A lightweight secure adaptive approach for internet-of-medical-things healthcare applications in edge-cloud-based networks

Mobile-cloud-based healthcare applications are increasingly growing in practice. For instance, healthcare, transport, and shopping applications are designed on the basis of the mobile cloud. For executing mobile-cloud applications, offloading and scheduling are fundamental mechanisms. However, mobile healthcare workflow applications with these methods are widely ignored, demanding applications in various aspects for healthcare monitoring, live healthcare service, and biomedical firms. However, these offloading and scheduling schemes do not consider the workflow applications' execution in their models. This paper develops a lightweight secure efficient offloading scheduling (LSEOS) metaheuristic model. LSEOS consists of light weight, and secure offloading and scheduling methods whose execution offloading delay is less than that of existing methods. The objective of LSEOS is to run workflow applications on other nodes and minimize the delay and security risk in the system. The metaheuristic LSEOS consists of the following components: adaptive deadlines, sorting, and scheduling with neighborhood search schemes. Compared to current strategies for delay and security validation in a model, computational results revealed that the LSEOS outperformed all available offloading and scheduling methods for process applications by 10% security ratio and by 29% regarding delays

Dynamic application partitioning and task-scheduling secure schemes for biosensor healthcare workload in mobile edge cloud

Currently, the use of biosensor-enabled mobile healthcare workflow applications in mobile edge-cloud-enabled systems is increasing progressively. These applications are heavyweight and divided between a thin client mobile device and a thick server edge cloud for execution. Application partitioning is a mechanism in which applications are divided based on resource and energy parameters. However, existing application-partitioning schemes widely ignore security aspects for healthcare applications. This study devises a dynamic application-partitioning workload task-scheduling-secure (DAPWTS) algorithm framework that consists of different schemes, such as min-cut algorithm, searching node, energy-enabled scheduling, failure scheduling, and security schemes. The goal is to minimize the energy consumption of nodes and divide the application between local nodes and edge nodes by applying the secure min-cut algorithm. Furthermore, the study devises the secure-min-cut algorithm, which aims to migrate data between nodes in a secure form during application partitioning in the system. After partitioning the applications, the node-search algorithm searches optimally to run applications under their deadlines. The energy and failure schemes maintain the energy consumption of the nodes and the failure of the system. Simulation results show that DAPWTS outperforms existing baseline approaches by 30% in terms of energy consumption, deadline, and failure of applications in the system.publishedVersio

Cryptanalysis on Secure ECC based Mutual Authentication Protocol for Cloud-Assisted TMIS

The creation of TMIS (Telecare Medical Information System) makes it simpler for patients to receive healthcare services and opens up options for seeking medical attention and storing medical records with access control. With Wireless Medical Sensor Network and cloud-based architecture, TMIS gives the chance to patients to collect their physical health information from medical sensors and also upload this information to the cloud through their mobile devices. The communication is held through internet connectivity, therefore security and privacy are the main motive aspects of a secure cloud-assisted TMIS. However, because very sensitive data is transmitted between patients and doctors through the cloud server, thus security protection is important for this system. Recently, Kumar et al designed a mutual authentication protocol for cloud-assisted TMIS based on ECC [2]. In this paper, we revisited this scheme and traced out that their scheme has some significant pitfalls like health report revelation attack, and report confidentiality. In this study, we will provide the cryptanalysis of the scheme developed by Kumar et al

Healthcare support for underserved communities using a mobile social media platform

© 2017 Elsevier Ltd Emerging digital technologies for healthcare information support have already contributed to reducing the digital divide among rural communities. Although mobile health (m-health) applications facilitate provision of support for treatment consultation in real-time, their substantial potential has not yet been operationalised for decision support to meet citizen demand in developing nations. Modern healthcare information access, especially in rural areas of developing countries, is critical to effective healthcare, since both information and expert opinions are limited. Mobile phone and social media penetration, however, is often extensive. In this paper, we design and evaluate an innovative mobile decision support system (MDSS) solution for rural citizens healthcare decision support and information dissemination. Developed using a design science approach, the instantiated artifact connects underserved rural patients in Bangladesh to general practitioners (GPs) – allowing GPs, based on queries and information support provided, to evaluate patient conditions virtually and provide answers for further diagnosis or treatment. A cloud platform using social media embodies health record information and is used with a rating technique that matches queries to profiled remote experts, participating asynchronously. A comprehensive evaluation of the MDSS artifact ensures its utility, efficacy, and reliability

