A secure multifactor remote user authentication scheme for Internet of Multimedia Things environment

To attain ubiquitous connectivity of everything, Internet of Things (IoT) systems must include “multimedia things.” Internet of Multimedia Things (IoMT) is a heterogeneous network of smart multimedia things connected together and with other physical devices to the Internet so as to achieve globally available multimedia services and applications. Due to the ever increasing amount of multimedia data in IoT environments, securing these systems becomes crucial. This is because these systems are easily susceptible to attacks when information or any service is accessed by the users. In this paper, we propose a secure three‐factor remote user authentication scheme for IoMT systems using ECC. The formal security proof performed using ROR model and BAN logic confirms that an attacker will not be able to extract sensitive user information. Through informal security analysis, we justify the resistance of the scheme against several security attacks. The performance comparison shows that the scheme is efficient in terms of computational cost, security features, and attack resistance. Furthermore, simulation of the scheme using AVISPA and Proverif proves that the scheme is secure against all active and passive attacks.     

Comparative Study of the Different Variants of the DV-Hop Based Node Localization Algorithms for Wireless Sensor Networks

Wireless Personal Communications - Node localization is one of the essential services where sensor nodes in the wireless sensor network collaborate to provide location information of sensor nodes...     

Enhancing Coverage Using Weight Based Clustering in Wireless Sensor Networks

Energy conservation in wireless sensor networks (WSNs) is a fundamental issue. For certain surveillance applications in WSN, coverage lifetime is an important issue and this is related to energy consumption significantly. In order to handle these two interlinked aspects in WSN, a new scheme named Weight based Coverage Enhancing Protocol (WCEP) has been introduced. The WCEP aims to obtain longer full coverage and better network life time. The WCEP is based on assigning different weight values to certain governing parameters which are residual energy, overlapping degree, node density and degree of sensor node. These governing parameters affect the energy and coverage aspects predominantly. Further, these four different parameters are prime elements in cluster formation process and node scheduling mechanisms. The weight values help in selection of an optimal group of Cluster Heads and Cluster Members, which result in enhancement of complete coverage lifetime. The simulation results indicate that WCEP performs better in terms of energy consumption also. The enhancement of value 24% in full coverage lifetime has been obtained as compared to established existing techniques.

     

Image and Video Forensics: A Critical Survey

With the extensive use of multimedia on internet and easy approachability of powerful image and video editing software, doctored visual contents have been extensively appearing in our electronic-mail in-boxes, Whatsapp, Facebook or any other social media. Recently, attempting blind tampering in visual contents have been progressively adopted. This paper presents a collaborative survey on detection of such attempts. Our aim is to establish an effective path, for researchers working in the field of image and video forensics, to unfold new aspects of forgery. This paper will avail the comprehensive study that will assist the researchers to go through the various challenges encountered in the previous work. The focus of this paper is to review the splicing and copy–move forgery detection methods in images as well as inter and intra-frame forgery challenges in videos, highlighting the commonly used datasets and hence assisting new researchers to work on with. The efficacy of the paper is that such collaborative survey under one umbrella is not available yet.

     

Semantic Information Extraction from Multi-Corpora Using Deep Learning

Information extraction plays a vital role in natural language processing, to extract named entities and events from unstructured data. Due to the exponential data growth in the agricultural sector, extracting significant information has become a challenging task. Though existing deep learning-based techniques have been applied in smart agriculture for crop cultivation, crop disease detection, weed removal, and yield production, still it is difficult to find the semantics between extracted information due to unswerving effects of weather, soil, pest, and fertilizer data. This paper consists of two parts. An initial phase, which proposes a data preprocessing technique for removal of ambiguity in input corpora, and the second phase proposes a novel deep learning-based long short-term memory with rectification in Adam optimizer and multilayer perceptron to find agricultural-based named entity recognition, events, and relations between them. The proposed algorithm has been trained and tested on four input corpora i.e., agriculture, weather, soil, and pest & fertilizers. The experimental results have been compared with existing techniques and it was observed that the proposed algorithm outperforms Weighted-SOM, LSTM+RAO, PLR-DBN, KNN, and Naïve Bayes on standard parameters like accuracy, sensitivity, and specificity.     

Microstructure and protein digestibility of beef: The effect of cooking conditions as used in stews and curries

Beef meat was cooked at 373 K for 10 and 30 min to investigate the effect of the cooking conditions generally used during beef stew and curry preparation on protein digestibility. The cooked meats, along with a raw control, were digested using an in vitro digestion model to simulate gastric and small-intestinal conditions. Samples taken at different digestion times were analyzed using SDS-PAGE, RP-HPLC, ninhydrin assays for amino N and transmission electron microscopy. Simulated gastric conditions quickly led to the loss of basic sarcomere structure in raw meat myofibrils whereas the sarcomere structure of the compact cooked meat myofibrils remained intact after 30 min of gastric digestion. Prolonged cooking of meat (30 min) resulted in incomplete digestion of small MW (<10 kDa) peptides, as observed from SDS-PAGE. This agreed with the amount of ninhydrin-reactive amino N released during digestion, which decreased with an increase in cooking time. The RP-HPLC peak areas of the major identified amino acids (tryptophan, tyrosine and phenylalanine) also decreased with an increase in cooking time. This suggested the formation of “limit peptides” during prolonged cooking of beef, which were not further broken down into free amino acids by digestive enzymes and therefore might not be bioavailable.     

