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Due to the connectivity of the multiple devices and the systems on the same network, rapid development has become possible in Internet of Things (IoTs) for the last decade. But, IoT is mostly affected with severe security challenges due to the potential vulnerabilities happened through the multiple connectivity of sensors, devices and system. In order to handle the security challenges, literature presents a handful of security protocols for IoT. The purpose of this paper is to present a threat profiling and elliptic curve cryptography (ECC)-based mutual and multi-level authentication for the security of IoTs. This work contains two security attributes like memory and machine-related attributes for maintaining the profile table. Also, the profile table stores the value after encrypting the value with ECC to avoid storage resilience using the proposed protocol. Furthermore, three entities like, IoT device, server and authorization centre (AC) performs the verification based on seven levels mutually to provide the resilience against most of the widely accepted attacks. Finally, DPWSim is utilized for simulation of IoT and verification of proposed protocol to show that the protocol is secure against passive and active attacks.

In this work, the authors have presented a threat profiling and ECC-based mutual and multi-level authentication for the security of IoTs. This work contains two security attributes like memory and machine-related attributes for maintaining the profile table. Also, the profile table stores the value after encrypting the value with ECC to avoid storage resilience using the proposed protocol. Furthermore, three entities like, IoT device, server and AC performs the verification based on seven levels mutually to provide the resilience against most of the widely accepted attacks.

DPWSim is utilized for simulation of IoT and verification of the proposed protocol to show that this protocol is secure against passive and active attacks. Also, attack analysis is carried out to prove the robustness of the proposed protocol against the password guessing attack, impersonation attack, server spoofing attack, stolen verifier attack and reply attack.

This paper presents a threat profiling and ECC-based mutual and multi-level authentication for the security of IoTs.

Association rule mining generates the patterns and correlations from the database, which requires large scanning time, and the cost of computation associated with the generation of the rules is quite high. On the other hand, the candidate rules generated using the traditional association rules mining face a huge challenge in terms of time and space, and the process is lengthy. In order to tackle the issues of the existing methods and to render the privacy rules, the paper proposes the grid-based privacy association rule mining.

The primary intention of the research is to design and develop a distributed elephant herding optimization (EHO) for grid-based privacy association rule mining from the database. The proposed method of rule generation is processed as two steps: in the first step, the rules are generated using apriori algorithm, which is the effective association rule mining algorithm. In general, the extraction of the association rules from the input database is based on confidence and support that is replaced with new terms, such as probability-based confidence and holo-entropy. Thus, in the proposed model, the extraction of the association rules is based on probability-based confidence and holo-entropy. In the second step, the generated rules are given to the grid-based privacy rule mining, which produces privacy-dependent rules based on a novel optimization algorithm and grid-based fitness. The novel optimization algorithm is developed by integrating the distributed concept in EHO algorithm.

The experimentation of the method using the databases taken from the Frequent Itemset Mining Dataset Repository to prove the effectiveness of the distributed grid-based privacy association rule mining includes the retail, chess, T10I4D100K and T40I10D100K databases. The proposed method outperformed the existing methods through offering a higher degree of privacy and utility, and moreover, it is noted that the distributed nature of the association rule mining facilitates the parallel processing and generates the privacy rules without much computational burden. The rate of hiding capacity, the rate of information preservation and rate of the false rules generated for the proposed method are found to be 0.4468, 0.4488 and 0.0654, respectively, which is better compared with the existing rule mining methods.

Data mining is performed in a distributed manner through the grids that subdivide the input data, and the rules are framed using the apriori-based association mining, which is the modification of the standard apriori with the holo-entropy and probability-based confidence replacing the support and confidence in the standard apriori algorithm. The mined rules do not assure the privacy, and hence, the grid-based privacy rules are employed that utilize the adaptive elephant herding optimization (AEHO) for generating the privacy rules. The AEHO inherits the adaptive nature in the standard EHO, which renders the global optimal solution.

The paper aims to introduce an intelligent recognition system for viewpoint variations of gait and speech. It proposes a convolutional neural network-based capsule network (CNN-CapsNet) model and outlining the performance of the system in recognition of gait and speech variations. The proposed intelligent system mainly focuses on relative spatial hierarchies between gait features in the entities of the image due to translational invariances in sub-sampling and speech variations.

This proposed work CNN-CapsNet is mainly used for automatic learning of feature representations based on CNN and used capsule vectors as neurons to encode all the spatial information of an image by adapting equal variances to change in viewpoint. The proposed study will resolve the discrepancies caused by cofactors and gait recognition between opinions based on a model of CNN-CapsNet.

This research work provides recognition of signal, biometric-based gait recognition and sound/speech analysis. Empirical evaluations are conducted on three aspects of scenarios, namely fixed-view, cross-view and multi-view conditions. The main parameters for recognition of gait are speed, change in clothes, subjects walking with carrying object and intensity of light.

