A survey of IoT security based on a layered architecture of sensing and data analysis

The Internet of Things (IoT) is leading today’s digital transformation. Relying on a combination of technologies, protocols, and devices such as wireless sensors and newly developed wearable and implanted sensors, IoT is changing every aspect of daily life, especially recent applications in digital healthcare. IoT incorporates various kinds of hardware, communication protocols, and services. This IoT diversity can be viewed as a double-edged sword that provides comfort to users but can lead also to a large number of security threats and attacks. In this survey paper, a new compacted and optimized architecture for IoT is proposed based on five layers. Likewise, we propose a new classification of security threats and attacks based on new IoT architecture. The IoT architecture involves a physical perception layer, a network and protocol layer, a transport layer, an application layer, and a data and cloud services layer. First, the physical sensing layer incorporates the basic hardware used by IoT. Second, we highlight the various network and protocol technologies employed by IoT, and review the security threats and solutions. Transport protocols are exhibited and the security threats against them are discussed while providing common solutions. Then, the application layer involves application protocols and lightweight encryption algorithms for IoT. Finally, in the data and cloud services layer, the main important security features of IoT cloud platforms are addressed, involving confidentiality, integrity, authorization, authentication, and encryption protocols. The paper is concluded by presenting the open research issues and future directions towards securing IoT, including the lack of standardized lightweight encryption algorithms, the use of machine-learning algorithms to enhance security and the related challenges, the use of Blockchain to address security challenges in IoT, and the implications of IoT deployment in 5G and beyond

Use of natural fluorescent triacyglycerols from Parinari glaberrimum to detect low lipase activity in Brassica napus seedlings

Lipases (triacylglycerol acyl hydrolass EC 3.1.1.3) are defined as enzymes that catalyse the hydrolysis of triacylglycerols, releasing long-chain fatty acids. Germinating oilseeds have been explored as a possible source of lipases for biotechnological processing of oils and fats. However, purification and sensitive assays to detect a true lipase activity in plant cellular homogenates and culture media are required. The main aim of this study was to design a convenient, specific, sensitive and continuous lipase activity assay using natural long-chain triacylglycerols (TAGs). Oil was extracted from Parinari glaberrimum seed kernels and the purified TAGs were used as a substrate for detecting low levels of lipase activities. An increase in the fluorescence was observed, which is due to the parinaric acid released by various lipase activities. This increase in the fluorescence intensity is linear with time and proportional to the amount of lipase added. This new method, performed under non-oxidative conditions, was applied successfully to detect low lipase levels in crude protein extracts from plant seeds.Keywords: Brassica napus, fluorescent lipids, lipase assay, plant lipasesAfrican Journal of Biotechnology Vol. 12(23), pp. 3719-372

Immunopurification and characterization of a rape (Brassica napus L.) seedling lipase

Lipase or triacylglycerol acylhydrolase (E.C.3.1.1.3) was purified to homogeneity from rapeseed-germinated cotyledons (Brassica napus L.). The purification scheme involved homogenization, centrifugation, ultracentrifugation and affinity chromatography using polyclonal antibodies raised against porcine pancreatic lipase. The purified rapeseed lipase was homogenous and did not contain contaminating proteins detectable by SDS-PAGE and HPLC analysis. The specific activity of the purified preparation was increased about 1950 times, with an overall yield of 35%. The rapeseed lipase was found to be a cytosoluble, glycosylated and heat-labile serine-hydrolase. It was monomeric with a molecular mass of 38 kDa and a pH of 6.6. The purification method used in the present work is rapid, simple, and yields highly purified lipase. It may therefore be applicable in the purification of other uncharacterized plant lipases.Keywords: Brassica napus L., immuno-affinity, lipase, purification, triacylglycerol acyl hydrolaseAfrican Journal of Biotechnology Vol. 12(21), pp. 3224-323