Heavy metal accumulation in vegetables irrigated with water from different sources

The present study was carried out to assess levels of different heavy metals like iron, manganese, copper and zinc, in vegetables irrigated with water from different sources. The results indicated a substantial build-up of heavy metals in vegetables irrigated with wastewater. The range of various metals in wastewater-irrigated plants was 116–378, 12–69, 5.2–16.8 and 22–46 mg/kg for iron (Fe), manganese (Mn), copper (Cu) and zinc (Zn), respectively. The highest mean levels of Fe and Mn were detected in mint and spinach, whereas the levels of Cu and Zn were highest in carrot. The present study highlights that both adults and children consuming vegetables grown in wastewater-irrigated soils ingest significant amount of these metals. However, the values of these metals were below the recommended maximum tolerable levels proposed by the [Joint FAO/WHO Expert Committee on Food Additives (1999). Summary and conclusions. In 53rd Meeting, Rome, June 1–10, 1999]. However, the regular monitoring of levels of these metals from effluents and sewage, in vegetables and in other food materials is essential to prevent excessive build-up of these metals in the food chain.     

Characterization of Gum Ghatti (Anogeissus latifolia): A Structural and Rheological Approach

ABSTRACT:  Gatifolia, a commercial gum ghatti ( Anogeissus latifolia ) product was studied for its structural, thermal, and rheological characteristics. This study may prove helpful for the use of gum ghatti in a diverse range of food applications. The molecular weight ( M _W) and  R_g  (radius of gyration) for gum ghatti were calculated to be approximately 8.94 × 10⁷ g/mol and 140 nm, respectively, using high-performance size exclusion chromatography (HPSEC) system combined with multi-angle laser light scattering (MALLS). Gum ghatti solutions exhibited pseudoplastic behavior (as determined by flow experiments), which became more prevalent with increasing concentrations. Gum ghatti also displayed time-dependent shear-thickening behavior and showed negative hysteresis during up–down flow measurements. Under the measurement conditions at the range of frequencies and temperatures studied, the gum did not behave as a typical viscoelastic gel.     

Effect of High-Pressure Processing on Physical, Biochemical, and Microbiological Characteristics of Black Tiger Shrimp (Penaeus monodon)

The effect of high-pressure processing on quality and shelf life of black tiger shrimp was studied. Shrimp was high-pressure processed at selected pressure levels of 100, 270, and 435 MPa for 5 min at room temperature (25?±?2 °C). Changes in physical, biochemical, and microbiological characteristics after processing and during subsequent chilled storage were examined for 35 days. After processing significant (P?<?0.05) increase in moisture content and parallel reduction in protein content was observed. No significant changes were observed in TVB-N and TMA-N levels of shrimp after processing; however, these significantly increased with storage. Whiteness index increased with pressure intensity imparting brighter and mildly cooked appearance. Pressure-induced hardening effect was observed, which showed decreasing trend during storage. The treated samples maintained lower viable counts throughout the storage, thus having better microbial quality than untreated sample. Shelf life was extended to 15 days in shrimp treated at 435 MPa compared with 5 days in untreated sample. Pressure treatment of 435 MPa was found to be most effective in preserving the quality and extending the shelf life of black tiger shrimp.     

Survival of Salmonella, Escherichia coli O157:H7, and Listeria monocytogenes on Inoculated Almonds and Pistachios Stored at -19, 4, and 24° C

The survival of Salmonella, Escherichia coli O157:H7, and Listeria monocytogenes was determined on almonds and pistachios held at typical storage temperatures. Almond kernels and inshell pistachios were inoculated with four- to six-strain cocktails of nalidixic acid-resistant Salmonella, E. coli O157:H7, or L. monocytogenes at 6 log CFU/g and then dried for 72 h. After drying, inoculated nuts were stored at -19, 4, or 24°C for up to 12 months. During the initial drying period after inoculation, levels of all pathogens declined by 1 to -log CFU/g on both almonds and pistachios. During storage, moisture content (4.8%) and water activity (0.4) of the almonds and pistachios were consistent at -19°C; increased slowly to 6% and 0.6, respectively, at 4°C; and fluctuated from 4 to 5% and 0.3 to 0.5 at 24°C, respectively. Every 1 or 2 months, levels of each pathogen were enumerated by plating; samples were enriched when levels fell below the limit of detection. No reduction in population level was observed at -19 or 4°C for either pathogen, with the exception of E. coli O157:H7-inoculated almonds stored at 4°C (decline of 0.09 log CFU/g/month). At 24°C, initial rates of decline were 0.20, 0.60, and 0.71 log CFU/g/month on almonds and 0.15, 0.35, and 0.86 log CFU/g/month on pistachios for Salmonella, E. coli O157:H7, and L. monocytogenes, respectively, but distinct tailing of the survival curves was noted for both E. coli O157:H7 and L. monocytogenes.