Secured Data Storage Using Deduplication in Cloud Computing Based on Elliptic Curve Cryptography

The tremendous development of cloud computing with related technologies is an unexpected one. However, centralized cloud storage faces few challenges such as latency, storage, and packet drop in the network. Cloud storage gets more attention due to its huge data storage and ensures the security of secret information. Most of the developments in cloud storage have been positive except better cost model and effectiveness, but still data leakage in security are billion-dollar questions to consumers. Traditional data security techniques are usually based on cryptographic methods, but these approaches may not be able to withstand an attack from the cloud server's interior. So, we suggest a model called multi-layer storage (MLS) based on security using elliptical curve cryptography (ECC). The suggested model focuses on the significance of cloud storage along with data protection and removing duplicates at the initial level. Based on divide and combine methodologies, the data are divided into three parts. Here, the first two portions of data are stored in the local system and fog nodes to secure the data using the encoding and decoding technique. The other part of the encrypted data is saved in the cloud. The viability of our model has been tested by research in terms of safety measures and test evaluation, and it is truly a powerful complement to existing methods in cloud storage.     

Anomaly Detection for Industrial Internet of Things Cyberattacks

The evolution of the Internet of Things (IoT) has empowered modern industries with the capability to implement large-scale IoT ecosystems, such as the Industrial Internet of Things (IIoT). The IIoT is vulnerable to a diverse range of cyberattacks that can be exploited by intruders and cause substantial reputational and financial harm to organizations. To preserve the confidentiality, integrity, and availability of IIoT networks, an anomaly-based intrusion detection system (IDS) can be used to provide secure, reliable, and efficient IIoT ecosystems. In this paper, we propose an anomaly-based IDS for IIoT networks as an effective security solution to efficiently and effectively overcome several IIoT cyberattacks. The proposed anomaly-based IDS is divided into three phases: pre-processing, feature selection, and classification. In the pre-processing phase, data cleaning and normalization are performed. In the feature selection phase, the candidates’ feature vectors are computed using two feature reduction techniques, minimum redundancy maximum relevance and neighborhood components analysis. For the final step, the modeling phase, the following classifiers are used to perform the classification: support vector machine, decision tree, k-nearest neighbors, and linear discriminant analysis. The proposed work uses a new data-driven IIoT data set called X-IIoTID. The experimental evaluation demonstrates our proposed model achieved a high accuracy rate of 99.58%, a sensitivity rate of 99.59%, a specificity rate of 99.58%, and a low false positive rate of 0.4%.     

Ubi-App: a ubiquitous application for universal access from handheld devices

Universal access from a handheld device (such as a PDA, cell phone) at any time or anywhere is now a reality. Ubicomp Assistant (UA) (Sharmin et al. in Proceedings of the 21st annual ACM symposium on applied computing (ACM SAC 2006), Dijon, France, pp 1013–1017, 2006) is an integral service of MARKS (Sharmin et al. in Proceedings of the third international conference on information technology: new generations (ITNG 2006), Las Vegas, Nevada, USA, pp 306–313, 2006). It is a middleware developed for handheld devices, and has been designed to accommodate different types of users (e.g., education, healthcare, marketing, or business). This customizable service employs the ubiquitous nature of current short range, low-power wireless connectivity and readily available, low-cost lightweight mobile devices. These devices can reach other neighbouring devices using a free short-range ad hoc network. To the best of the authors’ knowledge, the UA service is the only service designed for these devices. This paper presents the details of Ubi-App, a ubiquitous application for universal access from any handheld device, which uses UA as a service. The results of a usability test and performance evaluation of the prototype show that Ubi-App is useful, easy to use, easy to install, and does not degrade the performance of the device.     

Efficient implementation of Jacobi iterative method for large sparse linear systems on graphic processing units

In this paper, an original Jacobi implementation is considered for the solution of sparse linear systems of equations. The proposed algorithm helps to optimize the parallel implementation on GPU. The performance analysis of GPU-based (using CUDA) algorithm of the implementation of this algorithm is compared to the corresponding serial CPU-based algorithm. Numerical experiments performed on a set of matrices arising from the finite element discretization of various equations (3D Laplace equation, 3D gravitational potential equation, 3D Heat equation) with different meshes, illustrate the performance, robustness and efficiency of our algorithm, with a speed up to 23\(\times \) in double-precision arithmetics.     

Modelling of air damping effect on the performance of encapsulated MEMS resonators

Microsystem Technologies - The dynamic performance of a micro-resonator depends on its energy loss mechanism which is quantified by Q-factor (Quality factor). This paper presents numerical...     

