Improved Verifier-Based Three-Party Password-Authenticated Key Exchange Protocol from Ideal Lattices

With the advent of large-scale social networks, two communication users need to generate session keys with the help of a remote server to communicate securely. In the existing three-party authenticated key exchange (3PAKE) protocols, users’ passwords need to be stored on the server; it cannot resist the server disclosure attack. To solve this security problem, we propose a more efficient 3PAKE protocol based on the verification element by adopting a public-key cryptosystem and approximate smooth projection hash (ASPH) function on an ideal lattice. Using the structure of separating authentication from the server, the user can negotiate the session key only after two rounds of communication. The analysis results show that it can improve the efficiency of computation and communication and resist the server disclosure attack, quantum algorithm attack, and replay attack; moreover, it has session key privacy to the server. This protocol can meet the performance requirement of the current communication network.

Live Spoofing Detection for Automatic Human Activity Recognition Applications

Human Activity Recognition (HAR) has become increasingly crucial in several applications, ranging from motion-driven virtual games to automated video surveillance systems. In these applications, sensors such as smart phone cameras, web cameras or CCTV cameras are used for detecting and tracking physical activities of users. Inevitably, spoof detection in HAR is essential to prevent anomalies and false alarms. To this end, we propose a deep learning based approach that can be used to detect spoofing in various fields such as border control, institutional security and public safety by surveillance cameras. Specifically, in this work, we address the problem of detecting spoofing occurring from video replay attacks, which is more common in such applications. We present a new database containing several videos of users juggling a football, captured under different lighting conditions and using different display and capture devices. We train our models using this database and the proposed system is capable of running in parallel with the HAR algorithms in real-time. Our experimental results show that our approach precisely detects video replay spoofing attacks and generalizes well, even to other applications such as spoof detection in face biometric authentication. Results show that our approach is effective even under resizing and compression artifacts that are common in HAR applications using remote server connections.

Initial Clinical Experience With a Simple, Home System for Early Detection and Monitoring of Diabetic Foot Ulcers: The Foot Selfie

Background: Diabetic foot ulcers (DFUs) are a leading cause of disability and morbidity. There is an unmet need for a simple, practical, home method to detect DFUs early and remotely monitor their healing. Method: We developed a simple, inexpensive, smartphone-based, “ Foot Selfie” system that enables patients to photograph the plantar surface of their feet without assistance and transmit images to a remote server. In a pilot study, patients from a limb-salvage clinic were asked to image their feet daily for six months and to evaluate the system by questionnaire at five time points. Transmitted results were reviewed weekly. Results: Fifteen patients (10 male) used the system after approximately 5 minutes of instruction. Participants uploaded images on a median of 76% of eligible study days. The system captured and transmitted diagnostic quality images of the entire plantar surface of both feet, permitting clinical-management decisions on a remote basis. We monitored 12 active wounds and 39 pre-ulcerative lesions (five wounds and 13 pre-ulcerative lesions at study outset); we observed healing of seven wounds and reversal of 20 pre-ulcerative lesions. Participants rated the system as useful, empowering, and preferable to their previous methods of foot screening. Conclusions: With minimal training, patients transmitted diagnostic-quality images from home on most days, allowing clinicians to review serial images. This system permits inexpensive home foot screening and monitoring of DFUs. Further studies are needed to determine whether it can reduce morbidity of DFUs and/or the associated cost of care. Artificial intelligence integration could improve scalability.

An Optical Smartphone-Based Inspection Platform for Identification of Diseased Orchids

Infections of orchids by the Odontoglossum ringspot virus or Cymbidium mosaic virus cause orchid disfiguration and are a substantial source of economic loss for orchid farms. Although immunoassays can identify these infections, immunoassays are expensive, time consuming, and labor consuming and limited to sampling-based testing methods. This study proposes a noncontact inspection platform that uses a spectrometer and Android smartphone. When orchid leaves are illuminated with a handheld optical probe, the Android app based on the Internet of Things and artificial intelligence can display the measured florescence spectrum and determine the infection status within 3 s by using an algorithm hosted on a remote server. The algorithm was trained on optical data and the results of polymerase chain reaction assays. The testing accuracy of the algorithm was 89%. The area under the receiver operating characteristic curve was 91%; thus, the platform with the algorithm was accurate and convenient for infection screening in orchids.

