Biblio

There are various Lightweight Block Ciphers (LBC) nowadays that exist to meet the demand on security requirements of the current trend in computing world, the application in the resource-constrained devices, and the Internet of Things (IoT) technologies. One way to evaluate these LBCs is to conduct a performance analysis. Performance evaluation parameters seek appropriate value such as encryption time, security level, scalability, and flexibility. Like SIMECK block cipher whose algorithm design was anchored with the SIMON and SPECK block ciphers were efficient in security and performance, there is a need to revisit its design. This paper aims to present a comparative study on the performance analysis of the enhanced round function of the SIMECK Family block cipher. The enhanced ARX structure of the round function on the three variants shows an efficient performance over the original algorithm in different simulations using the following methods of measurement; avalanche effect, runtime performance, and brute-force attack. Its recommended that the enhanced round function of the SIMECK family be evaluated by different security measurements and attacks.

Benchmarking is an important measure for companies to investigate their performance and to increase efficiency. As companies usually are reluctant to provide their key performance indicators (KPIs) for public benchmarks, privacy-preserving benchmarking systems are required. In this paper, we present an enhanced privacy-preserving benchmarking protocol, which we implemented and evaluated based on the real-world scenario of product cost optimisation. It is based on homomorphic encryption and enables cloud-based KPI comparison, providing a variety of statistical measures. The theoretical and empirical evaluation of our benchmarking system underlines its practicability.

The growing popularity of Android and the increasing amount of sensitive data stored in mobile devices have lead to the dissemination of Android ransomware. Ransomware is a class of malware that makes data inaccessible by blocking access to the device or, more frequently, by encrypting the data; to recover the data, the user has to pay a ransom to the attacker. A solution for this problem is to backup the data. Although backup tools are available for Android, these tools may be compromised or blocked by the ransomware itself. This paper presents the design and implementation of RANSOMSAFEDROID, a TrustZone based backup service for mobile devices. RANSOMSAFEDROID is protected from malware by leveraging the ARM TrustZone extension and running in the secure world. It does backup of files periodically to a secure local persistent partition and pushes these backups to external storage to protect them from ransomware. Initially, RANSOMSAFEDROID does a full backup of the device filesystem, then it does incremental backups that save the changes since the last backup. As a proof-of-concept, we implemented a RANSOMSAFEDROID prototype and provide a performance evaluation using an i.MX53 development board.

Cloud Computing is one of the large and essential environment now a days to work for the storage collection and privacy preserve to that data. Cloud data security is most important and major concern for the client while use of the cloud services provided by the different service providers. There can be some major security concern and conflicts between the client and the service provider. To get out from those issues, a third party auditor uses as an auditor for assurance of data in the environment. Storage systems for the cloud has many fundamental challenges still today. All basic as well critical challenges among which storage space and security is generally the top concern in the cloud environment. To give the appropriate security issues we have proposed third party authentication system. The cloud not only for the simplified data storage but also secure data acquisition in cloud environment. At last we have perform different security analysis as well performance analysis. It give the results that proposed scheme has significant increases in efficiency for maintaining highly secure data storage and acquisition. The proposed method also helps to minimize the cost in environment and also increases communication efficiency in the cloud environment.

Using heterogeneous clouds has been considered to improve performance of big-data analytics for healthcare platforms. However, the problem of the delay when transferring big-data over the network needs to be addressed. The purpose of this paper is to analyze and compare existing cloud computing environments (PaaS, IaaS) in order to implement middleware services. Understanding the differences and similarities between cloud technologies will help in the interconnection of healthcare platforms. The paper provides a general overview of the techniques and interfaces for cloud computing middleware services, and proposes a cloud architecture for healthcare. Cloud middleware enables heterogeneous devices to act as data sources and to integrate data from other healthcare platforms, but specific APIs need to be developed. Furthermore, security and management problems need to be addressed, given the heterogeneous nature of the communication and computing environment. The present paper fills a gap in the electronic healthcare register literature by providing an overview of cloud computing middleware services and standardized interfaces for the integration with medical devices.