Cloud-assisted Wireless Body Area Networks Research Articles

Correction to: An Improved Certificateless Mutual Authentication and Key Agreement Protocol for Cloud-Assisted Wireless Body Area Networks

Correction to: An Improved Certificateless Mutual Authentication and Key Agreement Protocol for Cloud-Assisted Wireless Body Area Networks

An Improved Certificateless Mutual Authentication and Key Agreement Protocol for Cloud-Assisted Wireless Body Area Networks

An Improved Certificateless Mutual Authentication and Key Agreement Protocol for Cloud-Assisted Wireless Body Area Networks

Quality-Driven Energy-Efficient Big Data Aggregation in WBANs

In the Internet of Things (IoT) era, the development of wireless body area networks (WBANs) and their applications in big data infrastructure has gotten a lot of attention from the medical research community. Since sensor nodes are low-powered devices that require heterogeneous quality of service, managing large amounts of medical data is critical in WBANs. Therefore, effectively aggregating a large volume of medical data is important. In this context, we propose a quality-driven and energy-efficient big data aggregation approach for cloud-assisted WBANs. For both the intra-BAN (Phase I) and inter-BAN (Phase II) communications, the aggregation approach is cost effective. Extensive simulation results show that quality-driven energy-efficient big data aggregation for WBANs improves network efficiency in terms of traffic served and energy consumption by 5–7 and 7–8% as compared to the existing schemes.

An Efficient Certificate-Based Data Integrity Auditing Protocol for Cloud-Assisted WBANs

With the evolution of wireless body area networks (WBANs), wearable equipment will improve the human healthcare service. However, the medical data generated in WBANs increase dramatically with time, and the massive data cause the storage burden. With the help of cloud computing, the cloud service provider (CSP) can assist data owners in storing these data collected by sensors. By keeping their data in the CSP, the data integrity and authenticity is a big concern of data owners. To date, many data integrity auditing protocols have been proposed to address this issue. Most of them rely on traditional public-key mechanism, or identity-based cryptography (IBC), or certificateless cryptography (CLC). However, they suffer from the heavy cost of certificate management, key escrow, or the requirement of a secret channel for each user, respectively. To solve these drawbacks, we propose an efficient certificate-based data integrity auditing protocol for cloud-assisted WBANs. In our protocol, the computation cost in tag generation for a data block is fixed, and is independent of the size of the data block. We prove our protocol is secure in the random oracle model (ROM) and use the Java pairing-based cryptography library (JPBC) to implement the protocol. The experimental results show that our protocol is computationally efficient and practical.

Backdoor-resistant identity-based proxy re-encryption for cloud-assisted wireless body area networks

The wireless body area network (WBAN) provides users with real-time medical services. Meanwhile, the cloud technology provides greater storage space and computing power for medical data. Both of them have contribute to the development of telemedicine. In a cloud-assisted WBAN, the open network environment and the semi-trust cloud service providers expose the user’s private medical data to backdoor adversaries who can make exfiltration attacks, such as the algorithm substitution attack (ASA) through the process of data sharing. Therefore, it is necessary to find a secure and efficient medical data sharing scheme for the huge amount of medical data. In this paper, we first design an identity-based proxy re-encryption scheme with cryptographic reverse firewall (IBPRE-CRF), then show the application in a multiple-access telemedicine data sharing scenario. Security analysis shows that the IBPRE-CRF scheme provides chosen plaintext attack security and resists exfiltration attacks. Performance analysis shows that the IBPRE-CRF scheme has a significant communication and computational cost advantage while being resistant to exfiltration attacks in clouds. Therefore, our IBPRE-CRF scheme is suitable for telemedicine data sharing in a cloud-assisted WBAN.

Lightweight verifiable data management system for cloud-assisted wireless body area networks

Lightweight verifiable data management system for cloud-assisted wireless body area networks

A Certificateless Authentication and Key Agreement Scheme for Secure Cloud-assisted Wireless Body Area Network

A Certificateless Authentication and Key Agreement Scheme for Secure Cloud-assisted Wireless Body Area Network

Distributed Pricing Policy for Cloud-Assisted Body-to-Body Networks with Optimal QoS and Energy Considerations