IOT Enabled Wearable Gloves with SEMG Subsystem with Posture Analysis

Electromyogram (EMG) is a technique to track the record , analyze and estimate the electrical activity produced by muscles. This technique is used to detect the muscle issues that harm the nerves activity , muscle tissues and identify the location where they are joined together . This paper discusses the implementation of a project which can be considered as a tool for the acquisition of muscle activity, presentation and real-time attainment of EMG signal using a specific EMG sensor. The live EMG reading is recorded using the Wi-Fi- enabled Raspberrypi and then sent to a remote server in our case ThingSpeak server with the help of IoT concepts which helps in the telemetry of the obtained biomedical signals using the cloud. Results are displayed in ThingSpeak. The live recordings are also obtained on the PC using the serial plotter. This project can also help us in monitor and observe the progress of the patient treatment even if the physiotherapist could not come and data can be directly sent to them. Thus, the project aims to develop an EMG monitoring device based on IoT, for analyzing and acquiring EMG signals. Keywords: EMG sensor, Raspberry pi, LCD, ADS1115

Literature Review on Cloud Application

The software that runs its processing logic is a cloud application. In this the data is stored between two systems: client-side and server-side. End-users local hardware and remote server is also a part where some processing is done. However, most data storage exists on a remote server which is one of the major perk of using cloud application. In some cases a local device with no storage space is built with cloud application. Using web browser cloud application interacts with its users; this facility makes the organizations to switch their infrastructure to the cloud for gaining the benefit of digital transformations. In cloud applications it is easier for the clients to move or manage their data safely and it also provides the flexibility required for the emerging organizations to sustain in the digital market. As the cloud applications are emerged with sophistication many papers were employed on its branches. This research paper emphasizes on the evolution and long-term trends of cloud applications. Findings from the paper enable the enterprise with perplexity to decide on adopting cloud.

CONCEPTUAL MODEL DEPICTING RISK FACTORS INFLUENZING CLOUD DATA SECURITY

Cloud Platform has the data stored in a remote server and accessed with the help of services provided by cloud service providers. The primary objective is to provide data security due to the confidentiality of data transmitted to the remote server, over an unmonitored and multi-tenancy channel (internet). The major components of cloud platform are application, service, runtime cloud, storage and infrastructure. This is a conceptual paper trying to explain the risk factors to be deemed in a cloud environment. The benefits include scalability, availability, reliability, flexibility, increased collaboration, competitive edge, sustainability, reduced proportional cost. Risk factors influencing the data security and Integrity are identified up to three level of sub-constructs.. All the risk factors including hackers, mishandling of passwords, risk of data accessed from public /unmonitored sources, security in communication channels, intentional and unintentional data security threats created due to human interference are included in the scope of this paper. In this paper, the identification of sub factors of cloud data security risk components is achieved. The futuristics scope of this paper is to identify early risk prediction and mitigation strategies to all the identified risk factors related to data security by implementing SEM methodology.

Vehicle Monitoring System based On IOT, Using 4G/LTE

In our World of today, the quest to get rich at all cost without working for our money has led some of our youth into crimes such as robbery and kidnapping. As a result of this and by the sheer fact that vehicles are now very expensive to buy these days, there is a need for people to safeguard their vehicles against these hoodlums to avoid loss of their precious Assets to these rampaging criminals. Tracking is technology that is used by many companies and individuals to track a vehicle, an individual or an asset by using many ways like GPS that operates using satellites and ground-based stations or by using our approach which depends on the cellular mobile towers. Vehicle tracking system is a system that can be used in monitoring and locating a vehicle, avoid theft or recover a stolen vehicle, for monitoring of vehicle routes to ensure strict compliance to an already defined vehicle routes, monitor driver’s behavior, predict bus arrival as well as for fleet management. Internet of things has made it very possible to devices to inter communicate amongst themselves and exchange information, helping in acquiring and analyzing information faster that we used to know in the past and this has helped more especially in vehicle monitoring to ensure that vehicle owners feel safe about their investments without fearing about their loss. In this paper, we propose a vehicle monitoring system based on IOT technology, using 4G/LTE to get the get the coordinate, speed, and overall condition of the vehicle, process and send to a remote server to be analyzed and used in locating the vehicle and monitor its other configured parameters. This is realized using Raspberry pi, 4G/LTE, GPS, Accelerometer and other sensors with communicate amongst themselves to get the environmental parameters which is processed and sent to a remote server where it is analyzed and represented on a map to locate the vehicle and monitor the other set parameters. 4G/LTE provides fast internet connectivity with

Client-side XSLT, Validation and Data Security

Client-side XSLT (CSX) is often used in scenarios where data (in XML) from a remote server is provided to a user who processes it in some way, for example, rendering it locally for display. That is, the server provides the data, and the client does the work on that data to make it useful. However, that is not the only scenario in which CSX is useful. In an environment in which the user already has, or is in the process of creating, XML, CSX can be a convenient and powerful tool, enabling users to perform operations on their data, securely, on their own systems. The potential for this use of CSX is illustrated with uses of Saxon-JS for several security-related applications.

ReVisE: Remote visualization environment for large numerical simulation datasets

The paper presents a new open-source visualization system, named ReVisE, aimed to provide interactive visualization of large datasets, which are results of complex numerical simulations. These datasets are hosted on a remote server or a supercomputer. The design of the system is briefly described. Dataset representation, proposed for interactive visualization and implemented in the system, is discussed. The effectiveness of our approach is confirmed by results of performance measurements on test and real-life large datasets. A comparison with other visualization systems is presented. Future plans of system development are outlined.