Electrically conducting thin films obtained by ion implantation in pyrolyzed polyacrylonitrile

Heat treatment of polyacrylonitrile (PAN) leads to products with semiconductor-to-metal range of conductivities. The electrical properties of these materials are further modified by ion implantation. The conductivity, 1×10^–7 (Ω cm)^–1, of heat treated PAN at 435°C (PAN435) increases upon ion implantation with As⁺, Kr⁺, Cl⁺ or F⁺, reaching the maximum value of 8.9×10^–1 (Ω cm)^–1 at a dose of 5×10¹⁶ ion/cm² and an energy of 200 KeV for the case of F⁺ implantation. On the other hand, ion implantation in the more conducting heat-treated PAN at 750 °C (PAN750) leads to a decrease in the electrical conductivity. It is shown that the conductivity modifications are primarily due to structural rearrangements induced by the energetic ions. Specific chemical doping contribution to conductivity is noted for halogen implantation in PAN435. The temperature dependence of conductivity of PAN heat treated at 750°C suggests a two path conduction, namely a three dimensional variable range hopping conduction and a metallic conduction. After ion implantation, the conductivity-temperature dependence is interpreted in terms of a variable range hopping conduction mechanism. Received: 25 August 2000 / Reviewed and accepted: 28 August 2000     

Selection of Methodology for Neural Network Modeling of Constitutive Hystereses Behavior of Soils

Classic constitutive modeling of geomaterials based on the elasticity and plasticity theories suffers from limitations pertaining to formulation complexity, idealization of behavior, and excessive empirical parameters. This article capitalizes on the modeling capabilities of neural networks as substitutes for the classic approaches. The neural network–based modeling overcomes the difficulties encountered in understanding the underlying microscopic processes governing the material's behavior by redirecting the efforts into learning the cause-effect relations from behavioral examples. Several methodologies are presented and cross-compared for effectiveness in approximating a theoretical hysteresis model resembling stress-strain behavior. The most effective methodology was used in modeling the constitutive behavior of an experimentally tested soil and produced models that simulated the real behavior of the soil with high accuracy. Although these models are empirical, they are retrainable and thus, unlike classic constitutive modeling techniques, can be revised and generalized easily when new data become available.     

An Investigation of Branch and Bound Methods for Solving the Segregated Storage Problem

The segregated storage problem consists of determining a minimum cost distribution of products among compartments such that only one product may be stored in a given compartment. This paper explores the computational aspects of using branch and bound methods to solve this problem. Such methods were first suggested for this problem by White and Francis. A variety of approaches are tested, utilizing heuristic node selection and branching decision rules. Three heuristics are also presented which generate solutions for use as initial upper bounds for improving efficiency of the branch and bound procedure or as solutions for very large problems.     

Energy‐efficient design of greenhouse for Canadian Prairies using a heating simulation model

Greenhouses in northern climates require a large amount of supplemental heating for growing crops in winter seasons, so energy‐efficient design of greenhouses based on local climate is important to minimize the heating demand. In this study, greenhouse design parameters including shape, orientation, the angle of the roof, and width of the span have been studied for the conceptual design of conventional greenhouses for Canadian Prairies using a heating simulation model. Five different shapes of greenhouses including even‐span, uneven‐span, modified arch, vinery, and quonset shape have been selected for the study. The simulation results proved that the uneven‐span gable roof shape receives the highest solar radiation, whereas the quonset shape receives the lowest solar radiation. However, the quonset shape greenhouse requires about 7.6% less annual heating as compared to the gable roof greenhouse, but the quonset would not be adopted as multispan greenhouses. Therefore, the gable roof greenhouse is considered as energy efficient for the multispan gutter connected greenhouses whereas quonset shape as a free‐standing single‐span greenhouses. In high northern latitudes, the greenhouse with east‐west orientation is more energy efficient from heating and cooling point of view when the length‐width ratio of the greenhouse is more than 1. The heating energy saving potential of the large span width in single‐span greenhouses is relatively higher as compared to the multispan greenhouses.     

Single basin double slope solar still with minimum basin depth and energy storing materials

Solar still is a simple device which can convert available waste or brackish water into potable water using solar energy. A single basin double slope solar still with an inner basin size 2.08 m × 0.84 m × 0.075 m and that of the outer basin size 2.3 m × 1 m × 0.25 m has been fabricated with mild steel plate and tested with a layer of water and different sensible heat storage materials like quartzite rock, red brick pieces, cement concrete pieces, washed stones and iron scraps. It is found that, the still with ¾ in. sized quartzite rock is the effective basin material. The still is theoretically modeled. In previous researcher’s work, variation in transmittance is taken as constant. The variations in solar incidence angle and transmittance of the covers are also considered in this work. The theoretical values are compared with actual values. The theoretical water and glass temperatures and the theoretical production rate are having higher deviation with actual. Hence, another thermal model developed for this still is applied to validate the results accurately. It is found that, the theoretical production rate using thermal model agrees well with experimental.