-128AEAD. First, we demonstrate an attack using a bit-flipping fault that requires access to 2 7.80 faulty outputs to recover the initial state. Then, we demonstrate an attack with a more relaxed assumption of a random fault with a probabilistic approach. Our probabilistic random fault attack requires access to 2 11.60 faulty outputs and 2 10.45 fault injections to recover the initial state with a success rate over 99%. Both of the above two attacks are based on precise control on the fault target. Finally, we apply a random fault attack with a deterministic approach (can conclusively determine the random fault value) and using different precision controls. For the precise control, we use existing approaches that have been applied to other ciphers, such as Tiaoxin-346. We also propose a technique for less stringent precision models, such as moderate control and no control, which are more practical than the precise control. Our result indicates that the deterministic random fault attack with a precise control requires an average of 2 7.64 fault injections and a data complexity of 2 8.80 . The deterministic random fault attack with moderate control requires a weak assumption on the fault injection and hence, is the best attack presented in this paper; and is expected to require about 2 9.39 fault injections with a data complexity of about 2 12.98 . All the attacks discussed in this paper are verified experimentally.

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