Security Solutions for Big Data Analytics in Healthcare

Impact of Big Data Analysis on Health

“…The technology presents capabilities to enhance managing chronic diseases and monitoring daily fitness goals [72]. Within smart healthcare systems, IoT infrastructures can help to bridge the gap between patient and their doctors [73]. The infrastructures can collect and transmit crucial medical information from patients [74].…”

Big Data Meet Cyber-Physical Systems: A Panoramic Survey

“…In healthcare, for instance, the security issues of information extraction from massive amount of data and accurate analytics are of high importance. Sensitive data recorded in databases need to be protected via monitoring which applications and users get accesses to the data [204]. In order to guarantee a strong secure big data analytics, the following tasks can be performed [205]:…”

“…The work [270] adopted an energy-efficient architecture for Industrial Internet of Things (IIoT) with a sense entities domain, RESTful service hosted networks, a cloud server, and user applications to balance the traffic load and support a longer lifetime of the whole system. The paper [271] mainly studied two important issues: 1) performing cyber-physical systems (CPS) communications over cellular [196] Secure data placement on cloud i) ensures users' data protection on clouds; ii) does not require complex signatures and keys; iii) provides data privacy at users' side i) data might need to be encrypted/decrypted before transferring to clouds; ii) can have a long data retrieval time; iii) not suitable for making real-time network decisions; iv) not very robust as attackers can guess data's locations; v) service providers can have access to users' data; vi) complicated data management and access [195] [197] [199] [202] [223] [215] Cryptographic Solutions i) ensures information protection, data privacy and integrity; ii) works in conjunction with other security solutions for more robust security i) costly in terms of computational overhead; ii) can have a large power consumption; iii) increases latency; iv) inefficient for many CPS devices with limited computational capabilities; v) works only for fixed malicious behaviors Data Access Permission Restrictions [50] [204] [224] [225] Advanced security controls i) selective access control; ii) can be used in conjunction with cryptography for a more robust security; iii) good for real-time data streams; iv) provides additional layer of protection i) difficult to access for legitimate users; ii) needs to be combined with other solutions; iii) not sufficient by itself to protect users' data; iv) might increase latency from accessing the data Visualization Detection of Anomalies [130] Anomaly Detection i) does not require costly solutions such as signatures and keys; ii) works for a variety of attacks with varying malicious behaviors; iii) can detect abnormal traffic patterns with no associated signature i) requires a large dataset for training; ii) costly in terms of overhead and storage of training data; iii) might require human analysts' intervention to make the detection more textbackslash supervise [179] [231] [130] [209] [211] [232] Visualization Techniques i) ideal for monitoring real-time traffic; ii) provides global overview of network problems i) not accurate if traffic patterns are misclassified; ii) requires complex statistical analysis of traffic; iii) might need to be supervised by humans; iv) might require prior knowledge for a better intrusion detection -Provide relay incentives to extend communication [24], [56], [128], [145], [233]...…”

A privacy‐preserving framework for smart context‐aware healthcare applications

“…The use of latest and emerging technologies, sensors and sharing techniques, and information and communication techniques make it easier to generate and share healthcare data but also introduces challenges with respect to security and privacy. This is because electronic healthcare data is susceptible to unlawful access, compromise integrity, and unauthorized distribution [53,54,55].…”

“…This is because electronic healthcare data is susceptible to unlawful access, compromise integrity, and unauthorized distribution. [53][54][55] Another major challenge with big data applications in the healthcare sector is complex and distributed nature of healthcare data, diverse schema and standards, and rapid growth of new health terminologies and ontologies. The major challenge here is not the lack of data but the lack of information to support decision making, planning, and strategy.…”