Towards securing machine learning models against membership inference attacks

From fraud detection to speech recognition, including price prediction, Machine Learning (ML) applications are manifold and can significantly improve different areas. Nevertheless, machine learning models are vulnerable and are exposed to different security and privacy attacks. Hence, these issues should be addressed while using ML models to preserve the security and privacy of the data used. There is a need to secure ML models, especially in the training phase to preserve the privacy of the training datasets and to minimise the information leakage. In this paper, we present an overview of ML threats and vulnerabilities, and we highlight current progress in the research works proposing defence techniques against ML security and privacy attacks. The relevant background for the different attacks occurring in both the training and testing/inferring phases is introduced before presenting a detailed overview of Membership Inference Attacks (MIA) and the related countermeasures. In this paper, we introduce a countermeasure against membership inference attacks (MIA) on Conventional Neural Networks (CNN) based on dropout and L2 regularization. Through experimental analysis, we demonstrate that this defence technique can mitigate the risks of MIA attacks while ensuring an acceptable accuracy of the model. Indeed, using CNN model training on two datasets CIFAR-10 and CIFAR-100, we empirically verify the ability of our defence strategy to decrease the impact of MIA on our model and we compare results of five different classifiers. Moreover, we present a solution to achieve a trade-off between the performance of the model and the mitigation of MIA attack

Splitting Arabic Texts into Elementary Discourse Units

International audienceIn this article, we propose the first work that investigates the feasibility of Arabic discourse segmentation into elementary discourse units within the segmented discourse representation theory framework. We first describe our annotation scheme that defines a set of principles to guide the segmentation process. Two corpora have been annotated according to this scheme: elementary school textbooks and newspaper documents extracted from the syntactically annotated Arabic Treebank. Then, we propose a multiclass supervised learning approach that predicts nested units. Our approach uses a combination of punctuation, morphological, lexical, and shallow syntactic features. We investigate how each feature contributes to the learning process. We show that an extensive morphological analysis is crucial to achieve good results in both corpora. In addition, we show that adding chunks does not boost the performance of our system

Inhibition de germination du pollen in vitro pour caractériser l'auto-incompatibilité d'origine pistillaire chez l'olivier (Olea europaea L.)

Inhibition of in vitro pollen germination to characterize the pistil origin of the autoincompatibility of olive (Olea europaea L). The in vitro pollen compatibility of the two table olive varieties 'Meski' (Tunisia) and 'Picholine' (France) was studied for five trees under irrigated conditions. Evaluation of the results demonstrated that 'Picholine' had the highest germination rate of pollen grains on standard culture medium at 86.4%. The autocompatibility test for 'Meski' showed a decrease in the germination rate from 44.8 to 21% when pollen grains were placed on a medium containing its pistil mixture. 'Picholine', meanwhile, exhibited stable or even decreased values ranging from 76 to 87% with its own pistil mixture. The 'Picholine' pollen exhibited its highest germination rate (77.6%) in the medium containing the 'Meski' pistil mixture, indicating the intercompatibility of 'Meski'. The addition to the medium of phenolic components extracted from 'Meski' pistils at three concentrations showed that the lowest germination rate of 'Meski' pollen grains (9.7%) was obtained at the highest concentration, C3 (2.826 mg·ml-1). The inhibitory effect of this concentration was significantly lower on the 'Picholine' pollen grains at 45%

Genetic differences between Tunisian camel and sheep strains of the cestode Echinococcus granulosus revealed by SSCP

Ovine and dromedary Echinococcus granulosus isolates from Tunisia were identified as G1 and G6 strains based on polymorphism of the mitochondrial cytochrome C oxydase CO1. Single strand conformation polymorphism (SSCP) was used in order to examine the genetic variation within and between Tunisian G1 and G6 strains and to estimate the extent of selfing. The dromedary isolates are genetically distinct from sheep isolates (high value of genetic variation between populations: Fst = 0.46). No significant deficiency in heterozygotes was found in sheep isolates, whereas heterozygote deficiency (suggesting selfing) was found in a limited number of camel isolates.Les Echinococcus granulosus de Tunisie ont été identifiés comme appartenant aux lignées G1 et G6 en se fondant sur le polymorphisme de la cytochrome oxydase CO1. Le polymorphisme de conformation simple brin (SSCP) a été utilisé afin d’évaluer la variabilité génétique intra et inter-isolats des lignées G1 et G6, et pour estimer le taux d’autofécondation. Les isolats issus de dromadaires sont génétiquement distincts des isolats ovins (valeur de Fst : 0,46). Il n’y a pas de déficit significatif en hétérozygotes chez les isolats ovins. Un déficit en hétérozygotes est présent dans les isolats du dromadaire, ce qui suggère l’autofécondation comme l’un des modes de reproduction