In this paper, we define and explore proofs of retrievability (PORs). A POR scheme enables an archive or back-up service (prover) to produce a concise proof that a user (verifier) can retrieve a target file F, that is, that the archive retains and reliably transmits file data sufficient for the user to recover F in its entirety.A POR may be viewed as a kind of cryptographic proof of knowledge (POK), but one specially designed to handle a large file (or bitstring) F. We explore POR protocols here in which the communication costs, number of memory accesses for the prover, and storage requirements of the user (verifier) are small parameters essentially independent of the length of F. In addition to proposing new, practical POR constructions, we explore implementation considerations and optimizations that bear on previously explored, related schemes.In a POR, unlike a POK, neither the prover nor the verifier need actually have knowledge of F. PORs give rise to a new and unusual security definition whose formulation is another contribution of our work.We view PORs as an important tool for semi-trusted online archives. Existing cryptographic techniques help users ensure the privacy and integrity of files they retrieve. It is also natural, however, for users to want to verify that archives do not delete or modify files prior to retrieval. The goal of a POR is to accomplish these checks without users having to download the files themselves. A POR can also provide quality-of-service guarantees, i.e., show that a file is retrievable within a certain time bound.

PORs: Proofs of Retrievability for Large Files

The coronavirus disease (COVID-19) pandemic has affected the world in an unexpected manner The human race is battling against the pandemic while schools, universities, industries, hospitals, and governments are seeking new methods and technologies to seamlessly continue their usual operations In response, this article presents how 5G and Internet of Things (IoT) related technologies can be efficiently utilized and developed to fight against the COVID-19 pandemic Several use-cases on how 5G and IoT can be enablers to provide innovative solutions in the areas of telehealth, contact tracing, education, retail and supply chains, e-government/ remote office/ information sharing, smart manufacturing and factory automation, e-tourism, and entertainment are presented along with their technical requirements and challenges It is envisaged that the proposed solutions will be instrumental to facilitate the usual lifestyle, work, and other day-to-day activities of humans in the postpandemic world

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The Fight Against the COVID-19 Pandemic With 5G Technologies

Virtual reality and mixed reality for second chance tourism

Internet of Things (IoT) provides a strong platform to connect objects to the Internet for facilitating Machine to Machine (M2M) communication and transferring data using standard network protocols like TCP/IP. IoT is gaining rapidly day by day and till date, billions of devices are already connected and in the coming few years, the number can even touch trillions. With consistent advancements, lots of areas like Military, Agriculture, Industry, Healthcare, Robotics, Nanotechnology are adapting IoT for advanced solutions. The research paper proposes a comprehensive view of the new concept of IoT especially proposed for robotics i.e. Internet of Robotic Things (IoRT). IoRT is a mix of diverse technologies like Cloud Computing, Artificial Intelligence (AI), Machine Learning and Internet of Things (IoT). The paper also discusses architecture which plays a significant role in design of Multi-Role Robotic Systems for IoRT. In addition to this, enlists technologies behind IoRT, applications of IoRT and existing robotic systems based on Humanoid, Mobile, Flying and Swarm envisaged for future IoRT systems. The paper provides a strong base for researchers to envision the concept of IoRT and enable them to think out-of-the-box to design and implement IoRT based robotic systems in real-world applications.

Internet of Robotic Things: Driving Intelligent Robotics of Future - Concept, Architecture, Applications and Technologies

Originality/value: To the best of the authors’ knowledge, this chapter presents the first systematic and in-depth review of RAISA technologies in the restaurant industry.

Robots, Artificial Intelligence, and Service Automation in Restaurants

Virtual Reality and Augmented Reality, these days, is offering many useful applications that is attracting greater attention from tourism researchers and professionals. As, AR and VR technologies are evolving, the number of scientific applications is also at increase. VR and AR are proving their worth especially when planning, marketing, education, tourist sport preservation coming to light. The aim of this research paper is to highlight top technologies for Tourism and Hospitality with regard to AR and VR.

Virtual Reality (VR) & Augmented Reality (AR) technologies for tourism and hospitality industry

Objectives: The present research work generally focuses on predicting diseases from the lung disease test by using data mining techniques for spirometry data. Methods/Statistical Analysis: Spirometry is used to create baseline lung function, check out dyspnea, disclose pulmonary disease, watching effects of therapies used to treat respiratory disease, calculate respiratory impairment, evaluate operative risk, and performs surveillance for occupational-relevant lung diseases. Pulmonary function tests are used to find out lung capacity, based on which the many of the lung diseases can be identified. In this research work, a combination of k-means clustering algorithm and Decision tree algorithm was developed. From the results investigation, it is known that the proposed aggregated k-means algorithm and decision tree algorithm for spirometry data is better which compared to other algorithms such as Genetic algorithm, classifier training algorithm, and neural network based classification algorithms. Findings: Existing algorithms are unable to handle noisy data and also with Failure occurrence for a nonlinear data set. It should not classify the data set based on their input attributes. Prediction is not possible for existing system. Applications/Improvement: Spirometry data which is used to predict the lung capacity using Aggregated K-means and Decision tree algorithm. Our proposed approach is evaluated for each dataset accordingly.

Aggregated K Means Clustering and Decision Tree Algorithm for Spirometry Data

Objectives: Different user can access the same data repeatedly and trying to store it in the memory of the cloud server. Due to this there is a problem of maintaining the storage space and bandwidth. The main purpose of this study is how the data is secured, whether the authorized person is accessing the data or not and finally to check whether same data is repeatedly stored in the memory to avoid duplication of the data. Methods: In deduplication, to guard the confidentiality of sensitive information, it's encrypted/decrypted by the planned convergent coding technique before outsourcing for higher protection of knowledge security. Findings: The convergent encryption method and open authorization protocol and deduplication are combined together and check the data for deduplication in a secured way. The possibilities of using other algorithms are also considered for further implementation.

Effectuation of Secure Authorized Deduplication in Hybrid Cloud

Objectives : To be familiar with the kinds of coronary illness, and information mining procedures to fight them. Methods/Statistical analysis : To handle this, data mining concepts and techniques used were discussed to discover hidden patterns from medical domain. Findings : The purpose of predictions in data mining is to discover trends in patient data through patterns generation to improve the health strategy. The algorithms presented here are with a specific end goal to anticipate the coronary illness which includes some constraint.

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Survey on Heart Disease Prediction System Based on Data Mining Techniques

The objective of this paper is to separate the audit business related in the field of watermarking concentrating solely on restorative picture watermarking. Medicinal imaging has affected decidedly the social insurance framework around the globe by helping specialists perform visual diagnostics of the human body. One of the broadly utilized applications is to shield the patient's therapeutic history from unapproved individuals. It implants the watermark like patient's data and specialist's mark in host's restorative picture for telemedicine applications. It can be additionally utilized for confirmation if tolerant lost his/her picture. Watermarking in therapeutic pictures is regularly utilized for content verification, viable information circulation and administration, stockpiling, security, safe filing, controlled get to recovery and captioning. Most of the works are on the alter recognition of the pictures and inserting of the Electronics Patient Record (EPR) information in the medicinal.

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G. Suseendran

Papers

Virtual Reality (VR) & Augmented Reality (AR) technologies for tourism and hospitality industry

Aggregated K Means Clustering and Decision Tree Algorithm for Spirometry Data

Effectuation of Secure Authorized Deduplication in Hybrid Cloud

Survey on Heart Disease Prediction System Based on Data Mining Techniques

A Review of Watermarking Requirements, Techniques, Documents, Human Perception and Applications for Medical Images