Efficient blockchain-based group key distribution for secure authentication in VANETs

This paper proposes a group key distribution scheme using smart contract-based blockchain technology. The smart contract’s functions allow for securely distributing the group session key, following the initial legitimacy detection using public key infrastructure-based authentication. For message authentication, we propose a lightweight symmetric key cryptography-based group signature method, supporting the security and privacy requirements of vehicular ad hoc networks (VANETs). Our discussion examined the scheme’s robustness against typical adversarial attacks. To evaluate the gas costs associated with smart contract’s functions, we implemented it on the Ethereum main network. Finally, comprehensive analyses of computation and communication costs demonstrate the scheme’s effectiveness

Blockchain-based secret key extraction for efficient and secure authentication in VANETs

Intelligent transportation systems are an emerging technology that facilitates real-time vehicle-to-everything communication. Hence, securing and authenticating data packets for intra- and inter-vehicle communication are fundamental security services in vehicular ad-hoc networks (VANETs). However, public-key cryptography (PKC) is commonly used in signature-based authentication, which consumes significant computation resources and communication bandwidth for signatures generation and verification, and key distribution. Therefore, physical layer-based secret key extraction has emerged as an effective candidate for key agreement, exploiting the randomness and reciprocity features of wireless channels. However, the imperfect channel reciprocity generates discrepancies in the extracted key, and existing reconciliation algorithms suffer from significant communication costs and security issues. In this paper, PKC-based authentication is used for initial legitimacy detection and exchanging authenticated probing packets. Accordingly, we propose a blockchain-based reconciliation technique that allows the trusted third party (TTP) to publish the correction sequence of the mismatched bits through a transaction using a smart contract. The smart contract functions enable the TTP to map the transaction address to vehicle-related information and allow vehicles to obtain the transaction contents securely. The obtained shared key is then used for symmetric key cryptography (SKC)-based authentication for subsequent transmissions, saving significant computation and communication costs. The correctness and security robustness of the scheme are proved using Burrows–Abadi–Needham (BAN)-logic and Automated Validation of Internet Security Protocols and Applications (AVISPA) simulator. We also discussed the scheme’s resistance to typical attacks. The scheme’s performance in terms of packet delay and loss ratio is evaluated using the network simulator (OMNeT++). Finally, the computation analysis shows that the scheme saves ~99% of the time required to verify 1000 messages compared to existing PKC-based schemes

An Efficient Cross-Layer Authentication Scheme for Secure Communication in Vehicular Ad-hoc Networks

Intelligent transportation systems contribute to improved traffic safety by facilitating real-time communication between vehicles and infrastructures. In this context, message authentication is crucial to safeguard vehicular ad-hoc networks (VANETs) from malicious attacks. The current state-of-the-art for authentication in VANETs relies on conventional cryptographic primitives, introducing significant computation and communication overheads. This paper presents a cross-layer authentication scheme for vehicular communication, incorporating the short-term reciprocal features of the wireless channel for re-authenticating the corresponding terminal, reducing the overall complexity and computation and communication overheads. The proposed scheme comprises four steps: S1. Upper-layer authentication is used to determine the legitimacy of the corresponding terminal at the first time slot; S2. Upon the verification result, a location-dependent shared key with a minimum number of mismatched bits is extracted between both terminals; S3. Using the extracted key and under binary hypothesis testing, a PHY challenge-response algorithm for multicarrier communication is proposed for re-authentication; S4. In the case of false detection, the key extraction step (S2) is re-executed after adapting the quantisation levels at different conditions of channel non-reciprocity based on the feedback from the re-authentication step (S3). Simulation results show the effectiveness of the proposed scheme even at small signal-to-noise ratios. In addition, the immunity of the proposed scheme is proved against active and passive attacks, including signatures' unforgeability against adaptive chosen message attacks in the random oracle model. Finally, a comprehensive comparison in terms of computation and communication overheads demonstrates the superiority of the proposed scheme over its best rivals

An improved indoor positioning based on crowd-sensing data fusion and particle filter

