Enforcing patient privacy in healthcare WSNs through key distribution algorithms

Mišić, Jelena

doi:10.1002/sec.40

Cited by 15 publications

(12 citation statements)

References 21 publications

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“…• Public-key based solutions assume that a public-key cryptosystem, such as DiffieHellman key exchange protocol [8] or RSA [27], is used to establish a secret key for encryption on the basis of the public keys. Typical examples of public-key based solutions include [11], [13], [17], [19], [21], [22]. These solutions facilitate key distribution and update.…”

Section: Fig 1 Alarm-net Architecturementioning

confidence: 99%

Privacy Protection for Wireless Medical Sensor Data

Bouguettaya

Georgakopoulos

et al. 2016

IEEE Trans. Dependable and Secure Comput.

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In recent years, wireless sensor networks have been widely used in healthcare applications, such as hospital and home patient monitoring. Wireless medical sensor networks are more vulnerable to eavesdropping, modification, impersonation and replaying attacks than the wired networks. A lot of work has been done to secure wireless medical sensor networks. The existing solutions can protect the patient data during transmission, but cannot stop the inside attack where the administrator of the patient database reveals the sensitive patient data. In this paper, we propose a practical approach to prevent the inside attack by using multiple data servers to store patient data. The main contribution of this paper is securely distributing the patient data in multiple data servers and employing the Paillier and ElGamal cryptosystems to perform statistic analysis on the patient data without compromising the patients' privacy.

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Section: Fig 1 Alarm-net Architecturementioning

confidence: 99%

Privacy Protection for Wireless Medical Sensor Data

Bouguettaya

Georgakopoulos

et al. 2016

IEEE Trans. Dependable and Secure Comput.

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“…In situations where patients' data may be collected through automated systems, and in real time, there is a high possibility of constraints (Mišić & Mišić 2008). Thus, software applications and other devices that are used to store, access and manage health data should be integrated with mechanisms such as privacy protection, access control and secure transmission modules (Hsu, Lee & Su 2013).…”

Section: What Are the Factors That Influence Social Media Big Data?mentioning

confidence: 99%

“…Technological devices can be used to collect, access and manage big data, remotely and from different locations (Al Ameen et al 2012). However, the host databases should be situated in a secured location to prevent theft and destruction (Mišić & Mišić 2008). • Transformation -Rapidly increasing patients' heterogeneous big data helps to provide a valuable resource for use in the course of improving healthcare service delivery, which include medical decision-making (Christodoulakis et al 2016).…”

Section: What Are the Factors That Influence Big Data In Healthcare?mentioning

confidence: 99%

“…This could be attributed to the fact that research about healthcare information systems (HISs) pays little attention to privacy protection (Hsu et al 2013). A common understanding is that privacy of patients' big data is a foremost security concern in providing healthcare services and must be enforced through the use of strong technology, such as cryptography, irrespective of the source of data (Mišić & Mišić 2008). In search of solutions, Hsu et al (2013) proposed a framework that could be used to protect the electronic healthcare records (EHRs) of patients.…”

Section: Healthcare and Privacymentioning

confidence: 99%

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Integration of social media with healthcare big data for improved service delivery

Mgudlwa¹,

Iyamu²

2018

S. Afr. j. inf. manag.

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Background: In the last decade, social media users across the world have crossed 1 billion, making it one of the fastest growing sources of big data. Also, people needing healthcare continue to increase in every society. Through accessibility, communication and interaction between health practitioners and patients, this type of ever-growing, social media subscriber–based platform can be of significant use in improving healthcare delivery to society. However, users encounter serious challenges in their attempts to make use of social media and big data for health-related services. The challenges are primarily caused by factors such as integration, complexity, security and privacy. The challenges are mainly owing to the sensitive nature of the healthcare environment, as a result of personalisation and privacy of information. Objectives: The objectives of the study were to examine and gain a better understanding of the complexities that are associated with the use of social media and healthcare big data, through influencing factors, and to develop a framework that can be used to improve health-related services to the patients. Methods: The interpretivist approach was employed, within which qualitative data were collected. This included documents and existing literature in the areas of social media and healthcare big data. To have a good spread of both previous and current state of events within the phenomena being studied, literature published between 2006 and 2016 were gathered. The data were interpretively analysed. Results: Based on the analysis of the data, factors of influence were found, which were used to develop a model. The model illustrates how the factors of influence can enable and at the same time constrain the use of social media for healthcare services. The factors were interpreted from which a framework was developed. The framework is intended to guide integration of social media with healthcare big data through which service delivery to patients can be improved. Conclusion: This study can be used to guide integration of social media with healthcare big data by health facilities in the communities. The study contributes to healthcare workers’ awareness on how social media can possibly be used to improve the services that they provide to the needy. Also, the study will benefit information systems and technologies and academic domains, particularly from the health services’ perspective.

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“…In contrast to the physiological parameter based schemes, the cryptography based schemes are more mature and flexible which can be applied in both intrabody communication and external-body communication (authentication between service provider and controller). The cryptography based schemes can be divided into three types in general: symmetric cryptography based schemes [39][40][41][42][43][44], traditional public key infrastructure (PKI) based schemes [45][46][47][48][49][50], and some special cryptographic methods based schemes such as identity cryptography [51] and certificateless cryptography [52]. Compared with the latter two methods, symmetric cryptography based schemes need relatively low computational cost but support limited security functions and create key distribution problem; PKI based scheme needs relatively higher computational cost compared with symmetric cryptography based schemes; the special cryptographic methods support richer security service but need the highest computational cost.…”

Section: Related Workmentioning

confidence: 99%

LEPA: A Lightweight and Efficient Public Auditing Scheme for Cloud-Assisted Wireless Body Sensor Networks

Cui

Zhang

et al. 2017

Security and Communication Networks

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From smart watch to remote healthcare system, wireless body sensor networks (WBSNs) play an important role in modern healthcare system. However, the weak capacity of devices has limited WBSNs development. Considering the huge processing and storage capacity of the cloud, it can be merged with WBSNs to make up for the deficiencies of weak capacity. Based on this consideration, the concept of cloud-assisted WBSNs has been proposed recently. In contrast to generic data, the data in cloud-assisted WBSNs will be used for providing medical diagnosis, so the integrity of data is very important because any modification will result in severe consequences such as misdiagnosis. The public auditing scheme could provide an efficient solution to check the data integrity remotely without downloading them. However, the traditional public auditing scheme for cloud cannot be used directly due to the high data density and weak processing capacity in WBSNs. So, in this paper, we proposed a lightweight and efficient public auditing scheme, LEPA, for cloud-assisted WBSNs. Compared with similar schemes, the WBSNs’ client only needs to do one symmetrical encryption with low computational cost in LEPA. Security proof shows that LEPA can resist two types of adversaries in random oracle model. The efficiency evaluation also shows that LEPA outperforms previous proposals.

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Enforcing patient privacy in healthcare WSNs through key distribution algorithms

Cited by 15 publications

References 21 publications

Privacy Protection for Wireless Medical Sensor Data

Privacy Protection for Wireless Medical Sensor Data

Integration of social media with healthcare big data for improved service delivery

LEPA: A Lightweight and Efficient Public Auditing Scheme for Cloud-Assisted Wireless Body Sensor Networks

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