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Vehicular ad hoc Networks (VANETs) encompass the Internet of Vehicles, Vehicular Sensor Networks (VSNs), and electronic vehicles and tend to be an essential part of the world. In this network, communications are done through an open channel and are inevitably susceptible to a range of security issues. Their high mobility also adds to this concern. Roaming services are essential for global VANETs and mobility-based networks, which require a robust authentication mechanism to be maintained. Therefore, an effective and secure authentication and session key agreement mechanism in VANET is a challenge yet to be tackled. Recently, different three-party schemes were proposed to use in the handover authentication process, though they have their deficits. The present study showed that the three related schemes (Zhou et al., Patonico et al., and Eftekhari et al.) have security flaws such as insecurity against impersonation attack, key compromise impersonation attack, and man-in-the-middle attack. Also, a secure and robust handover authentication scheme is proposed for roaming service in VSNs, which stamps out the existing schemes' security problems. It considers the intra-network and inter-network roaming authentication models. Our proposed scheme, free from key escrow problems, is highly anonymous and provides forward/backward secrecy. Widely accepted random oracle model, AVISPA tool, and BAN logic used for security analysis. Our scheme outperforms the others in security metrics and improves communication overhead by up to 75%. Also, the simulation results show that our scheme is energy-efficient and imposes a lower end-to-end delay to the network.

Data aggregation is an effective mechanism to prolong lifetime in the wireless sensor networks by preventing extra data transmission. However, it may have some adverse effects on accuracy, confidentiality, delay, and privacy preserving. Sensing nodes tends to trade-off between energy demand and security issue. Data can be filtered by temporal correlation of sensory data, and thus, network traffic is controlled. Furthermore, data transmission via unnecessary nodes can be controlled by spatial correlation of sensing devices. This, in turn, prolongs network lifetime. CBDA algorithm was proposed by Hu et al. as a technique based on tree and chain formation and slice-mixing. However, we showed the proposed scheme was vulnerable to stolen key set attack and failed to provide forward secrecy. This has been fixed in proposed key distribution and agreement scheme. In this paper, we propose a continuous hybrid and energy-efficient secure data aggregation (CHESDA) algorithm that trades off between privacy preserving, data integrity, communication overload, delay and accuracy and then chooses the best scenario based on application and importance of the parameters. Here, privacy preserving is maintained by slice-mixing technique. Fuzzy logic is applied to choose optimal slicing in each subtree, and GNY logic is utilized to verify key authentication scheme. Results of analysis and simulations indicate that CHESDA, compared to PECDA and SMART, is more energy-efficient and highly secure with lower communication overhead.

Background: The development of preventive measures and promotion of healthcare delivery systems for disease management is dependent on detecting the incidence rates of the diseases and important risk factors. The current study aimed to determine some epidemiological indices and trends of the human brucellosis incidence in Iran between 2009 and 2017. Study design: A descriptive cross-sectional study. Methods: In the current study, online data were gathered from all cases of brucellosis who were potentially or definitely diagnosed and registered in medical centers, hospitals, laboratories, and private clinics in all districts of Iran. Epidemiologic questionnaires were used to collect data on demographic and background characteristics, risk factors, high-risk behaviors, and lab test results, respectively, based on the national brucellosis control plan. Results: A total of 138,448 cases of brucellosis have been studied in Iran from 2009 to 2017. The highest (25.89) and the lowest (12.07) incidence rates were observed in 2014 and 2009, respectively. In this nine-year study, the highest incidences were reported in the Hamadan, Lorestan, Kurdistan, and Kermanshah provinces. The cumulative percentages of the disease were estimated for different variables at the following rates: by gender: 57.9% for males; by age groups: 36.2% and 16.7% for the 25-44 and16-24 years age groups, respectively; by occupation: 33.2% for housewives; and by residential area: 75.7% for rural residents. Conclusions: Based on the obtained results, although the incidence of human brucellosis in Iran has declined since 2015, the number of cases has remained high.