The proposed CNN-CapsNet has some limitations when considering for detecting the walking targets from surveillance videos considering multimodal fusion approaches using hardware sensor devices. It can also act as a pre-requisite tool to analyze, identify, detect and verify the malware practices.

This research work includes for detecting the walking targets from surveillance videos considering multimodal fusion approaches using hardware sensor devices. It can also act as a pre-requisite tool to analyze, identify, detect and verify the malware practices.

This proposed research work proves to be performing better for the recognition of gait and speech when compared with other techniques.

This paper aims to investigate on composite fabrics to develop the improved sleeping bag using trilayered textile structures. A thermal comfort analysis of fabrics is essential to design an enhanced type of sleeping bag.

In this study, optimizing thermal and permeability properties of different combinations of trilayer composite fabrics was done. The inner layer was 100% wool-knitted single jersey fabric. The middle layer was polyester needle punched non-woven fabric. The outermost layer was nylon-based Core-Tex branded waterproof breathable fabric. Five variations in wool-knitted samples were developed by changing the loop length and yarn count to optimize the best possible combination. Two different polyester non-woven fabrics have been produced with the changes in bulk density. Twelve trilayer composite fabric samples have been produced, and thermal comfort properties such as thermal conductivity, thermal absorptivity, thermal resistance, air permeability and relative water vapour permeability have been analysed.

Among the 12 samples, one optimized sample has been found with the specification of 100% wool with 25 Tex yarn linear density having 4.432-mm loop length inner-layered fabric, 96 g/m² polyester nonwoven fabric as the middle layer, and 220 g/m² Nylon-Core tex branded outermost layer. All the functional properties of the composite fabric are significantly different with the knitted wool fabrics and polyester nonwoven fabrics, which have been confirmed by analysis of variance study.

This research work supports for producing sleeping bag with enhanced comfort level.

The essential properties of active sports fabrics are moisture management, quick-drying, body heat management and thermal regulations. Fibre type, blending nature, yarn and fabric structure and the finishing treatment are the key parameters that influenced the performance of the clothing meant for sportswear. This study aims to investigate the effect of fibre blending and structural tightness factors on bi-layer sport fabric's dimensional, moisture management and thermal properties.

In this study, 12 different bi-layer inter-lock fabrics were produced. Polyester filament (120 Denier) yarn was fed to form the backside of the fabric, and the face side was varied with cotton, modal, wool and soya spun yarns of 30sNe. Three different types of structural tightness factors were considered, such as low, medium and high were taken for sample development. The assessment towards dimensional, moisture management and thermal properties was carried out on all the samples.

The polyester-modal blend with a high tightness factor has shown maximum overall moisture management capability (OMMC) values of 0.73 and air permeability of 205.3 cm³/cm²/s. The same sample has shown comparatively higher thermal conductivity of 61.72 × 10^–3 W m^-1 °C^-1(Under compression state) and 58.45 × 10^–3 W m^-1 °C^-1 (under recovery state). In the case of surface roughness is concerned, polyester-modal blends have shown the lowest surface roughness, surface roughness amplitude and surface friction co-efficient. Among the selected fibre combinations, the overall comfort level of polyester-modal bi-layer knitted structure with a higher tightness factor is appreciable. Polyester-modal is more suitable for active sportswear among the four fiber blend combinations.

The outcome of this study will help to gain a better understanding of fibre blends, structural tightness factor and other process specifications for the development of bi-layer fabric for active sportswear applications. The dynamic functional testing methods (Moisture management and Thermal properties) were carried out to simulate the actual wearing environment of the sports clothing. This study will create a new scope of research opportunities in the field of bi-layer sports textiles.

This study was conducted to explore the influence of fibre blend and structural tightness factor on the comfort level of sportswear and to find the suitable fibre blend for active sportswear clothing.

Eri is a short-stapled fibre that possesses an excellent soft feel and warmness to the wearer. Investigation of thermal comfort and moisture properties of Eri silk fabric provides the enhanced commercial scope for Eri silk-based clothing.

To examine the impact of process factors on thermal and moisture properties, three different single knit Eri silk structures were made, each with a different loop length and yarn count. Three different linear densities of Eri silk spun yarn (15, 20 and 25 tex) were selected. Three distinct knitted constructions, including plain jersey, popcorn and cellular blister, were created, along with two different loop lengths.

The novel cellular blister structure has shown appreciable thermal comfort properties than the other two structures. Yarn fineness and loop length were significant with most of the thermal comfort properties.

In recent times the Eri silk production is completely domesticated, so the new demand can easily be met by the producers. This research will create a new scope for Eri silk fibres in sportswear and leisure wear.

This study was conducted to explore the influence of knit structure, loop length and yarn count on the thermal comfort properties of the clothing.

The study aims to investigate the influence of fabric hybridization, stacking sequences and matrix materials on the tensile strength and damping behavior of jute/carbon reinforced hybrid composites.