Providing security and fault tolerance in P2P connections between clouds for mHealth services

[EN] The mobile health (mHealth) and electronic health (eHealth) systems are useful to maintain a correct administration of health information and services. However, it is mandatory to ensure a secure data transmission and in case of a node failure, the system should not fall down. This fact is important because several vital systems could depend on this infrastructure. On the other hand, a cloud does not have infinite computational and storage resources in its infrastructure or would not provide all type of services. For this reason, it is important to establish an interrelation between clouds using communication protocols in order to provide scalability, efficiency, higher service availability and flexibility which allow the use of services, computing and storage resources of other clouds. In this paper, we propose the architecture and its secure protocol that allows exchanging information, data, services, computing and storage resources between all interconnected mHealth clouds. The system is based on a hierarchic architecture of two layers composed by nodes with different roles. The routing algorithm used to establish the connectivity between the nodes is the shortest path first (SPF), but it can be easily changed by any other one. Our architecture is highly scalable and allows adding new nodes and mHealth clouds easily, while it tries to maintain the load of the cloud balanced. Our protocol design includes node discovery, authentication and fault tolerance. We show the protocol operation and the secure system design. Finally we provide the performance results in a controlled test bench.Lloret, J.; Sendra, S.; Jimenez, JM.; Parra-Boronat, L. (2016). Providing security and fault tolerance in P2P connections between clouds for mHealth services. Peer-to-Peer Networking and Applications. 9(5):876-893. doi:10.1007/s12083-015-0378-3S87689395The Fifty-eighth World Health Assembly, Resolutions and Decisions. Document: A58/21. Available at: http://www.who.int/healthacademy/media/WHA58-28-en.pdf . [Last access: Dec. 30, 2014]World Health organization. Topics of eHealth. In WHO website. Available at: http://www.who.int/topics/eHealth/en/ . [Last access: Dec. 30, 2014]Pickup JC, Freeman SC, Sutton AJ (2011) Glycaemic control in type 1 diabetes during real time continuous glucose monitoring compared with self monitoring of blood glucose: meta-analysis of randomised controlled trials using individual patient data. BMJ 343:d3805Promotional Material Digital health: working in partnership. Department of Health. UK. (2014) Available at: https://www.gov.uk/government/publications/digital-health-working-in-partnership/digital-health-working-in-partnerships#digital-health---harnessing-technology-for-patient-benefit . [Last access: Dec. 30, 2014]eHealth for a Healthier Europe!– opportunities for a better use of healthcare resources. Available at: https://joinup.ec.europa.eu/sites/default/files/files_epractice/sites/eHealth%20for%20a%20Healthier%20Europe %20-%20Opportunities%20for%20a%20better%20use%20of%20healthcare%20resources.pdf. [Last access: Dec. 30, 2014]Adibi S (2012) Link technologies and BlackBerry mobile health (mHealth) solutions: a review. IEEE Trans Inf Technol Biomed 16(4):586–597Chiarini G, Ray P, Akter S, Masella C, Ganz A (2013) mHealth technologies for chronic diseases and elders: a systematic review. IEEE J Sel Areas Commun 31(9):6–18Lopes IM, Silva BM, Rodrigues JJ, Lloret J, Proenca ML (2011) A mobile health monitoring solution for weight control. In proceedings of the 2011 International Conference on Wireless Communications and Signal Processing (WCSP 2011), Nanjing, pp 1–5Lopes IM, Silva BM, Rodrigues JJPC, Lloret J (2012) Performance evaluation of cooperation mechanisms for m-health applications. In