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BACKGROUND: In the Healthcare (HC) sector, the usage of Wireless Sensor Healthcare Networks (WSHN) is attaining specific importance. The sensor device is implanted into the patient's body, and the sensed health information of patients is transformed via data aggregating devices like mobile devices, cameras, and so on, to the doctors. Thus, the early signs of diseases are identified, and remote monitoring of the patient's health is carried out by the physician on time. This aids in improving the health condition of the people and reduces the severity of disorders. But, the security gap in HC remains unresolved, despite various advantages. OBJECTIVE: This work proposes secured data communication in WSHN using Exponential Message Digest5 (EXP-MD5) and Diffie Hellman Secret Key-based Elliptic Curve Cryptography (DHSK-ECC) techniques. METHODS: Primarily, the patient registers their details in the Hospital Cloud Server (HCS). With hospital ID and patient ID, public and private keys are generated during registration. Afterward, by utilizing the Navie Shuffling (NS) technique, nCr combinations are created and shuffled. After shuffling, any of the randomly selected combinations are encoded utilizing the American Standard Code for Information Interchange (ASCII) code. For patient authentication, the ASCII code is further converted into a Quick Response(QR) code. Upon successful registration, the patient logs in to HCS. The patient can book for doctor's appointment if the login details are verified with those of the registered details. On consulting the doctor at the pre-informed time, the digital signature is created utilizing the Universal Unique Salt-based Digital Signature Algorithm (UUS-DSA) for authenticating the patient details. Further, for providing accessibility to all the authorized patients, the registered patients on HCS are considered as nodes. Then, an authorized path is created using the EXP-MD5 technique to protect each individual patient's details. The patient's IoT data is sensed, followed by authorized path creation. The data is encrypted via the DHSK-ECC algorithm for secure data transmission. Lastly, all the information is stored in HCS, so that the patient's health condition is regularly monitored by the doctor and the needy advice is suggested to the patients in the future. Also, hash matching is carried out when the doctor needs to access data. RESULTS: The proposed technique's efficacy is validated by the performance analysis in comparison with other conventional techniques. CONCLUSION: In this proposed research, the authentication is performed in multiple scenarios to enhance data security and user privacy. The patient details are authenticated during registration and verification to access the online consultation only by the authorized person. Further, the patient health information is encrypted in the proposed work after consultation so that the intrusion of medical records by malicious users and data tampering is prevented. Also, the sensed data gathered from patients are transferred to the HCS by creating the authorized path, which further enhances the security of patient data. Thus, the data communication of the WSHN is well-secured in this work through multi-level authentication and improved cryptography techniques.
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BACKGROUND: Increasing numbers of cyber attacks threaten us personally and professionally. Cyber crimes include obtaining sensitive information (medical or financial) but may extend to organising heinous crimes including murders and aggravated sexual assaults. A major vector of cyber crimes is brute force attacks on secured shell servers. AIM OF STUDY: This research highlights the prevalence of the intensity of brute force attacks on secured shell servers via quali-quantitative analysis of cyber attacks. METHODOLOGY: The brute force attacks were recorded over a period of 20 days with the help of logs taken from five dedicated servers installed in a production environment. RESULTS: There were a minimum of 6470 and maximum of 22,715 attacks on a server per day. The total number of attacks on all the servers during the study period was 1,065,920. The brute force attacks were mainly targeted at the service network accounts. CONCLUSION: Growth of the field of cyber forensics is the optimal solution to prevent the malicious use of internet services and the commissioning of crimes by this means.
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The increasing challenges of agricultural processes and the growing demand for food globally are driving the industrial agriculture sector to adopt the concept of 'smart farming'. Smart farming systems, with their real-time management and high level of automation, can greatly improve productivity, food safety, and efficiency in the agri-food supply chain. This paper presents a customized smart farming system that uses a low-cost, low-power, and wide-range wireless sensor network based on Internet of Things (IoT) and Long Range (LoRa) technologies. In this system, LoRa connectivity is integrated with existing Programmable Logic Controllers (PLCs), which are commonly used in industry and farming to control multiple processes, devices, and machinery through the Simatic IOT2040. The system also includes a newly developed web-based monitoring application hosted on a cloud server, which processes data collected from the farm environment and allows for remote visualization and control of all connected devices. A Telegram bot is included for automated communication with users through this mobile messaging app. The proposed network structure has been tested, and the path loss in the wireless LoRa is evaluated.
