Decoding motion aftereffects from activity patterns in human visual cortex

Anonymous mutual authentication and key agreement scheme for wearable sensors in wireless body area networks

Wireless body area network (WBAN) provide a mechanism of transmitting a persons physiological data to application providers e.g. hospital. Given the limited range of connectivity associated with WBAN, an intermediate portable device e.g. smartphone, placed within WBAN's connectivity, forwards the data to a remote server. This data, if not protected from an unauthorized access and modification may be lead to poor diagnosis. In order to ensure security and privacy between WBAN and a server at the application provider, several authentication schemes have been proposed. Recently, Wang and Zhang proposed an authentication scheme for WBAN using bilinear pairing. However, in their scheme, an application provider could easily impersonate a client. In order to overcome this weakness, we propose an efficient remote authentication scheme for WBAN. In terms of performance, our scheme can not only provide a malicious insider security, but also reduce running time of WBAN (client) by 51 % as compared to Wang and Zhang scheme.

Nowadays, the design and construction of efficient internet of things (IoTs) has become a new strategies for improving living quality of all aspects. Emerging as one of the most significant extension of medical IoTs, wireless body area networks (WBANs) is capable of monitoring crucial physiological and behavioral information through wearable sensors, offering a new paradigm for the next-generation healthcare systems. As a matter of fact, due to the inherent open wireless communicating characteristics, data security and user privacy issues of WBANs have attracted attentions from both industry and academia. So far, lots of relevant researches emphasize on secure transmission and privacy protection. However, the computation and communication limitations for individual WBAN sensor have not been taken proper consideration. Moreover, the implementation of cloud computing infrastructure has provided WBANs with superior transmission and processing qualities. Emphasizing on the above issues, this paper construct a pairing-free authentication and sensor cooperation scheme in cloud-assisted WBANs, where most of the practical requirements for WBAN sensors could be satisfied. Our design guarantee the sensor anonymity in the whole transmission session. Note that our design offers pairing-free validation procedure followed with active sensor cooperation, which is suitable for massive sensor scenarios. The security analysis proves that our designed scheme is capable of achieving desired security properties and offer adequate resistances to the charted malicious attacks. Meanwhile, security comparison demonstrates that the proposed protocol is secure compared with the state-of-the-arts.

This paper explores how the integration and performance of Wireless Body Area Networks (WBANs) contribute to sustainable healthcare practices. WBANs play a crucial role in reducing the environmental footprint of healthcare systems by providing continuous monitoring that can prevent unnecessary hospitalizations and reduce the consumption of disposable medical supplies. Additionally, the design of WBANs using environmentally friendly materials, low-power devices, and recyclable components is discussed to optimize the sustainability of healthcare practices. To enhance infrastructure, services, and quality of life, new technologies have been integrated to improve WBANs. Patients' essential health data may be continuously and instantly collected thanks to these networks, and healthcare providers can receive the data right away for quick analysis and action. WBANs have healthcare benefits, but there are also major drawbacks. Technologies that can combine low power consumption, minimal delay, and high enough data rates are needed for WBANs in order to support a variety of medical applications. The effectiveness of the LoRaWAN and IEEE 802.15.6 technologies in WBAN is assessed in this paper. With the use of seven crucial metrics which are throughput, arrival rate, delay, energy consumption, residual energy, network lifetime, and packet delivery ratio (PDR), this paper seeks to study which technology is appropriate with WBANs using NS3 as a simulation program. With network parameters, 1000 seconds, and 50 nodes, the paper evaluated the performance of each technology. The results show that IEEE 802.15.6 is superior in terms of throughput, PDR, and arrival rate whereas LoRaWAN is superior in terms of energy consumption, residual energy, network lifetime, and delay.

Wireless body area networks (WBANs) are an emerging technology expected to revolutionize mobile healthcare via the real-time monitoring and analysis of medical data. This article describes the generalized WBAN concept and examples of WBAN medical applications for a variety of users and scenarios. The properties of wireless communication channels used in WBANs - specifically the human body communications channel and the 60 GHz Millimeter-wave (mmWave) - highlight the challenges facing modern WBAN development. Several research topics related to WBAN implementation in 5G networks are examined, including simulating extremely high-frequency communications, routing protocols, energy harvesting, tailoring WBANs to individual users, and user satisfaction. Future WBAN developments related to 6G networks and quantum technologies are also explored to demonstrate the potential future of mobile health.