Streptococcus pneumoniae is a common cause of community-acquired pneumonia, meningitis, and otitis media in children. The aim of this study was to determine the prevalence of nasopharyngeal carriage of Streptococcus pneumoniae among children in the city of Hamadan, west of Iran. In this cross-sectional study, 532 students aged 7 to 14 years old from Hamadan were enrolled during the period from February to April 2016. Children were recruited using multi-stage sampling method. Informed consent form was obtained from parents of children. A researcher developed checklist was completed for every child by interviewer and samples of the throat of children were taken by swap method from the nasopharyngeal area. Descriptive statistics and chi square test were used to describe the study population. This study was approved by the Committee on Ethics of Hamadan University of Medical Sciences (IR.UMSHA.REC.1394.66). Prevalence of nasopharyngeal carriage of S. pneumoniae in children was 12.03% (95%CI: 9.38–15.10). About 37% (196 persons) of study population were male and 63% were female. Sixty four percent (345 people) of the studied population were from district two in Hamadan and others from District one. Prevalence of nasopharyngeal carriage of S. pneumoniae by sex was 13.77% (95% CI: 9.27–19.40) in males and 11.02 % (95% CI: 7.87–14.85) in females (P = 0.345). Considering the high prevalence of nasopharyngeal carriage of Streptococcus pneumoniae in children studied in Hamadan, pneumococcal conjugate vaccine (PCV) is recommended to be integrated into the Iran’s National Immunization Program.

Background: The most recent emerging infectious disease, coronavirus disease 2019 (COVID-19), is pandemic now. Iran is a country with community transmission of the disease. Telehealth tools have been proved to be useful in controlling public health disasters. We developed an online self-screening platform to offer a population-wide strategy to control the massive influx to medical centers. Methods: We developed a platform operating based on given history by participants, including sex, age, weight, height, location, primary symptoms and signs, and high risk past medical histories. Based on a decision-making algorithm, participants were categorized into four levels of suspected cases, requiring diagnostic tests, supportive care, not suspected cases. We made comparisons with Iran STEPs (STEPwise approach to Surveillance) 2016 study and data from the Statistical Centre of Iran to assess population representativeness of data. Also, we made a comparison with officially confirmed cases to investigate the effectiveness of the platform. A multilevel mixed-effects Poisson regression was used to check the association of visiting platform and deaths caused by COVID-19. Results: About 310 000 individuals participated in the online self-screening platform in 33 days. The majority of participants were in younger age groups, and males involved more. A significant number of participants were screened not to be suspected or needing supportive care, and only 10.4% of males and 12.0% of females had suspected results of COVID-19. The penetration of the platform was assessed to be acceptable. A correlation coefficient of 0.51 was calculated between suspected results and confirmed cases of the disease, expressing the platform’s effectiveness. Conclusion: Implementation of a proper online self-screening tool can mitigate population panic during wide-spread epidemics and relieve massive influx to medical centers. Also, an evidence-based education platform can help fighting infodemic. Noticeable utilization and verified effectiveness of such platform validate the potency of telehealth tools in controlling epidemics and pandemics.

Security in wearable sensor networks and telecare medical information systems (TMIS) has turned to an issue of scholarly interest in recent years. Adequate security to agree on a temporary session key is essential for establishing a secure connection on various layers of the protocol stack in the Internet of Things (IoT) environments. Recently, Gupta et al. proposed a lightweight authentication and key agreement scheme for wearable sensing devices. Our analysis of Gupta et al.’s scheme revealed that it is insecure against privileged-insider attack, compromise sensing device, and desynchronization attacks in wearable sensor registration and login and authentication phases. In this paper, a Scalable Healthcare Authentication Protocol with Attack-Resilience and Anonymous Key-agreement, SHAPARAK, is proposed to overcome security flaws of existing schemes. The proposed protocol offers more scalability as it uses a public channel in the process of registration of each wearable sensing device. It also contains the password and biometrics changing phase without involvement of the trusted server. The security analysis of the proposed scheme is evaluated using the GNY logic, AVISPA tool, random oracle model, and informal security analysis. It is also shown that the proposed protocol is cost-efficient in terms of computation and communication overheads, compared to the existing schemes.