Cloud-Assisted Wireless Body Area Networks (WBANs) is one of the key emerging technology for medical applications in the era of Internet-of-Things. In cloud-assisted WBANs, the WBANs are able to access the cloud resources, which are geographically close to the local Access Points (APs). However, in the presence of poor radio link-quality between cloud-assisted WBANs and APs, energy consumption and service delay of the network dynamically changed. Therefore, in order to solve this problem, we propose an energy-efficient Body-to-Body (B2B) communications among coexisting WBANs to relay the information of the patients to nearest APs to provide real-time healthcare services. On the other hand, the healthcare services enabled for cloud-assisted WBANs is popularly known as Healthcare-as-a-Service (He-aaS). In He-aaS, it is very challenging to finalize a price agreement between WBANs and Health-Cloud Service Providers (H-CSPs) as WBANs follow a heterogeneous architecture. The existing pricing mechanisms, which are constrained to the homogeneous applications, are not compatible to He-aaS. We propose an optimal and distributed pricing policy for He-aaS in order to increase the profit level of each WBAN with the consideration of the optimal QoS and energy. Analysis of the proposed algorithms and the inferences of the results validates the usefulness of the proposed energy-efficient B2B communication and distributed pricing policy. Extensive results indicate that our proposed schemes are able to efficiently utilize limited resource with optimal QoS and energy consideration.

Practical pairing-Free sensor cooperation scheme for cloud-Assisted wireless body area networks

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.

Bargaining Solution-Based Resource Allocation Scheme for Cloud-Assisted Wireless Body Area Networks

Wireless body area network (WBAN) is an emerging technology that has enormous potentials for continuous health monitoring of various diseases. For different medical and healthcare applications, the collected physiological data from multiple WBANs are further transmitted to the remote medical cloud servers. However, several technical issues and challenges are associated with the integration of WBANs and cloud computing services. In this study, we develop a new cloud-assisted WBAN control scheme to effectively use the limited system resource. By employing the main ideas of Generalized Gini and Choquet bargaining solutions, our approach unfolds into dual stages of bargaining processes while increasing the flexibility and adaptability. In particular, we consider the unique features of cloud-assisted WBAN applications and provide a generalized fair-efficient solution for the resource allocation problem. Numerical simulation results demonstrate that we can verify the superiority of our proposed scheme over the existing protocols. Lastly, major further challenges and future research directions about the cloud-assisted WBAN paradigm are summarized and discussed.

LDVAS: Lattice-Based Designated Verifier Auditing Scheme for Electronic Medical Data in Cloud-Assisted WBANs

Data integrity has become an extremely important security issue in cloud-assisted wireless body area networks (WBANs). As accurate medical diagnostic analysis is heavily based on outsourced electronic medical data in cloud storage, any corrupted data may lead to fateful consequences. Data auditing contributes to medical data integrity verification, but most of existing data auditing schemes are vulnerable to attackers equipped with practical quantum-computing devices, which are very likely to be invented in the near future. Besides, in many scenarios, a patient has no capability to execute medical data integrity verification personally, he/she has to specify a verifier to complete data auditing. To this end, we present an efficient lattice-based designated verifier auditing scheme (LDVAS), which could be well deployed in cloud-assisted WBANs. In particular, LDVAS enables a patient to designate a unique verifier to execute data auditing in post-quantum secure settings, and any others cannot fulfil such task without the approval of the patient. We formally prove the security of LDVAS based on the hardness assumptions of lattice-based problems. The performance evaluation demonstrates the high efficiency and feasibility of LDVAS on the side of the designated verifier.

A Lightweight Fine-Grained Search Scheme over Encrypted Data in Cloud-Assisted Wireless Body Area Networks

The wireless body area networks (WBANs) have emerged as a highly promising technology that allows patients’ demographics to be collected by tiny wearable and implantable sensors. These data can be used to analyze and diagnose to improve the healthcare quality of patients. However, security and privacy preserving of the collected data is a major challenge on resource-limited WBANs devices and the urgent need for fine-grained search and lightweight access. To resolve these issues, in this paper, we propose a lightweight fine-grained search over encrypted data in WBANs by employing ciphertext policy attribute based encryption and searchable encryption technologies, of which the proposed scheme can provide resource-constraint end users with fine-grained keyword search and lightweight access simultaneously. We also formally define its security and prove that it is secure against both chosen plaintext attack and chosen keyword attack. Finally, we make a performance evaluation to demonstrate that our scheme is much more efficient and practical than the other related schemes, which makes the scheme more suitable for the real-world applications.

UMKESS: user-oriented multi-group key establishments using secret sharing

With the rapid development of group-oriented services, there are more and more multi-group communications in which users may join multiple group communications simultaneously. For example, in a wireless body area network (WBAN), medical personnels get together to hold a consultation for the patient and multiple consultation groups co-existed at the same time. A doctor may join more than one consultation groups simultaneously. Most existing group key establishment schemes establish a single group key for a single group. Applying a conventional group key establishment scheme in a straightforward manner (that is, running many times) can provide group-key-oriented multi-group key establishments. Since most group key establishment schemes suffer from larger rekeying overheads if users depart or join the network frequently, it is obvious that these schemes are not suitable for multiple groups co-existing applications such as WBAN. In this paper, we define a new type of user-oriented multi-group key establishments using secret sharing (UMKESS) for secure communications in WBAN. Since health data are private and sensitive information, efficient and secure data transmission in cloud-assisted WBANs is needed. In our proposed UMKESS, each user keeps only one share and uses the share to join multiple groups simultaneously, that is, or achieve multiple things at one stroke. Furthermore, the key generation center can manage user departing or joining dynamically with no rekeying overhead. The security strength of UMKESS is discussed in detail. In comparing to the latest group-key-oriented multi-group key establishment using secret sharing, UMKESS significantly improves the effectiveness of the multi-group communications and it is desirable for WBAN.