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Heavy metals (HMs) in soil and water bodies greatly threaten human health. The wide separation of HMs urges the necessity to develop an expert system for HMs prediction and detection. In the current perspective, several propositions are discussed to design an innovative intelligence system for HMs prediction and detection in soil and water bodies. The intelligence system incorporates the Edge Cloud Server (ECS) data center, an innovative deep learning predictive model and the Federated Learning (FL) technology. The ECS data center is based on satellite sensing sources under human expertise ruling and HMs in-situ measurement. The FL system comprises a machine learning (ML) technique that trains an algorithm across multiple decentralized edge servers holding local data samples without exchanging them or breaching data privacy. The expected outcomes of the intelligence system are to quantify the soil and water bodies' HMs, develop new modified HMs pollution contamination indices and provide decision-makers and environmental experts with an appropriate vision of soil, surface water, and crop health.
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Metales Pesados , Contaminantes del Suelo , Monitoreo del Ambiente/métodos , Sistemas Especialistas , Humanos , Metales Pesados/análisis , Suelo , Contaminantes del Suelo/análisis , Tecnología , AguaRESUMEN
Public key encryption supporting equality test (PKEwET) schemes, because of their special function, have good applications in many fields, such as in cloud computing services, blockchain, and the Internet of Things. The original PKEwET has no authorization function. Subsequently, many PKEwET schemes have been proposed with the ability to perform authorization against various application scenarios. However, these schemes are incapable of traceability to the ciphertexts. In this paper, the ability of tracing to the ciphertexts is introduced into a PKEwET scheme. For the ciphertexts, the presented scheme supports not only the equality test, but also has the function of traceability. Meanwhile, the security of the proposed scheme is revealed by a game between an adversary and a simulator, and it achieves a desirable level of security. Depending on the attacker's privileges, it can resist OW-CCA security against an adversary with a trapdoor, and can resist IND-CCA security against an adversary without a trapdoor. Finally, the performance of the presented scheme is discussed.
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There are common problems in realistic medical consumables management such as inconsistent material names, irregular billing, extensive management of sub-warehouse. It is necessary to use information systems to achieve full-process, refined, traceable management of medical consumables. A cloud-based information management system of medical consumables is introduced, which connects consumables access, acceptance, consumption and settlement by matching UDI code, charge code and medical insurance code. The system connects to external systems such as charging system. The system realizes traceable management of full-process from manufacture, supplier to hospital material management department, and finally to consumption department. The management efficiency of medical consumables supply chain is improved.
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Sistemas de Información Administrativa , Administración de Materiales de HospitalRESUMEN
This study aimed to determine the prevalence and risk factors for brain white matter changes in normal young and middle-aged participants who underwent Brain Dock (brain screening). We analyzed 5,000 consecutive healthy participants from the Brain Dock registry between August to December 2018. Age, sex, body mass index (BMI), medical history, deep subcortical white matter high intensity (DSWMH), periventricular high intensity (PVH), and enlargement of perivascular space (EPVS) were investigated in relation to age. The prevalence of DSWMH, PVH, and EPVS were 35.3%, 14.0%, and 17.8%, respectively. Multivariate logistic regression analyses for brain white matter changes were conducted. The significant risk factors in participants aged < 50 years were: age (OR:1.09, 95% CI:1.07-1.12), the female sex (1.29, 1.03-1.60), BMI obesity (1.86, 1.12-3.08), and hypertension (1.67, 1.18-2.35) for DSWMH; age (1.08, 1.04-1.13) and the female sex (1.56, 1.03-2.36) for PVH; and age (1.07, 1.05-1.10) and the female sex (0.77, 0.60-1.00) for EPVS. In conclusion, age was consistently identified as a significant risk factor in young and middle-aged participants. Some risk factors for brain white matter changes were identified even in young and middle-aged participants in this study. Further longitudinal studies should be done in the future.
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Encéfalo/diagnóstico por imagen , Leucoencefalopatías/epidemiología , Sustancia Blanca/diagnóstico por imagen , Adolescente , Adulto , Anciano , Anciano de 80 o más Años , Bases de Datos Factuales , Femenino , Humanos , Leucoencefalopatías/diagnóstico por imagen , Leucoencefalopatías/etiología , Imagen por Resonancia Magnética , Masculino , Persona de Mediana Edad , Prevalencia , Sistema de Registros , Factores de Riesgo , Adulto JovenRESUMEN
Long-range radio (LoRa) communication is a widespread communication protocol that offers long range transmission and low data rates with minimum power consumption. In the context of solid waste management, only a low amount of data needs to be sent to the remote server. With this advantage, we proposed architecture for designing and developing a customized sensor node and gateway based on LoRa technology for realizing the filling level of the bins with minimal energy consumption. We evaluated the energy consumption of the proposed architecture by simulating it on the Framework for LoRa (FLoRa) simulation by varying distinct fundamental parameters of LoRa communication. This paper also provides the distinct evaluation metrics of the the long-range data rate, time on-air (ToA), LoRa sensitivity, link budget, and battery life of sensor node. Finally, the paper concludes with a real-time experimental setup, where we can receive the sensor data on the cloud server with a customized sensor node and gateway.
