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 early prediction of deterioration could have an important role in supporting healthcare professionals, as an estimated 11% of deaths in hospital follow a failure to promptly recognize and treat deteriorating patients1. To achieve this goal requires predictions of patient risk that are continuously updated and accurate, and delivered at an individual level with sufficient context and enough time to act. Here we develop a deep learning approach for the continuous risk prediction of future deterioration in patients, building on recent work that models adverse events from electronic health records2–17 and using acute kidney injury—a common and potentially life-threatening condition18—as an exemplar. Our model was developed on a large, longitudinal dataset of electronic health records that cover diverse clinical environments, comprising 703,782 adult patients across 172 inpatient and 1,062 outpatient sites. Our model predicts 55.8% of all inpatient episodes of acute kidney injury, and 90.2% of all acute kidney injuries that required subsequent administration of dialysis, with a lead time of up to 48 h and a ratio of 2 false alerts for every true alert. In addition to predicting future acute kidney injury, our model provides confidence assessments and a list of the clinical features that are most salient to each prediction, alongside predicted future trajectories for clinically relevant blood tests9. Although the recognition and prompt treatment of acute kidney injury is known to be challenging, our approach may offer opportunities for identifying patients at risk within a time window that enables early treatment. A deep learning approach that predicts the risk of acute kidney injury may help to identify patients at risk of health deterioration within a time window that enables early treatment.

A clinically applicable approach to continuous prediction of future acute kidney injury

Vehicular ad hoc networks (VANETs) are becoming the most promising research topic in intelligent transportation systems, because they provide information to deliver comfort and safety to both drivers and passengers. However, unique characteristics of VANETs make security, privacy, and trust management challenging issues in VANETs’ design. This survey article starts with the necessary background of VANETs, followed by a brief treatment of main security services, which have been well studied in other fields. We then focus on an in-depth review of anonymous authentication schemes implemented by five pseudonymity mechanisms. Because of the predictable dynamics of vehicles, anonymity is necessary but not sufficient to thwart tracking an attack that aims at the drivers’ location profiles. Thus, several location privacy protection mechanisms based on pseudonymity are elaborated to further protect the vehicles’ privacy and guarantee the quality of location-based services simultaneously. We also give a comprehensive analysis on various trust management models in VANETs. Finally, considering that current and near-future applications in VANETs are evaluated by simulation, we give a much-needed update on the latest mobility and network simulators as well as the integrated simulation platforms. In sum, this paper is carefully positioned to avoid overlap with existing surveys by filling the gaps and reporting the latest advances in VANETs while keeping it self-explained.

A Survey on Recent Advances in Vehicular Network Security, Trust, and Privacy

Multi-key privacy-preserving deep learning in cloud computing

An Efficient Algorithm for Media-based Surveillance System (EAMSuS) in IoT Smart City Framework

The session initiation protocol (SIP) is an IP-based telephony authentication mechanism for multimedia big data communications over the Internet. It is used to set up, and control voice and video calls, as well as for instant messaging. One of the concerns of this kind of open-text-based protocol is the security for user authentication. The HTTP digest-based challenge-response authentication process is used in the original SIP. However, this kind of authentication procedure is insecure and a pre-existing user configuration on the remote server is required. According to the literature, several authentication mechanisms for SIP are already devised, but none of these SIPs are robust against existing security attacks. Therefore, we design a three-factor SIP (TF-SIP) for multimedia big data communications, which is robust and flexible against existing known security issues. We show that our TF-SIP is provably secure in the random oracle model. We formally verify the mutual authentication and the freshness of the agreed session key between the user and the remote server using the BAN logic analysis. We found that the communication and computation costs are low, but the storage cost is slightly higher for our TF-SIP in comparison with other SIPs.

A Provably Secure Three-Factor Session Initiation Protocol for Multimedia Big Data Communications

https://cyberleninka.org/article/n/1492040.pdf

Energy-aware hybrid fruitfly optimization for load balancing in cloud environments for EHR applications

Nowadays, access control and data security are two most critical problems with cloud computing. Access control can be defined as a procedure by which users can access data from the cloud server. At the time of accessing data, there are many problems, such as data security, high data accessing time, data lost, overhead, data redundancy, etc. In the first part of this paper, a brief discussion of fundamentals of cloud computing are presented. Moreover, all the issues of cloud computing are also discussed in this paper. Finally, future work directions have been identified for the cloud computing environment.

Cloud Computing: Fundamentals and Research Issues

The development of human being passes through several transition phases throughout the life span. The most critical phase that may influence the individuals' lifestyle is the college admission. During this phase, the students are independent and they are responsible for their own lives especially if they are far away from parental home. A healthy lifestyle is identified by regular exercises, healthy diet, and organized sleeping pattern. However, the transfer into a new environment may alternate the usual habits and cause major fluctuations in lifestyle. The students may be vulnerable to several stressful factors including inability to organize time, stress of exams and deadlines, irregular sleeping pattern, new peer's relationships, and inability to accommodate with the new surroundings. These factors may result in decreased level of physical activity and increased consumption of fast food that may lead to changes in body weight. The exposure to these changes in lifestyle may influence the well-being of individual and overall health. The aim of this study is to focus on the lifestyle of university students including the level of physical activity and type of diet followed and how it affects their weight. The result of our study, showed most of the students do not follow a certain diet, do not consider their food choices healthy and would like to take more care about their health. This is mostly due to the fact that they don't exercise as much as they like to.

Balamurugan Balusamy

Papers

A Provably Secure Three-Factor Session Initiation Protocol for Multimedia Big Data Communications

Energy-aware hybrid fruitfly optimization for load balancing in cloud environments for EHR applications

Cloud Computing: Fundamentals and Research Issues

Students university healthy lifestyle practice: quantitative analysis.

Artificial intelligence inspired energy and spectrum aware cluster based routing protocol for cognitive radio sensor networks