The hybrid composites were fabricated with different sequences of fabric plies in epoxy and polyester matrix using a hand layup technique. The tensile and vibration characteristics were evaluated on the hybrid laminated composite models using finite element analysis (FEA), and the results were validated experimentally according to ASTM standards. The surface morphology of the fractured specimens was studied using the scanning electron microscope.

The experimental results revealed that the position of jute layers in the hybrid composites has a significant influence on the tensile strength and damping behavior. The hybrid composite with jute fiber at the surface sides and carbon fibers at the middle exhibited higher tensile strength with superior damping properties. Further, it is found that the experimental results are in good coherence with the FEA results.

The less weight and low-cost hybrid composites were fabricated by incorporating the jute and carbon fabrics in interply configurations. The influences of fabric hybridization, stacking arrangements and matrix materials on the tensile and vibration behavior of jute/carbon hybrid composites have been numerically evaluated and the results were experimentally validated.

The purpose of this study is to understand the behavior of hybrid bio-composites under varied applications.

Fabrication methods and material characterization of various hybrid bio-composites are analyzed by studying the tensile, impact, flexural and hardness of the same. The natural fiber is a manufactured group of assembly of big or short bundles of fiber to produce one or more layers of flat sheets. The natural fiber-reinforced composite materials offer a wide range of properties that are suitable for many engineering-related fields like aerospace, automotive areas. The main characteristics of natural fiber composites are durability, low cost, low weight, high specific strength and equally good mechanical properties.

The tensile properties like tensile strength and tensile modulus of flax/hemp/sisal/Coir/Palmyra fiber-reinforced composites are majorly dependent on the chemical treatment and catalyst usage with fiber. The flexural properties of flax/hemp/sisal/coir/Palmyra are greatly dependent on fiber orientation and fiber length. Impact properties of flax/hemp/sisal/coir/Palmyra are depended on the fiber content, composition and orientation of various fibers.

This study is a review of various research work done on the natural fiber bio-composites exhibiting the factors to be considered for specific load conditions.

Parts that are to be used in aircraft, satellites, automobiles and ships should have sound microstructure. Components made from AA6082/Si₃N₄ and AA6082/SiC composites are in demand from industries. Hence, these components are to be fabricated by suitable technique at the appropriate value of process parameters. The purpose of this paper is Microstructure analysis of AA6082/Si3N4 and AA6082/SiC composites

AA6082/Si₃N₄ and AA6082/SiC composites are successfully fabricated using the stir casting process. Their microstructures have been analyzed. This has been done at different magnification. The effect of the addition of Si₃N₄ and SiC particles in the 6082 aluminum alloy is investigated. Microstructure of AA6082/Si₃N₄ and AA6082/SiC composites are also compared. Results show that Si₃N₄ and SiC particles have good wettability with AA6082. These reinforcement particles are homogeneously distributed in the matrix of AA6082.

There are no adverse effects of reactions in the microstructure of AA6082/Si₃N₄ and AA6082/SiC composites. There is not much difference between the distribution and interfacial characteristics of Si₃N₄ and SiC particles. AA6082/Si₃N₄ and AA6082/SiC composites have good properties. This is high strength at low density. Due to which they become suitable for the aircraft and space industry. So far, SiC, Al₂O₃ and tungsten carbide have been mostly used as reinforcements with different grades of aluminum alloy.

Not much experimental work is found with Si₃N₄ and SiC particles as reinforcement with AA6082. The novelty of this research work is that an effort has been made to fabricate AA6082/Si₃N₄ and AA6082/SiC composites at such values of process parameters, by stir casting process, so that sound and defect free microstructure is obtained. Microstructure of AA6082/Si₃N₄ and AA6082/SiC composites is also compared, to find which is better.

The purpose of this study to find an alternate method to minimize waste i.e., eggshell and rice husk ash. In this paper, eggshell (ES) and rice husk ash (RHA) particles are used as reinforcements for examining their effect on the coefficient of thermal expansion (CTE), grain size (GS) and corrosion behavior for developed composite material.

In this investigation, 5 Wt.% each of ES and RHA reinforcement particles have been introduced. To investigate the microstructures of the developed composite material, scanning electron microscope was used. Physical and mechanical properties of composite material are tensile strength and hardness that have been examined.

The result of this paper shows that number of grains per square inch for composition Al/5% ES/5% RHA composite was found to be 1,243. Minimum value of the volume CTE was found to be 6.67 × 10–6/°C for Al/5% ES/5% RHA composite. The distribution of hard phases of ES particles in metal matrix is responsible for improvements in tensile strength and hardness. These findings demonstrated that using carbonized ES as reinforcement provides superior mechanical and physical properties than using uncarbonized ES particles.

There are several articles examining the impact of varying Wt.% of carbonized ES and rice husk reinforcement on the microstructures and mechanical characteristics of metal composites. CTE, GS and corrosion behavior are among of the features that are examined in this paper.