Empowering integrity and confidentiality in smart healthcare systems through effective edge cryptographic strategies

Current mechanization has motivated innumerable segments of our day-to-day existence. With the development of Information and Communication Technologies (ICTs), smart medical management is using current age group data or information mechanization such as Internet of Things (IoT), Big Data, Cloud Computing, Blockchain and Artificial Intelligence (AI) to comprehensively transform the traditional medicinal arrangements and make medical treatment more environmentally friendly, appropriate and personalize. According to Blue Stream Consultancy, “Smart Healthcare is defined as technology that brings better diagnostic tools, better patient care, and equipment to improve the quality of life for all.” Smart Healthcare is no longer the simplest manner of adopting new merchandise and technologies for analysis and remedy, but it includes an extra trade of records a number of the events, a greater energetic function of patients during treatment and, in the end a higher management of medical facts. The Internet of Things (IoT) replace the commercial enterprise spectrum and its software varies extensively from agriculture to healthcare, to transportation, and so on. Health centre surrounding can be very worrying, particularly for elder residents and younger one. With continuous growth of global populace, the traditional make an appointment with the patient’s doctor has misplaced its efficiency. Therefore, Smart Healthcare becomes crucial. Smart Healthcare may be applied in any context, from temperature control for toddlers to caring for the aged. The difficulty and costs of implementation depend on the desired precision of the individual accuracy, functionality and complexity of the software involved. Security and privacy issues in smart healthcare is challenging as patient personal information are share among different parties. IoT-based smart healthcare systems involve authentication, data integrity, identification and scalability, as they use heterogeneous devices to collect patient vital information which need to be process in real time.This chapter analyzes the architecture and basic protocols used in smart healthcare systems, then identifies the security and privacy challenges in different layers, along with secure computational challenges that need to be addressed to accelerate the deployment and adoption of Smart Healthcare technologies for ubiquitous healthcare access. This chapter proposes blockchain-based architecture for addressing security and privacy issues existing within IoT to enable smart healthcare systems. The smart contracts are designed to implement the working logic of each user in the smart healthcare system.

Cutting-edge technologies have been widely employed in healthcare delivery, resulting in transformative advances and promising enhanced patient care, operational efficiency, and resource usage. However, the proliferation of networked devices and data-driven systems has created new cybersecurity threats that jeopardize the integrity, confidentiality, and availability of critical healthcare data. This review paper offers a comprehensive evaluation of the current state of cybersecurity in the context of smart healthcare, presenting a structured taxonomy of its existing cyber threats, mechanisms and essential roles. This study explored cybersecurity and smart healthcare systems (SHSs). It identified and discussed the most pressing cyber threats and attacks that SHSs face, including fake base stations, medjacking, and Sybil attacks. This study examined the security measures deployed to combat cyber threats and attacks in SHSs. These measures include cryptographic-based techniques, digital watermarking, digital steganography, and many others. Patient data protection, the prevention of data breaches, and the maintenance of SHS integrity and availability are some of the roles of cybersecurity in ensuring sustainable smart healthcare. The long-term viability of smart healthcare depends on the constant assessment of cyber risks that harm healthcare providers, patients, and professionals. This review aims to inform policymakers, healthcare practitioners, and technology stakeholders about the critical imperatives and best practices for fostering a secure and resilient smart healthcare ecosystem by synthesizing insights from multidisciplinary perspectives, such as cybersecurity, healthcare management, and sustainability research. Understanding the most recent cybersecurity measures is critical for controlling escalating cyber threats and attacks on SHSs and networks and encouraging intelligent healthcare delivery.

A smart healthcare system is a need of the present world. Artificial intelligence, the internet of things, big data, etc. are essential technologies that build a smart and intelligent healthcare system. Deployment of a smart healthcare system not only serves diagnosis and treatment to more patients but also reduces the workload on health workers. Some patients face difficulties using the technology, which needs to be simplified. The most important issue in a smart healthcare system is cyber security. In smart healthcare systems, wearable devices and hospital management store patient information in digital format, which is available in cloud storage, which can be hacked, and it needs strong cyber security. With the development of technologies, smart healthcare systems can provide more intelligent and convenient applications and services. It can provide better service, self-health management, timely and appropriate medical service that can be accessed whenever needed, personalized medical service, improve the doctor-patient relationship, and reduce the cost of services.