Due to the lack of global positioning system (GPS) signals in some enclosed areas, indoor localization has recently gained significant importance for academics. However, indoor localization has a number of challenges and defects, including accuracy, cost, coverage, and ease of use. This paper explores the integration between the inertial measurement unit (IMU) and Wi-Fi-based received signal strength indicator (RSSI) measurements, demonstrating their combined potential for robust indoor localization. IMUs excel at capturing precise short-term motion dynamics, offering insights into an object’s acceleration and orientation. Conversely, RSSI measurements serve as valuable indicators for relative positioning within indoor environments. By fusing data from these sources, our approach compensates for the inherent weaknesses of each sensor type. To achieve accurate indoor positioning, we employ techniques such as sensor fusion, Wi-Fi fingerprinting, and dead reckoning. Wi-Fi fingerprinting allows us to create a database that maps RSSI measurements to specific locations, while dead reckoning helps mitigate drift and inaccuracies. By combining these methods, we estimate a device’s position with increased precision. Through experimental evaluation, we assess the performance and efficiency of our integrated approach, comparing the estimated path or new location with a predefined reference path. The findings emphasise a significant improvement in accuracy, with the integration of crowd-sensing, particle filtering, and magnetic fingerprinting techniques resulting in a notable increase from 80.49% to 96.32% accuracy

Signaling mechanisms of a water soluble curcumin derivative in experimental type 1 diabetes with cardiomyopathy

BACKGROUND: Curcumin exhibits anti-diabetic activities, induces heme-oxygenase-1 (HO-1) and is an inhibitor of transcriptional co-activator p300. A novel water soluble curcumin derivative (NCD) has been developed to overcome low invivo bioavailability of curcumin. We evaluated the effect of the NCD on signaling mechanisms involved in cardiomyocyte hypertrophy and studied whether its action is mediated via inducible HO-1. MATERIALS AND METHODS: Rats were divided into controls, controls receiving NCD, diabetic, diabetic receiving NCD, diabetic receiving pure curcumin, diabetic receiving HO inhibitor, zinc protoporphyrin IX (ZnPP IX) and diabetic receiving NCD and ZnPP IX. NCD and curcumin were given orally. After 45 days, cardiac physiologic parameters, plasma glucose, insulin, glycated hemoglobin (GHb), HO-1 gene expression and HO activity in pancreas and cardiac tissues were assessed. Gene expression of p300, atrial natriuretic peptide (ANP) and myocyte enhancer factor 2 (MEF2A and MEF2C) were studied. RESULTS: NCD and curcumin decreased plasma glucose, GHb and increased insulin levels significantly in diabetic rats. This action may be partially mediated by induction of HO-1 gene. HO-1 gene expression and HO activity were significantly increased in diabetic heart and pancreas. Diabetes upregulated the expression of ANP, MEF2A, MEF2C and p300. NCD and curcumin prevented diabetes-induced upregulation of these parameters and improved left ventricular function. The effect of the NCD was better than the same dose of curcumin

A Comparative Study of Single and Multi-Stage Forecasting Algorithms for the Prediction of Electricity Consumption Using a UK-National Health Service (NHS) Hospital Dataset

Accurately looking into the future was a significantly major challenge prior to the era of big data, but with rapid advancements in the Internet of Things (IoT), Artificial Intelligence (AI), and the data availability around us, this has become relatively easier. Nevertheless, in order to ensure high-accuracy forecasting, it is crucial to consider suitable algorithms and the impact of the extracted features. This paper presents a framework to evaluate a total of nine forecasting algorithms categorised into single and multistage models, constructed from the Prophet, Support Vector Regression (SVR), Long Short-Term Memory (LSTM), and the Least Absolute Shrinkage and Selection Operator (LASSO) approaches, applied to an electricity demand dataset from an NHS hospital. The aim is to see such techniques widely used in accurately predicting energy consumption, limiting the negative impacts of future waste on energy, and making a contribution towards the 2050 net zero carbon target. The proposed method accounts for patterns in demand and temperature to accurately forecast consumption. The Coefficient of Determination (R 2 ), Mean Absolute Error (MAE), and Root Mean Square Error (RMSE) were used to evaluate the algorithms’ performance. The results show the superiority of the Long Short-Term Memory (LSTM) model and the multistage Facebook Prophet model, with R 2 values of 87.20% and 68.06%, respectivel

Antimicrobial resistance among migrants in Europe: a systematic review and meta-analysis