proceedings of the 2012 I.E. Global Communications Conference (GLOBECOM 2012), AnaheimKyriacou EC, Pattichis CS, Pattichis MS (2009) An overview of recent health care support systems for eEmergency and mHealth applications. In proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2009), Hilton Minneapolis, pp 1246–1249Nkosi MT, Mekuria F (2010) Cloud computing for enhanced mobile health applications. In proceedings of the 2010 I.E. Second International Conference on Cloud Computing Technology and Science (CloudCom 2010), Indianapolis, pp 629–633Sultan N (2014) Making use of cloud computing for healthcare provision: opportunities and challenges. Int J Inf Manag 34(2):177–184Pandey S, Voorsluys W, Niu S, Khandoker A, Buyya R (2012) An autonomic cloud environment for hosting ECG data analysis services. Futur Gener Comput Syst 28(1):147–154Xia H, Asif I, Zhao X (2013) Cloud-ECG for real time ECG monitoring and analysis. Comput Methods Prog Biomed 110(3):253–259Bourouis A, Feham M, Bouchachia A (2012) A new architecture of a ubiquitous health monitoring system: a prototype of cloud mobile health monitoring system. arXiv preprint. Reference: arXiv:1205.6910Chen KR, Lin YL, Huang MS (2011) A mobile biomedical device by novel antenna technology for cloud computing resource toward pervasive healthcare. In proceedings of the 11th International Conference on Bioinformatics and Bioengineering (BIBE 2011), Taichung, pp 133–136Lacuesta R, Lloret J, Sendra S, Peñalver L (2014), Spontaneous ad hoc mobile cloud computing network. Sci World J (Article ID 232419): 1–19Ghafoor KZ, Bakar KA, Mohammed MA, Lloret J (2013) Vehicular cloud computing: trends and challenges (Chapter 14). In Mobile Networks and Cloud computing Convergence for Progressive Services and Applications. IGI Global. pp. 262–274. DOI: 10.4018/978-1-4666-4781-7.ch014Wan J, Zhang D, Zhao S, Yang LT, Lloret J (2014) Context-aware vehicular cyber-physical systems with cloud support: architecture, challenges and solutions. IEEE Commun Mag 52(8):106–113. doi: 10.1109/MCOM.2014.6871677Rodrigues JJPC, Zhou L, Mendes LDP, Lin K, Lloret J (2012) Distributed media-aware flow scheduling in cloud computing environment. Comput Commun 35(15):1819–1827Dutta R, Annappa B (2014) Protection of data in unsecured public cloud environment with open, vulnerable networks using threshold-based secret sharing. Netw Protoc Algoritm 6(1):58–75Modares H, Lloret J, Moravejosharieh A, Salleh R (2013) Security in mobile cloud computing (Chapter 5). In Mobile Networks and Cloud computing Convergence for Progressive Services and Applications. IGI Global. pp. 79–91Mehmood A, Song H, Lloret J (2014) Multi-agent based framework for secure and reliable communication among open clouds. Netw Protoc Algoritm 6(4):60–76Mendes LDP, Rodrigues JJPC, Lloret J, Sendra S (2014) Cross-layer dynamic admission control for cloud-based multimedia sensor networks. IEEE Syst J 8(1):235–246Xiong J, Li F, Ma J, Liu X, Yao Z, Chen PS (2014) A full lifecycle privacy protection scheme for sensitive data in cloud computing. Peer-to-Peer Netw Appl 1–13Yang H, Kim H, Mtonga K (2014) An efficient privacy-preserving authentication scheme with adaptive key evolution in remote health monitoring system. Peer-to-Peer Netw Appl 1–11Silva BM, Rodrigues JJ, Canelo F, Lopes IM, Lloret J (2014) Towards a cooperative security system for mobile-health applications. Electron Commer Re 1–27Flynn D, Gregory P, Makki H, Gabbay M (2009) Expectations and experiences of eHealth in primary care: a qualitative practice-based investigation. Int J Med Inform 78(9):588–604Thampi SM (2010) Survey of search and replication schemes in unstructured P2P networks. Netw Protoc Algoritm 2(1):93–131Khan SM, Mallesh N, Nambiar A, Wright M (2010) The dynamics of salsa: a robust structured P2P system. Netw Protoc Algoritm 2(4):40–60Garcia M, Hammoumi