Wireless Body area Networks (WBANs)- groups of sensors deployed inside a human body- are envisioned to improve the healthcare domain by continuously monitoring and reporting patient's health to the health care systems. However, the nature of openly deployed sensor nodes, coupled with the lack of security, make it easy for intruders to attack WBANs. In this paper, we propose a new scheme, PMAS, to achieve mutual authentication between a cell phone (personal device representing the sink) and WBANs' sensor nodes. In addition, based on a modified idea of Diffie-Hellman key exchange scheme, we establish a shared secret key between that sink and every sensor node in the network. The security analysis shows that PMAS thwarts different attacks, including the replay, fake sink, fake sensor, and Denial of Service (DOS) attacks. Furthermore, comparing to previous authentication schemes, the computation and communication overheads added by our scheme are much smaller than those in previous schemes.

In humanware applications, resource constrained sensor devices are tactically placed on human body to form Wireless Body Area Networks (WBAN). Then the WBAN is used for monitoring biometrics and movements of human body. Keeping in mind the resource constrained devices, WBANs are treated just like wireless sensor networks when considering a solution for key management. However, WBANs differ from traditional wireless sensor networks in scale, topology and security requirements. Also, the WBANs can also use random values from biometric measurements for the generation of keys. These differences render the key management schemes of WSNs inefficient and overly complex for WBANs scenario. Therefore, we propose a key management scheme that is efficient and fulfills the security requirements of WBAN.

Recent years have seen a huge growth in Wireless body area network (WBAN) for monitoring human health, for processing and transmission of data and information. In WBAN tiny sensors are attached on the human body that monitor different parameters of the body and then send data further to the hospital server with the help of internet. This technology will make the human life more healthy and cheerful. WBAN faces many stringent problems in phases of delay, power, temperature and community lifetime which need to be taken into intention inside the design of various routing protocols. These routing protocol play a critical position in the general system performance in phases of delay like energy consumption, and temperature. WBAN is vital in radical look at on existing routing protocols. Mainly this paper contributes to review existing Ad-Hoc routing protocols. This paper also provides an overview on WBAN in health care, architecture of WBAN, non-medical and medical application and discussion about ad-hoc network routing protocol for WBAN.

In the field of health care, the Wireless Body Area Networks(WBANs), through placed miniaturization, low power consumption of sensor nodes in patient's body or on the surface to measure a variety of physiological parameters, to monitor or diagnose the health of human body. However, in this process, WBANs nodes usually use batteries, especially for implantable flexible node it is difficult to accomplish the replacement of batteries, the energy that the node can carry is very limited, so the efficient use of energy is the most important problem to consider when designing WBANs routing algorithm. By considering the factors such as residual energy of node, the importance level of node, path cost and path energy difference ratio, this paper gives the definition of Optimal Path of Energy Consumption(OPEC) in WBANs, and The Optimal Energy Consumption Artificial Bee Colony(ABC) Based WBANs(OEABC) is designed. The performance simulation is carried out to verify the effectiveness of the OEABC, compared with Genetic Algorithm and Ant Colony Algorithm, it shows that t the OEABC has a fast convergence rate.

FIFO Order reliable convergecast in WBAN

In the generation of communication technologies, IoT based WBAN enables inventive software to improve the quality of life of the patient, providing the healthcare provider helpful tools for monitoring the patient. However, there are sensitive information within the WBANs and insecure data violate the patient’s security and as a consequence may lead to wrong diagnosis or treatment. Authentication and key agreement schemes are considered crucial requirements to make communications secure. Furthermore, to achieve a level of high security in WBAN involves numerous challenges because of its resource constraints and critical applications. In this paper, We made a comparative performance study on authentication and key agreement on different schemes on the Internet of Things(IoT) based wireless body area network (WBAN) and reveals it has improved the security issues and increase the efficiency of the system.