BACKGROUND: Rates of antimicrobial resistance (AMR) are rising globally and there is concern that increased migration is contributing to the burden of antibiotic resistance in Europe. However, the effect of migration on the burden of AMR in Europe has not yet been comprehensively examined. Therefore, we did a systematic review and meta-analysis to identify and synthesise data for AMR carriage or infection in migrants to Europe to examine differences in patterns of AMR across migrant groups and in different settings. METHODS: For this systematic review and meta-analysis, we searched MEDLINE, Embase, PubMed, and Scopus with no language restrictions from Jan 1, 2000, to Jan 18, 2017, for primary data from observational studies reporting antibacterial resistance in common bacterial pathogens among migrants to 21 European Union-15 and European Economic Area countries. To be eligible for inclusion, studies had to report data on carriage or infection with laboratory-confirmed antibiotic-resistant organisms in migrant populations. We extracted data from eligible studies and assessed quality using piloted, standardised forms. We did not examine drug resistance in tuberculosis and excluded articles solely reporting on this parameter. We also excluded articles in which migrant status was determined by ethnicity, country of birth of participants' parents, or was not defined, and articles in which data were not disaggregated by migrant status. Outcomes were carriage of or infection with antibiotic-resistant organisms. We used random-effects models to calculate the pooled prevalence of each outcome. The study protocol is registered with PROSPERO, number CRD42016043681. FINDINGS: We identified 2274 articles, of which 23 observational studies reporting on antibiotic resistance in 2319 migrants were included. The pooled prevalence of any AMR carriage or AMR infection in migrants was 25·4% (95% CI 19·1-31·8; I2 =98%), including meticillin-resistant Staphylococcus aureus (7·8%, 4·8-10·7; I2 =92%) and antibiotic-resistant Gram-negative bacteria (27·2%, 17·6-36·8; I2 =94%). The pooled prevalence of any AMR carriage or infection was higher in refugees and asylum seekers (33·0%, 18·3-47·6; I2 =98%) than in other migrant groups (6·6%, 1·8-11·3; I2 =92%). The pooled prevalence of antibiotic-resistant organisms was slightly higher in high-migrant community settings (33·1%, 11·1-55·1; I2 =96%) than in migrants in hospitals (24·3%, 16·1-32·6; I2 =98%). We did not find evidence of high rates of transmission of AMR from migrant to host populations. INTERPRETATION: Migrants are exposed to conditions favouring the emergence of drug resistance during transit and in host countries in Europe. Increased antibiotic resistance among refugees and asylum seekers and in high-migrant community settings (such as refugee camps and detention facilities) highlights the need for improved living conditions, access to health care, and initiatives to facilitate detection of and appropriate high-quality treatment for antibiotic-resistant infections during transit and in host countries. Protocols for the prevention and control of infection and for antibiotic surveillance need to be integrated in all aspects of health care, which should be accessible for all migrant groups, and should target determinants of AMR before, during, and after migration. FUNDING: UK National Institute for Health Research Imperial Biomedical Research Centre, Imperial College Healthcare Charity, the Wellcome Trust, and UK National Institute for Health Research Health Protection Research Unit in Healthcare-associated Infections and Antimictobial Resistance at Imperial College London

Perspective Chapter: The Toxic Silver (Hg)

In the late 1950s, residents of a Japanese fishing village known as “Minamata” began falling ill and dying at an alarming rate. The Japanese authorities stated that methyl-mercury-rich seafood and shellfish caused the sickness. Burning fossil fuels represent ≈52.7% of Hg emissions. The majorities of mercury’s compounds are volatile and thus travel hundreds of miles with wind before being deposited on the earth’s surface. High acidity and dissolved organic carbon increase Hg-mobility in soil to enter the food chain. Additionally, Hg is taken up by areal plant parts via gas exchange. Mercury has no identified role in plants while exhibiting high affinity to form complexes with soft ligands such as sulfur and this consequently inactivates amino acids and sulfur-containing antioxidants. Long-term human exposure to Hg leads to neurotoxicity in children and adults, immunological, cardiac, and motor reproductive and genetic disorders. Accordingly, remediating contaminated soils has become an obligation. Mercury, like other potentially toxic elements, is not biodegradable, and therefore, its remediation should encompass either removal of Hg from soils or even its immobilization. This chapter discusses Hg’s chemical behavior, sources, health dangers, and soil remediation methods to lower Hg levels