M, Canovas A, Lloret J (2011) Controlling P2P file-sharing networks’ traffic. Netw Protoc Algoritm 3(4):54–92Lloret J, Garcia M, Tomas J, Rodrigues JJPC (2014) Architecture and protocol for InterCloud communication. Inf Sci 258:434–451Chowdhury CR (2014) A survey of cloud based health care system. Int J Innov Res Comput Commun Eng 2(8):5477–5481Ghosh R, Papapanagiotou I, Boloor KA (2014) Survey on research initiatives for healthcare clouds. Cloud Computing Applications for Quality Health Care Delivery. IGI Global 1–18Donahue S (2010) Can cloud computing help fix health care? Cloudbook J 1(6):1–6Deng M, Petkovic M, Nalin M, Baroni IA (2011) Home healthcare system in the cloud--addressing security and privacy challenges. In proceedings of the 2011 I.E. International Conference on Cloud Computing (CLOUD 2011), Washington, pp 549–556Wang X, Gui Q, Liu B, Chen Y, Jin Z (2013) Leveraging mobile cloud for telemedicine: a performance study in medical monitoring. In proceedings of the 39th Annual Northeast Bioengineering Conference (NEBEC 2013), Syracuse, pp 49–50Alamri A (2012) Cloud-based e-health multimedia framework for heterogeneous network. In proceedings of the 2012 I.E. International Conference on Multimedia and Expo Workshops (ICMEW 2012), Melbourne, pp 447–452Constantinescu L, Kim J, Feng DD (2012) Sparkmed: a framework for dynamic integration of multimedia medical data into distributed m-health systems. IEEE Trans Inf Technol Biomed 16(1):40–52Botts N, Thoms B, Noamani A, Horan TA (2010) Cloud computing architectures for the underserved: public health cyberinfrastructures through a network of healthatms. In proceedings of the 43rd Hawaii International Conference on System Sciences (HICSS 2010), Honolulu, pp 1–10Fan L, Buchanan W, Thummler C, Lo O, Khedim A, Uthmani O, Lawson A, Bell D (2011) DACAR platform for eHealth services cloud. In proceedings of the 2011 I.E. International Conference on Cloud Computing (CLOUD 2011), Washington, pp 219–226Ruiz-Zafra A, Benghazi K, Noguera M, Garrido JL (2013) Zappa: An Open Mobile Platform to Build Cloud-Based m-Health Systems. In proceedings of the 4th International Symposium on Ambient Intelligence (ISAmI 2013), Salamanca, pp 87–94Nijon S, Dickerson RF, Asare P, Li Q, Hong D, Stankovic JA, Hu P, Shen G, Jiang X (2013) Auditeur: a mobile-cloud service platform for acoustic event detection on smartphones. In Proceeding of the 11th annual international conference on Mobile systems, applications, and services. ACM, Taipei, pp 403–416Lloret J, Diaz JR, Boronat F, Jiménez JM (2006) A fault-tolerant P2P-based protocol for logical networks interconnection. In proceedings of the International Conference on Networking and Services (ICNS’06), Silicon ValleyLloret J, Palau C, Boronat F, Tomas J (2008) Improving networks using group-based topologies. Comput Commun 31(14):3438–3450Lloret J, Boronat Segui F, Palau C, Esteve M (2005) Two levels SPF-based system to interconnect partially decentralized P2P file sharing networks. In proceedings of the Joint International Conference on Autonomic and Autonomous Systems and International Conference on Networking and Services.(ICAS-ICNS 2005), Papeete, p 39Cramer C, Kutzner K, Fuhrmann T (2004) Bootstrapping locality-aware P2P networkS. In proceedings of the 12th IEEE International Conference on Networks (ICON 2004), Singapore, pp 357–361FIPS 180-1 - Secure Hash Standard, SHA-1. National Institute of Standards and Technology. http://www.itl.nist.gov/fipspubs/fip180-1.htm [Last access: Dec. 30, 2014]Eastlake D., Jones P., US Secure Hash Algorithm 1 (SHA1),(2001). In IETF website, Available at: http://www.ietf.org/rfc/rfc3174.txt [Last access: March 20, 2015]Lacuesta R, Lloret J, Garcia M, Peñalver L (2011) Two secure and energy-saving spontaneous Ad-Hoc protocol for wireless mesh client networks. J Netw Comput Appl 3(2):492–50