Dynamic wireless sensor network DWSN is a group of mobile sensor nodes deployed in an intended area. Secure communication in DWSNs depends on the existence of an efficient key management scheme. Because of the movements of sensor nodes and unknown mobility pattern, dynamic key management is an important issue in such networks. In this paper, we propose a new key management scheme, which uses key pre-distribution and post-deployment key establishment mechanisms for DWSNs. The proposed approach ensures that the two communicating nodes share at least one common key. It also provides efficient ways for key generation and revocation as well as addition or deletion of mobile sensor nodes. Compared with the other key management schemes, which are designed for DWSNs, our simulation and analytical results demonstrate the efficiency of the proposed approach in terms of confidentiality, resilience, memory usage, energy consumption and overhead. Copyright © 2014 John Wiley & Sons, Ltd.

The novel influenza A (H1N1) virus was first detected in March 2009 in Mexico and then disseminated to many other countries worldwide. In this study, we assessed the potential risk factors of swine flu as well as the most important clinical manifestations of this infectious disease among confirmed cases during early phase of pandemic H1N1.Subjects (cases and controls) were selected from those patients with signs and symptoms of respiratory tract infection who referred to health centers of eight cities throughout Hamedan Province, western Iran form July to December 2009. Characteristics of the participants were obtained by interviewers using pre-determined questionnaire. Cases were distinguished by pharyngeal soap speci-mens positive for influenza A virus using polymerase chain reaction (PCR). Logistic regression model was conducted at 0.05 significance level using Stata 9.1 statistical software to assess the effects of various risk factors on H1N1 influenza infection.Totally, 245 confirmed cases of H1N1 influenza were compared with 388 controls. Case fatality rate of influenza infection was about 2.86%. In comparison with age group of 1-19 yr old, adjusted odds ratio estimates was 1.91 [95% CI: 1.06, 3.46] for age group of 20-39 yr old, 0.94 [0.37, 2.38] for age group of 40-59 yr old, and 0.34 [0.09, 1.37] for age group of 60-79 yr old. Adjusted odds ratio estimates of influenza A infection was 8.12 [95% CI: 3.11, 21.6] for pregnant women compared to non-pregnant women; 1.84 [95% CI: 1.32, 2.86] for high educated individuals in comparison with low educated individuals; 2.11 [95% CI: 1.25, 3.57] for whose who had close contact with suspected influenza patients; and 2.15 [95% CI: 1.16, 3.98] for individuals with normal body mass index (BMI= 25-30) compared with underweight individuals (BMI20). There were no significant differences in clinical manifestations between cases and controls.The risk of influenza A infection is highest among children and adolescents, pregnant women, high educated individuals, and those who had close contact with suspected influenza patients during pandemic phase. In addition, there is no pathogonomonic sign or symptom to distinguish influenza infection clinically from other kinds of respiratory track infections.

Multi-join query optimization is an important technique for designing and implementing database management system. It is a crucial factor that affects the capability of database. This paper proposes a Bees algorithm that simulates the foraging behavior of honey bee swarm to solve Multi-join query optimization problem. The performance of the Bees algorithm and Ant Colony Optimization algorithm are compared with respect to computational time and the simulation result indicates that Bees algorithm is more effective and efficient.

Path‐finding problems are generally famous in computer sciences, specifically those which are associated with uncertain environments are very common in artificial intelligence. Although in such problems greedy approaches are computationally light‐weighted, they may not guarantee a good solution or even a solution. Our objective is to analyze the suitability of greedy solutions in a typical instance of uncertain path‐finding problems.

Foraging behavior of bees in finding food resource is one of the useful patterns to develop algorithms for solving complex problems. This article by simulation of such behavior and consider a memory for them proposed a method in discrete spaces. The proposed method is applied to Travel Salesman Problem (TSP) and successfully solved it. Simulation results have been proved the performance of our algorithm compared to similar strategies.