Biomedical Microelectromechanical Systems (BioMEMS) serve as a crucial catalyst in enhancing IoT communication security and safeguarding smart healthcare systems. Situated at the nexus of advanced technology and healthcare, BioMEMS are instrumental in pioneering personalized diagnostics, monitoring, and therapeutic applications. Nonetheless, this integration brings forth a complex array of security and privacy challenges intrinsic to IoT communications within smart healthcare ecosystems, demanding comprehensive scrutiny. In this manuscript, we embark on an extensive analysis of the intricate security terrain associated with IoT communications in the realm of BioMEMS, addressing a spectrum of vulnerabilities that spans cyber threats, data manipulation, and interception of communications. The integration of real-world case studies serves to illuminate the direct repercussions of security breaches within smart healthcare systems, highlighting the imperative to safeguard both patient safety and the integrity of medical data. We delve into a suite of security solutions, encompassing rigorous authentication processes, data encryption, designs resistant to attacks, and continuous monitoring mechanisms, all tailored to fortify BioMEMS in the face of ever-evolving threats within smart healthcare environments. Furthermore, the paper underscores the vital role of ethical and regulatory considerations, emphasizing the need to uphold patient autonomy, ensure the confidentiality of data, and maintain equitable access to healthcare in the context of IoT communication security. Looking forward, we explore the impending landscape of BioMEMS security as it intertwines with emerging technologies such as AI-driven diagnostics, quantum computing, and genomic integration, anticipating potential challenges and strategizing for the future. In doing so, this paper highlights the paramount importance of adopting an integrated approach that seamlessly blends technological innovation, ethical foresight, and collaborative ingenuity, thereby steering BioMEMS towards a secure and resilient future within smart healthcare systems, in the ambit of IoT communication security and protection.

Federated learning (FL) has emerged as an efficient machine learning (ML) method with crucial privacy protection features. It is adapted for training models in Internet of Things (IoT)-related domains, including smart healthcare systems (SHSs), where the introduction of IoT devices and technologies can arise various security and privacy concerns. However, as FL cannot solely address all privacy challenges, privacy-enhancing technologies (PETs) and blockchain are often integrated to enhance privacy protection in FL frameworks within SHSs. The critical questions remain regarding how these technologies are integrated with FL and how they contribute to enhancing privacy protection in SHSs. This survey addresses these questions by investigating the recent advancements on the combination of FL with PETs and blockchain for privacy protection in smart healthcare. First, this survey emphasizes the critical integration of PETs into the FL context. Second, to address the challenge of integrating blockchain into FL, it examines three main technical dimensions such as blockchain-enabled model storage, blockchain-enabled aggregation, and blockchain-enabled gradient upload within FL frameworks. This survey further explores how these technologies collectively ensure the integrity and confidentiality of healthcare data, highlighting their significance in building a trustworthy SHS that safeguards sensitive patient information.

Insights into security and privacy issues in smart healthcare systems based on medical images

Smart healthcare, as an examplar domain, is empowered by the remarkable miniaturization of sensors and the proliferation of smart devices, which lead to the production of massive amounts of healthcare data. Smart healthcare in the future is expected as a health service system that uses wearable devices, IoT, and mobile internet to dynamically collect and deliver healthcare data and then intelligently provide healthcare services. However, security is increasingly being challenged due to the highly valuable data transformed in such a healthcare network that might be tampered with by malicious users or disclosed without considering the privacy of patients. These pose new challenges for improving healthcare services’ safety, quality, and efficiency. In this paper, we propose a redactable signature scheme (RSS) with a short signature and fine-grained sharing control for authenticating the integrity and authenticity of healthcare data while preserving the privacy of patients in the smart healthcare system. The security analysis of our construction shows that it achieves unforgeability and unlinkability. Finally, the efficiency comparison with other related solutions indicates that our scheme could solve the security issues for healthcare data sharing in the smart healthcare system with less computational and communication overhead.KeywordsSmart healthcareAuthenticationFine-grainedPrivacy-preservingUnlinkability

The purpose of this paper is to propose a systematic solution to improve human healthcare situation and to amend the current medical and healthcare systems. The paper first evaluates the current smart healthcare technologies and their progress in different regions, then identifies the major limitation of current smart healthcare systems, specifically the current challenges of patient-hospital relationship and how insufficient communication between hospitals and patients jeopardize the patient-hospital relationship. The paper analyzes several impacting factors, including the interactions between smart healthcare system and other smart systems under the framework of smart cities, and how these factors would affect the whole systems systematically. Under such a framework we discuss in this paper how to enhance the patient experience in hospital by smart healthcare technologies and solve the problems of unsatisfying relationship between patients and hospitals. The studies are conducted from the following three aspects: hospitals exchange information, patients learn about hospitals, and hospitals gather data from patients. The research introduces different examples of medical technology and of intersections between healthcare system and other systems. However, due to the difference of medical resources and the development of infrastructures in different countries, smart healthcare system still need amendment.

