Smart home security: challenges,issues and solutions at different IoT layers

The Journal of Supercomputing - The Internet of Things is a rapidly evolving technology in which interconnected computing devices and sensors share data over the network to decipher different...     

Parallelization of the Scale‐Changing Technique in Grid Computing environment for the electronmagnetic simulation of multi‐scale structures

A parallel computing approach to run fast and full‐wave electromagnetic simulation of complex structures in Grid Computing environment is presented. In this study, we show how Grid Computing improves speed and/or reliability over that provided by a single computer, while typically being much more cost‐effective than single computers of comparable speed or reliability. An efficient monolithic (unique) formulation for the electromagnetic modelling of complex (multi‐scale) structures, i.e. structures that exhibit multiple metallic patterns whose sizes cover a large range of scales, is used here. This approach, named the Scale‐Changing Technique, is based on the cascade of multi‐modal Scale‐Changing Networks, each network modelling the electromagnetic coupling between two successive scale levels. These networks can be first computed separately, in an adaptive use of Grid Computing architecture nature, and then cascaded for the global electromagnetic simulation. Based on this technique, a fast computer algorithm was developed and tested in the Grid‐Computing environment. For illustration purposes, the electromagnetic analysis of multi‐scale structures, applied to phase‐shifter elements and an example of infinite passive reflectarray, was carried out. The obtained results have confirmed the effectiveness of such an approach compared with sequential computing. This approach shows very good computation performance while keeping the same accuracy. Besides, this method is very promising for optimizing circuit with multiple design parameters to handle and for the global electromagnetic simulation of multi‐scale and/or oer‐sized structures. Copyright © 2010 John Wiley & Sons, Ltd.     

Dynamic S-Box Generation Using Novel Chaotic Map with Nonlinearity Tweaking

A substitution box (S-Box) is a crucial component of contemporary cryptosystems that provide data protection in block ciphers. At the moment, chaotic maps are being created and extensively used to generate these S-Boxes as a chaotic map assists in providing disorder and resistance to combat cryptanalytical attempts. In this paper, the construction of a dynamic S-Box using a cipher key is proposed using a novel chaotic map and an innovative tweaking approach. The projected chaotic map and the proposed tweak approach are presented for the first time and the use of parameters in their working makes both of these dynamic in nature. The tweak approach employs cubic polynomials while permuting the values of an initial S-Box to enhance its cryptographic fort. Values of the parameters are provided using the cipher key and a small variation in values of these parameters results in a completely different unique S-Box. Comparative analysis and exploration confirmed that the projected chaotic map exhibits a significant amount of chaotic complexity. The security assessment in terms of bijectivity, nonlinearity, bits independence, strict avalanche, linear approximation probability, and differential probability criteria are utilized to critically investigate the effectiveness of the proposed S-Box against several assaults. The proposed S-Box’s cryptographic performance is comparable to those of recently projected S-Boxes for its adaption in real-world security applications. The comparative scrutiny pacifies the genuine potential of the proposed S-Box in terms of its applicability for data security.     

A Framework of Deep Learning and Selection-Based Breast Cancer Detection from Histopathology Images

Breast cancer (BC) is a most spreading and deadly cancerous malady which is mostly diagnosed in middle-aged women worldwide and effecting beyond a half-million people every year. The BC positive newly diagnosed cases in 2018 reached 2.1 million around the world with a death rate of 11.6% of total cases. Early diagnosis and detection of breast cancer disease with proper treatment may reduce the number of deaths. The gold standard for BC detection is biopsy analysis which needs an expert for correct diagnosis. Manual diagnosis of BC is a complex and challenging task. This work proposed a deep learning-based (DL) solution for the early detection of this deadly disease from histopathology images. To evaluate the robustness of the proposed method a large publically available breast histopathology image database containing a total of 277524 histopathology images is utilized. The proposed automatic diagnosis of BC detection and classification mainly involves three steps. Initially, a DL model is proposed for feature extraction. Secondly, the extracted feature vector (FV) is passed to the proposed novel feature selection (FS) framework for the best FS. Finally, for the classification of BC into invasive ductal carcinoma (IDC) and normal class different machine learning (ML) algorithms are used. Experimental outcomes of the proposed methodology achieved the highest accuracy of 92.7% which shows that the proposed technique can successfully be implemented for BC detection to aid the pathologists in the early and accurate diagnosis of BC.     