The Wireless Body Area Networks (WBAN) is an emerging type of real-time monitoring used in the healthcare sector. It has the potential to revolutionize the healthcare sector by allowing patients not to physically visit doctor clinics or hospitals for medical checkups. But implementing such a system is challenged by many factors. The most important one is energy consumption. Energy consumption of all nodes in general and that of the gateway node in particular is critical. The gateway node is responsible for conveying sensor information to medical servers or doctors. Failure of the gateway node means failure of the overall WBAN system of a patient. Thus, extending the life time of the gateway node is a desirable objective in designing WBAN systems. As energy consumption is directly related to the end-to-end delay, Packet Delivery Ratio (PDR) and medium accessibility rate. So, placement on the human body in a location that is affected the least by delay and has high PDR and medium accessibility should be chosen as the placement location for the gateway node. In this paper, we identify the optimal placement location on the human body for a gateway node in terms of end-to-end delay, PDR, and back-off duration period.

Developments in wireless communications and wearable devices have facilitated the emergence of a network of tiny sensors embedded in, on or around human body called Wireless Body Area Network (WBAN). Over the last decade, WBAN has increasingly been playing a vital role in modern medical systems because of its potential to revolutionize healthcare delivery. The data collected by the sensors contain sensitive information and are transmitted via wireless channels. However, the openness of these channels makes WBAN vulnerable to attacks by unauthorized users. Therefore, secure authentication and data encryption schemes in WBAN are essential. The resource constraint nature of the sensors makes traditional cryptographic schemes unsuitable. Consequently, authentication schemes based on channel characteristics are proposed, which are more suitable with fewer requirements. However, existing approaches do not consider mutual authentication as well as passive/active attacks. Motivated by these limitations, we propose in this paper, a mutual authentication and data encryption scheme based on signal propagation characteristics and enhanced butterfly algorithm. To validate the effectiveness of our scheme, we conducted an extensive real-world experiment involving 5 volunteers in indoor and outdoor areas, under distinct scenarios. We further conducted security and performance analyses to validate the effectiveness of our scheme in terms of resources and its resilience to various attacks. The results of the experiments and the analyses show that our scheme could mutually identify legitimate users and protect user data against active/passive eavesdropping attacks with minimal overhead.

The recent advancement in wireless body area networks (WBAN) plays an important role in remote health care systems. However, these networks are suffering from data security and privacy threats. Lack of anonymous authentication and secure data communication leads to operation failure in WBAN. Computational cost and privacy preservation are the two major hindrances for anonymous authentication in many existing schemes. Therefore, a secure and efficient privacy-preserving anonymous authentication scheme is proposed to provide data security and privacy to the users with low computational and communication cost. The performance analysis and experimental simulation results ensure that our proposed anonymous authentication method outperforms the existing systems in terms of providing data security and privacy with less computational overhead.

Wireless Body Area Network (WBAN) is a pioneer trend in healthcare technology.A WBAN consists of small sensors that may be worn or implanted on the patient's body or around them.These sensors are responsible for sending wireless, real-time physiological signs of the patient's body (such as blood pressure, heart rate, blood sugar, temperature, breathing, etc.) to an intermediate device.An intermediate device (such as a mobile phone) collects and prepares data to send and display to the doctor.In the WBAN, since data is sent through all broadcasts, any cyber attack such as eavesdropping and data modification/ sabotage can be done.Any cyber-attack on a WBAN could jeopardize the patient's health; therefore, securing the WBAN plays a crucial role in healthcare applications.Due to the limitation of energy, memory, and processing power of sensors in WBAN, it is not possible to use traditional security methods, such as encryption and security protocols.For this reason, one of the methods to provid security in the WBAN is the use of intrusion detection systems.An intrusion detection system (IDS), as a second-line defense, is one of the security methods in computer networks.Intrusion detection is the intelligent monitoring of network or computer systems to find any security breach.These systems are divided into two groups, signature-based and anomaly-based.One of the advantages 1 55 160 of anomaly-based systems is the detection of zero-day attacks.Statistical, knowledge-based, data mining and machine learning methods can be used to implement anomaly-based intrusion detection systems.In this paper, a new IDS has been presented which is able to detect denial of service (DoS) attacks in a WBAN.The proposed IDS is a hybrid anomaly-based system using machine learning and feature engineering methods.In the proposed IDS, a genetic algorithm is used to select features of collected data, in a way that increases the performance of the IDS, and as a result the WBAN (increasing detection rate and reducing energy consumption in the node).Then, using support vector machine and k nearest neighbor algorithms, the data classification is performed to detect DoS traffic from regular data traffic.Simulation results indicate that the proposed IDS has effective performance with a 90% detection rate.