Cloud Assisted Mobile Access Of Health Data With Privacy And Audit Ability

— Monitoring and advising patients via mobile health care system is the current trend in medical field that acts as a life saver due to its availability at anytime and anywhere. This e-healthcare system requires patient’s private data to be available at cloud, outsourced data storage. This situation faces privacy issues. Hence the proposed approach focus on providing a private cloud for mobile users to ensure less cost, effective and secure storage. The data keyed in the mobile is transferred to private cloud, which in turn is processed and again transferred to public cloud. The sensitivity of the outsourced cloud data is maintained using Attribute based Encryption technique which restricts data access based on encrypt/decrypt of data with its access structures. The data privacy is ensured by PRF based key management and secures indexing methodologies. Personal Health records view ability access control to the actual data owner is the core idea of this project. The project segregates the access users in to Public Domain Users and Private Domain users

Hybrid Workload Enabled and Secure Healthcare Monitoring Sensing Framework in Distributed Fog-Cloud Network

The Internet of Medical Things (IoMT) workflow applications have been rapidly growing in practice. These internet-based applications can run on the distributed healthcare sensing system, which combines mobile computing, edge computing and cloud computing. Offloading and scheduling are the required methods in the distributed network. However, a security issue exists and it is hard to run different types of tasks (e.g., security, delay-sensitive, and delay-tolerant tasks) of IoMT applications on heterogeneous computing nodes. This work proposes a new healthcare architecture for workflow applications based on heterogeneous computing nodes layers: an application layer, management layer, and resource layer. The goal is to minimize the makespan of all applications. Based on these layers, the work proposes a secure offloading-efficient task scheduling (SEOS) algorithm framework, which includes the deadline division method, task sequencing rules, homomorphic security scheme, initial scheduling, and the variable neighbourhood searching method. The performance evaluation results show that the proposed plans outperform all existing baseline approaches for healthcare applications in terms of makespan

A Framework for Securing Health Information Using Blockchain in Cloud Hosted Cyber Physical Systems

Electronic Health Records (EHRs) have undergone numerous technical improvements in recent years, including the incorporation of mobile devices with the cloud computing technologies to facilitate medical data exchanges between patients and the healthcare professionals. This cutting-edge architecture enables cyber physical systems housed in the cloud to provide healthcare services with minimal operational costs, high flexibility, security, and EHR accessibility. If patient health information is stored in the hospital database, there will always be a risk of intrusion, i.e., unauthorized file access and information modification by attackers. To address this concern, we propose a decentralized EHR system based on Blockchain technology. To facilitate secure EHR exchange across various patients and medical providers, we develop a reliable access control method based on smart contracts. We incorporate Cryptocurrency, specifically Ethereum, in the suggested system to protect sensitive health information from potential attackers. In our suggested approach, both physicians and patients are required to be authenticated. Patients can register, and a block with a unique hash value will be generated. Once the patient discusses the disease with the physician, the physician can check the patient's condition and offer drugs. For experimental findings, we employ the public Block chain Ganache and solidity remix-based smart contracts to protect privacy. Ethers are used as the crypto currencies