Certificateless Public Auditing Scheme for Cloud-Assisted Wireless Body Area Networks

Wireless body area networks (WBANs) consist of many small low-power sensors, through which users could monitor the real-time parameters of patients' physiology remotely. This capability could improve medical care and the monitoring of patients. WBAN devices typically have limited computing, storage, power, and communication capabilities. These limitations restrict the applications that WBANs can support. To enhance the capabilities of WBANs, the concept of cloud-assisted WBANs has been introduced recently. By using cloud computing technologies, cloud-assisted WBANs can provide more efficient processing of patients' physiology parameters and support richer services. In cloud-assisted WBANs, the data of patients' physiology are stored in the cloud. The integrity of the data is very important because these data will be used to provide a medical diagnosis and other medical treatments. To address the issue of integrity in cloud-assisted WBANs, we propose an efficient certificateless public auditing (CLPA) scheme. A security analysis of our proposed CLPA scheme shows that it is provably secure against two types of adversaries (i.e., a type-I adversary can replace users' public keys, and a type-II adversary can access the master key) in an environment of certificateless cryptography. A detailed performance analysis demonstrates that the proposed CLPA scheme yields better performance over a previously proposed CLPA scheme.

Cost-Effective Mapping between Wireless Body Area Networks and Cloud Service Providers Based on Multi-Stage Bargaining

This paper presents a bargaining-based resource allocation and price agreement in an environment of cloud-assisted Wireless Body Area Networks (WBANs). The challenge is to finalize a price agreement between the Cloud Service Providers (CSPs) and the WBANs, followed by a cost-effective mapping among them. Existing solutions primarily focus on profits of the CSPs, while guaranteeing different user satisfaction levels. Such pricing schemes are bias prone, as quantifying user satisfaction is fuzzy in nature and hard to implement. Moreover, such an traditional approach may lead to an unregulated market, where few service providers enjoy the monopoly/oligopoly situation. However, in this work, we try to remove such biasness from the pricing agreements, and envision this challenge from a comparatively fair point of view. In order to do so, we use the concept of bargaining , an interesting approach involving cooperative game theory. We introduce an exposition - multi-stage Nash bargaining solution (MUST-NBS), that unfolds into multiple stages of bargaining, as the name suggests, until we conclude price agreement between the CSPs and the WBANs. In addition, the proposed approach also consummates the final mapping between the CSPs and the WBANs, depending on the cost-effectiveness of the WBANs. Analysis of the proposed algorithms and the inferences of the results validates the usefulness of the proposed mapping technique.

Certificateless Public Auditing with Privacy Preserving for Cloud-Assisted Wireless Body Area Networks

With cloud computing being integrated with wireless body area networks, the digital ecosystem called cloud-assisted WBAN was proposed. In cloud-assisted medical systems, the integrity of the stored data is important. Recently, based on certificateless public key cryptography, He et al. proposed a certificateless public auditing scheme for cloud-assisted WBANs. But He et al.’s scheme is not a scheme with privacy preserving. After many checks on some of the same data blocks, the auditor can derive these data blocks. In this paper, we propose a certificateless public auditing scheme with privacy preserving for cloud-assisted WBANs. In the proof phase of the proposed scheme, the proof information is protected from being directly exposed to the auditor. So, the curious auditor could not derive the data blocks. We also prove that the proposed scheme is secure in the random oracle model under the assumption that the Diffie-Hellman problem is hard, and we give a comparison of the proposed scheme with He et al.’s scheme in terms of security and computation cost.