Simplified gateway selection scheme for multihop relay in vehicular ad hoc network

Integrating vehicular ad hoc network (VANET) and universal mobile telecommunication system (UMTS) could be a promising architecture for future machine‐to‐machine applications. This integration can help vehicles have steady Internet connection through the UMTS network and in communicating with other vehicles. However, dead spot areas and unsuccessful handoff processes caused by the high speed of vehicles can disrupt the implementation of this kind of architecture. In this paper, a new simplified gateway selection (SGS) scheme for multihop relay in a VANET‐UMTS integration network is proposed. The proposed scheme extends the coverage or/and calming of the frequent handoff process and allows vehicles to continue to be connected to the UMTS infrastructure network. An integrated simulation environment that combines VanetMobiSim and NS2 is used to simulate and evaluate the proposed scheme. The simulation results show that the SGS scheme performed better when it was implemented with ad hoc on a demand distance vector routing and destination‐sequenced distance vector routing protocols. Furthermore, the SGS scheme is compared with other cluster‐based gateway selections used in the previous works. The results show that our SGS scheme outperforms other cluster‐based gateway selections scheme in terms of selection delay, control packet overhead, packet delivery ratio, and overall throughput. Copyright © 2013 John Wiley & Sons, Ltd.     

Secure sensors data acquisition and communication protection in eHealthcare: Review on the state of the art

Recent advances in hardware technology have led to the development of low cost, power efficient and more feature rich devices that are amongst the most critical parts of communication networks. These devices or sensors can now sense data with more accuracy, process it by themselves and send it to the neighboring node or the sink node. However, robust and reliable security mechanisms are not yet properly implemented on these sensors due to their limited energy and computation power. Sensors also play a very important role in eHealthcare systems where ubiquitous patient monitoring is performed. As data is generated from the sensor nodes, reliable, secure and attack-resistant data acquisition and transmission is important for an efficient eHealthcare systems. This survey focuses on security issues of sensors data acquisition and transmission protocols, describing their main security features and comparing them in the context of a secure eHealthcare system. A taxonomy of open issues and future challenges is also discussed with respect to specific security metrics described in the paper.     

Surface plasmon polariton analogue to Young's double-slit experiment

When a light wave strikes a metal film it can, under appropriate conditions, excite a surface plasmon polariton (SPP)--a surface electromagnetic wave that is coupled to the free electrons in the metal. Such SPPs are involved in a wide range of phenomena, including nanoscale optical waveguiding, perfect lensing, extraordinary optical transmission, subwavelength lithography and ultrahigh-sensitivity biosensing. However, before the full potential of technology based on SPPs (termed 'plasmonics') can be realized, many fundamental questions regarding the interaction between light and matter at the nanoscale need to be answered. For over 200 years, Young's double-slit experiment has been a valuable pedagogical tool for demonstrating the wave nature of light. Here, we perform a double-slit experiment with SPPs to reveal the strong analogy between SPP propagation along the surface of metallic structures and light propagation in conventional dielectric components (such as glass waveguides). This allows us to construct a general framework to describe the propagation, diffraction and interference of SPPs. It also suggests that there is an effective diffraction limit for the lateral confinement of SPPs on metal stripe waveguides, and justifies the use of well-developed concepts from conventional optics and photonics in the design of new plasmonic devices.     

Readout responses of inclined strips in position-sensitivedetectors

Readout responses for the inclined strips in position-sensitive detectors have been studied using theoretical predictions and experimental results. Inclined strips are almost along the displacement direction of incident particles. Rotating conventional strips to near horizontal strips decreases the number of strips by a tangential factor for long-length position sensing. In addition to the channel reduction, the inclined strips modify about 10% in the readout linearity compared to the long-length zigzag patterns. There is resolution degradation because of the inherent high sensitivity of these strips to the avalanche size (about 8% of the detector full length). Double peak responses were observed for sensing the positions of the incident particles. Our theoretical predictions and experimental results are discussed in this paper     

Development and applications of a compact hybrid tabletop terawatt chirped-pulse amplification Ti:sapphire-Nd:glass laser for x-ray lasing and harmonic generation

A hybrid tabletop (2 m x 3 m) terawatt chirped-pulse amplification Ti:sapphire-Nd:glass laser (1054 nm, 475 fs, 500 mJ, 9 x 10(17) W cm(-2)) has been developed for laser-matter experiments. An overall gain factor of 10(10) was achieved for the laser. The results of laser applications in the studies of soft-x-ray Ni-like Mo 18.9-nm lasing and of harmonic generation from solid surfaces are presented.     

Inverted organic photovoltaic device with a new electron transport layer

We demonstrate that there is a new solution-processed electron transport layer, lithium-doped zinc oxide (LZO), with high-performance inverted organic photovoltaic device. The device exhibits a fill factor of 68.58%, an open circuit voltage of 0.86 V, a short-circuit current density of −9.35 cm/mA² along with 5.49% power conversion efficiency. In addition, we studied the performance of blend ratio dependence on inverted organic photovoltaics. Our device also demonstrates a long stability shelf life over 4 weeks in air.