A new technique for the construction of confusion component based on inverse LA-semigroups and its application in steganography

The present article introduced a novel idea for information hiding namely steganography. We have used new notions for the construction of the nonlinear component for block cipher based on inverse LA-semigroups. This nonlinear component fundamentally provides confidentiality in the proposed steganographic algorithm. The construction of the algorithm is fundamentally twofold. Firstly, we have constructed a novel scheme to design confusion component namely substitution box (S-box). Secondly, we have utilized the anticipated nonlinear component in digital steganography. The suggested algorithm is tested for different standard digital images. The authentication of the proposed algorithm is confirmed through statistical analysis.

     

Big Data Analytics in Healthcare——A Systematic Literature Review and Roadmap for Practical Implementation

The advent of healthcare information management systems(HIMSs)continues to produce large volumes of healthcare data for patient care and compliance and regulatory requirements at a global scale.Analysis of this big data allows for boundless potential outcomes for discovering knowledge.Big data analytics(BDA)in healthcare can,for instance,help determine causes of diseases,generate effective diagnoses,enhance Qo S guarantees by increasing efficiency of the healthcare delivery and effectiveness and viability of treatments,generate accurate predictions of readmissions,enhance clinical care,and pinpoint opportunities for cost savings.However,BDA implementations in any domain are generally complicated and resource-intensive with a high failure rate and no roadmap or success strategies to guide the practitioners.In this paper,we present a comprehensive roadmap to derive insights from BDA in the healthcare(patient care)domain,based on the results of a systematic literature review.We initially determine big data characteristics for healthcare and then review BDA applications to healthcare in academic research focusing particularly on No SQL databases.We also identify the limitations and challenges of these applications and justify the potential of No SQL databases to address these challenges and further enhance BDA healthcare research.We then propose and describe a state-of-the-art BDA architecture called Med-BDA for healthcare domain which solves all current BDA challenges and is based on the latest zeta big data paradigm.We also present success strategies to ensure the working of Med-BDA along with outlining the major benefits of BDA applications to healthcare.Finally,we compare our work with other related literature reviews across twelve hallmark features to justify the novelty and importance of our work.The aforementioned contributions of our work are collectively unique and clearly present a roadmap for clinical administrators,practitioners and professionals to successfully implement BDA initiatives in their organizations.     

Design of backtracking search heuristics for parameter estimation of power signals

Neural Computing and Applications - This study presents a novel implementation of evolutionary heuristics through backtracking search optimization algorithm (BSA) for accurate, efficient and robust...     

A dynamic variability management approach working with agile product line engineering practices for reusing features

The Journal of Supercomputing - Agile software development (ASD) and software product line (SPL) have shown significant benefits for software engineering processes and practices. Although both...     

A survey on search results diversification techniques

The quantity of information placed on the web has been greater than before and is increasing rapidly day by day. Searching through the huge amount of data and finding the most relevant and useful result set involves searching, ranking, and presenting the results. Most of the users probe into the top few results and neglect the rest. In order to increase user’s satisfaction, the presented result set should not only be relevant to the search topic, but should also present a variety of perspectives, that is, the results should be different from one another. The effectiveness of web search and the satisfaction of users can be enhanced through providing various results of a search query in a certain order of relevance and concern. The technique used to avoid presenting similar, though relevant, results to the user is known as a diversification of search results. This article presents a survey of the approaches used for search result diversification. To this end, this article not only provides a technical survey of existing diversification techniques, but also presents a taxonomy of diversification algorithms with respect to the types of search queries.     

Ellipsoidal neighbourhood outlier factor for distributed anomaly detection in resource constrained networks

Anomaly detection in resource constrained wireless networks is an important challenge for tasks such as intrusion detection, quality assurance and event monitoring applications. The challenge is to detect these interesting events or anomalies in a timely manner, while minimising energy consumption in the network. We propose a distributed anomaly detection architecture, which uses multiple hyperellipsoidal clusters to model the data at each sensor node, and identify global and local anomalies in the network. In particular, a novel anomaly scoring method is proposed to provide a score for each hyperellipsoidal model, based on how remote the ellipsoid is relative to their neighbours. We demonstrate using several synthetic and real datasets that our proposed scheme achieves a higher detection performance with a significant reduction in communication overhead in the network compared to centralised and existing schemes.     

Formal analysis of seamless application execution in mobile cloud computing

Mobile cloud computing augments the resource-constrained mobile devices to run rich mobile applications by leveraging the cloud resources and services. Compute-intensive mobile apps require significant communication resources for migrating the code from mobile devices to the cloud. For such apps, distributed application execution frameworks (DAEF) have been proposed in the literature. These frameworks either migrate the mobile app code during runtime or keep the app synchronized with another remotely executed app on the cloud. Frameworks also support mobile app live migration to cater for compute node mobility. One key research question arises is how successful are these DAEFs in achieving the seamless application execution under various network conditions? The answer to this question entails formal analysis of the DAEFs to determine the realistic bounds on propagation delay, bandwidth and application interaction with mobile device for various types and sizes of apps. In this research, we apply formal analysis techniques to define the execution time of the app and the time required for code migration. We also define three conditions for seamless application execution. Given realistic values for processor speed, application executable size, possible number of executed instructions, network propagation delay and transmission delay, we show what components of the mobile app need to be migrated during execution to the cloud. Finally, we compute realistic bounds for the app size (that can be executed seamlessly) based on important features which include cloud and device resources, bandwidth and latency profile.     

Security flaws in a recent RFID delegation protocol

Radio frequency identification (RFID) tag delegation enables a centralized back-end server to delegate the right to identify and authenticate a tag to specified readers. This should be used to mitigate the computational load on the server side and also to solve the issues in terms of latency and dependency on network connectivity. In this study, we describe a basic RFID delegation architecture and then under this model, we investigate the security of an RFID delegation protocol: Song Mitchell delegation (SMD), which is recently proposed by Song and Mitchell. We point out security flaws that have gone unnoticed in the design and present two attacks namely, a tag impersonation attack and a desynchronization attack against it. We also discover a subtle flaw by which a delegated entity can still keep its delegation rights after the expire of them—this infringes security policy of the scheme. More precisely, we show that the protocol will be still vulnerable to previously mentioned attacks, even if the back-end server ends the delegation right of a delegated reader and update the secrets of the delegated tags. To counteract such flaws, we improve the SMD protocol with a stateful variant so that it provides the claimed security properties.     

Exploitation of Social Media for Emergency Relief and Preparedness: Recent Research and Trends

Online Social Media, such as Twitter, Facebook and WhatsApp, are important sources of real-time information related to emergency events, including both natural calamities, man-made disasters, epidemics, and so on. There has been lot of recent work on designing information systems that would be useful for aiding post-disaster relief operations, as well as for pre-disaster preparedness. A special issue on “Exploitation of Social Media for Emergency Relief and Preparedness” was conducted for the journal Information Systems Frontiers. The objective of this special issue was to present a platform for dissemination of the empirical results of various technologies for extracting vital and actionable information from social media content in disaster situations. The papers included in this issue are expected to be the stepping stones for future explorations and technical innovations towards technologies meant for utilizing various online and offline information sources for enhancing pre-disaster preparedness and post-disaster relief operations.