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This paper proposes an IoT system based on wireless BLE connectivity to monitor the moisture content of wood, using a compact and low-cost moisture device that relies on a resistance measurement method valid for an ultra-wide range of resistance values. This device is digitally controlled with a BLE-incorporated micro-controller characterized by its small size and low power consumption, providing long-life battery. The proposed system consists of two main parts: first, the BLE moisture device including the moisture content measurement and wireless capability (BLE); second, the cloud-based monitoring platform, providing remote visualization and control for all the sensor nodes of the network. The complete infrastructure shows how multiple nodes can read and transmit moisture content of timber in buildings using small and unattended devices, with data saved in a central database and monitored by multiple commercial devices such as PC, smartphone, tablet, etc. The proposed system is innovative, scalable and low cost, and it can be deployed in wooden buildings and the wood industry, providing a practical solution that will help to avoid rot and other damaging effects caused by the moisture content.
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The Industrial Internet of Things (IIoT) is of great significance to the improvement of industrial efficiency and quality, and to reduce industrial costs and resources. However, there are few openly-reported practical project applications based on the IIoT up to now. For legacy automation devices in traditional industry, it is especially challenging to realize the upgrading of industrial automation adopting the IIoT technology with less investment. Based on the practical engineering experience, this paper introduces the automation renovation of a sewage treatment plant. The legacy automation devices are upgraded by the central controller of a STM32 processor (Produced by STMicroelectronics company, located in Geneva, Switzerland), and the WeChatApplet (Developed by Tencent company, located in Shenzhen, China) is used as the extended host computer. A set of remote monitoring and control systems of sewage treatment based on the IIoT is built to realize the wide-area monitoring and control of sewage treatment. The paper describes the field hardware system, wide-area monitoring and control application program, management cloud platform and security technologies in detail. The actual operation results show that the monitoring system has the requirements of high accuracy, good real-time performance, reliable operation and low cost.
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The rapid development of driver fatigue detection technology indicates important significance of traffic safety. The authors' main goals of this Letter are principally three: (i) A middleware architecture, defined as process unit (PU), which can communicate with personal electroencephalography (EEG) node (PEN) and cloud server (CS). The PU receives EEG signals from PEN, recognises the fatigue state of the driver, and transfer this information to CS. The CS sends notification messages to the surrounding vehicles. (ii) An android application for fatigue detection is built. The application can be used for the driver to detect the state of his/her fatigue based on EEG signals, and warn neighbourhood vehicles. (iii) The detection algorithm for driver fatigue is applied based on fuzzy entropy. The idea of 10-fold cross-validation and support vector machine are used for classified calculation. Experimental results show that the average accurate rate of detecting driver fatigue is about 95%, which implying that the algorithm is validity in detecting state of driver fatigue.
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BACKGROUND: A sudden shortage of physician resources due to overwhelming patient needs can affect the quality of care in the emergency department (ED). Developing effective response strategies remains a challenging research area. We created a novel system using information and communication technology (ICT) to respond to a sudden shortage, and tested the system to determine whether it would compensate for a shortage. METHODS: Patients (n = 4890) transferred to a level I trauma center in Japan during 2012-2015 were studied. We assessed whether the system secured the necessary physicians without using other means such as phone or pager, and calculated fulfillment rate by the system as a primary outcome variable. We tested for the difference in probability of multiple casualties among total casualties transferred to the ED as an indicator of ability to respond to excessive patient needs, in a secondary analysis before and after system introduction. RESULTS: The system was activated 24 times (stand-by request [n = 12], attendance request [n = 12]) in 24 months, and secured the necessary physicians without using other means; fulfillment rate was 100%. There was no significant difference in the probability of multiple casualties during daytime weekdays hours before and after system introduction, while the probability of multiple casualties during night or weekend hours after system introduction significantly increased compared to before system introduction (4.8% vs. 12.9%, P < 0.0001). On the whole, the probability of multiple casualties increased more than 2 times after system introduction 6.2% vs. 13.6%, P < 0.0001). DISCUSSION: After introducing the system, probability of multiple casualties increased. Thus the system may contribute to improvement in the ability to respond to sudden excessive patient needs in multiple causalities. CONCLUSIONS: A novel system using ICT successfully secured immediate responses from needed physicians outside the hospital without increasing user workload, and increased the ability to respond to excessive patient needs. The system appears to be able to compensate for a shortage of physician in the ED due to excessive patient transfers, particularly during off-hours.