PPM-HDA: Privacy-Preserving and Multifunctional Health Data Aggregation With Fault Tolerance

Wireless body area networks (WBANs), as a promising health-care system, can provide tremendous benefits for timely and continuous patient care and remote health monitoring. Owing to the restriction of communication, computation and power in WBANs, cloud-assisted WBANs, which offer more reliable, intelligent, and timely health-care services for mobile users and patients, are receiving increasing attention. However, how to aggregate the health data multifunctionally and efficiently is still an open issue to the cloud server (CS). In this paper, we propose a privacy-preserving and multifunctional health data aggregation (PPM-HDA) mechanism with fault tolerance for cloud-assisted WBANs. With PPM-HDA, the CS can compute multiple statistical functions of users’ health data in a privacy-preserving way to offer various services. In particular, we first propose a multifunctional health data additive aggregation scheme (MHDA+) to support additive aggregate functions, such as average and variance. Then, we put forward MHDA $^{\oplus }$ as an extension of MHDA+ to support nonadditive aggregations, such as min/max, median, percentile, and histogram. The PPM-HDA can resist differential attacks, which most existing data aggregation schemes suffer from. The security analysis shows that the PPM-HDA can protect users’ privacy against many threats. Performance evaluations illustrate that the computational overhead of MHDA+ is significantly reduced with the assistance of CSs. Our MHDA $^{\oplus }$ scheme is more efficient than previously reported min/max aggregation schemes in terms of communication overhead when the applications require large plaintext space and highly accurate data.

A Secure Cloud-Assisted Wireless Body Area Network in Mobile Emergency Medical Care System.

Recent advances in medical treatment and emergency applications, the need of integrating wireless body area network (WBAN) with cloud computing can be motivated by providing useful and real time information about patients' health state to the doctors and emergency staffs. WBAN is a set of body sensors carried by the patient to collect and transmit numerous health items to medical clouds via wireless and public communication channels. Therefore, a cloud-assisted WBAN facilitates response in case of emergency which can save patients' lives. Since the patient's data is sensitive and private, it is important to provide strong security and protection on the patient's medical data over public and insecure communication channels. In this paper, we address the challenge of participant authentication in mobile emergency medical care systems for patients supervision and propose a secure cloud-assisted architecture for accessing and monitoring health items collected by WBAN. For ensuring a high level of security and providing a mutual authentication property, chaotic maps based authentication and key agreement mechanisms are designed according to the concept of Diffie-Hellman key exchange, which depends on the CMBDLP and CMBDHP problems. Security and performance analyses show how the proposed system guaranteed the patient privacy and the system confidentiality of sensitive medical data while preserving the low computation property in medical treatment and remote medical monitoring.

Performance evaluation of Enhanced Very Fast Decision Tree (EVFDT) mechanism for distributed denial-of-service attack detection in health care systems

Securing cloud-assisted Wireless Body Area Network (WBAN) environment by applying security mechanism that consumes less resources is still a challenging task. This research makes an attempt to address the same. One of the most prominent attacks in cloud-assisted WBAN is Distributed Denial of Service (DDoS) attack that not only disrupts the communication but also diminishes the network bandwidth and capacity. This work is an extension of our previous research work in which an Enhanced Very Fast Decision Tree (EVFDT) was proposed which could detect DDoS attack successfully. However, in our previous work, the proposed algorithm is evaluated on the dataset generated by implementing LEACH protocol in NS-2. In this paper, a real-time cloud-assisted WBAN test bed is deployed to investigate the efficiency and accuracy of proposed EVFDT algorithm for real-time sensor network traffic. To evaluate the performance of proposed algorithm on real-time WBAN, four metrics are used including classification accuracy, time, memory, and computational cost. It was observed that EVFDT outperforms the existing algorithms by maintaining better results for these metrics even in the presence of extreme noise. Experimental results show that the EVFDT algorithm attains significantly high detection accuracy with less false alarm rate.

A multimedia healthcare data sharing approach through cloud-based body area network

Wireless Body Area Network (WBAN), as a dramatic platform for pervasive computing and communication, has been widely applied in healthcare domains. Since the patient-related data in the form of text, image, voice, etc. is significant in the process of healthcare services, efficiently managing these media data from various WBAN is vital for various applications. Recently, Cloud-assisted WBAN has become popular that can supply massive computing, flexible storage and various software services to WBAN. Still, there are some challenging issues exist in this platform to deliver and share the huge media healthcare data to remote terminals timely with guaranteed QoS support. In the paper, we propose an efficient network model that combines WBAN and Cloud for valid data sharing. The proposed network architecture is designed as four layers: perception layer, network layer, cloud computing layer, and application layer. In the network, the integration of TCP/IP and Zigbee in the coordinator devices is utilized. Consequently, WBAN coordinators can compatibility inter-operate with various local networks such as WiFi and LTE network to support high mobility of users. Besides, we integrate Content Centric Networking (CCN) with our proposed architecture to improve the ability of the WBAN coordinator. Thus, it can support uninterrupted media healthcare content delivery. In addition, adaptive streaming technique was also utilized to reduce packet loss. Various simulations were conducted using OPNET simulator to show the feasibility of the proposed architecture in terms of transmitting a huge amount of media healthcare data in real-time under traditional IP-based network.