There is a massive transformation in the traditional healthcare system from the specialist-centric approach to the patient-centric approach by adopting modern and intelligent healthcare solutions to build a smart healthcare system. It permits patients to directly share their medical data with the specialist for remote diagnosis without any human intervention. Furthermore, the remote monitoring of patients utilizing wearable sensors, Internet of Things (IoT) technologies, and artificial intelligence (AI) has made the treatment readily accessible and affordable. However, the advancement also brings several security and privacy concerns that poorly maneuvered the effective performance of the smart healthcare system. An attacker can exploit the IoT infrastructure, perform an adversarial attack on AI models, and proliferate resource starvation attacks in smart healthcare system. To overcome the aforementioned issues, in this survey, we extensively reviewed and created a comprehensive taxonomy of various smart healthcare technologies such as wearable devices, digital healthcare, and body area networks (BANs), along with their security aspects and solutions for the smart healthcare system. Moreover, we propose an AI-based architecture with the 6G network interface to secure the data exchange between patients and medical practitioners. We have examined our proposed architecture with the case study based on the COVID-19 pandemic by adopting unmanned aerial vehicles (UAVs) for data exchange. The performance of the proposed architecture is evaluated using various machine learning (ML) classification algorithms such as random forest (RF), naive Bayes (NB), logistic regression (LR), linear discriminant analysis (LDA), and perceptron. The RF classification algorithm outperforms the conventional algorithms in terms of accuracy, i.e., 98%. Finally, we present open issues and research challenges associated with smart healthcare technologies.

In recent years, Internet of Things (IoT) technology has been adopted in numerous application areas, such as healthcare, agriculture, industrial automation, and many more. The use of IoT and other technologies like cloud computing and machine learning has made the modern healthcare system to be smart, automated, and efficient. However, the continuous proliferation of cyber‐attacks on IoT devices has increased IoT challenges like data security, privacy protection, authentication, and so forth. In smart healthcare systems, due to the lack of authentication protocols, attackers can undermine the availability, confidentiality, and integrity of both smart healthcare devices and data, which can be life‐threatening in some situations. In this article, a privacy‐preserving mutual authentication scheme for IoT‐enabled healthcare systems is proposed to achieve lightweight and effective authentication of network devices. To support the processing capabilities of the IoT devices, this proposed authentication scheme is designed using lightweight cryptographic primitives, namely XOR, concatenation, and hash operation. The proposed scheme can establish a secure session between an authorized device and a gateway, and prevent unauthorized devices from getting access to healthcare systems. The security analysis and performance analysis assess the proposed authentication technique's effectiveness over existing well‐known schemes.

A smart device carries a great amount of sensitive patient data as it offers innovative and enhanced functionalities in the smart healthcare system. Moreover, the components of healthcare systems are interconnected via the Internet, bringing significant changes to the delivery of healthcare services to individuals. However, easy access to healthcare services and applications has given rise to severe risks and vulnerabilities that hamper the performance of a smart healthcare system. Moreover, a large number of heterogeneous devices accumulate data that vary in terms of size and formats, making it challenging to manage the data in the healthcare repository and secure it from attackers who seek to profit from the data. Thus, smart healthcare systems are susceptible to numerous security threats and risks, such as hardware and software-based attacks, system-level attacks, and network attacks that have the potential to place patients’ lives at risk. An analysis of the literature revealed a research gap in that most security surveys on the healthcare ecosystem examined only the security challenges and did not explore the possibility of integrating modern technologies to alleviate security issues in the smart healthcare system. Therefore, in this article, we conduct a comprehensive review of the various most recent security challenges and their countermeasures in the smart healthcare environment. In addition, an artificial intelligence (AI) and blockchain-based secure architecture is proposed as a case study to analyse malware and network attacks on wearable devices. The proposed architecture is evaluated using various performance metrics such as blockchain scalability, accuracy, and dynamic malware analysis. Lastly, we highlight different open issues and research challenges facing smart healthcare systems.

The intelligent use of resources enabled by Internet of Things has raised the expectations of the technical as well as the consumer community. However there are many challenges in designing an IoT healthcare system, like security, authentication and exchanging data. The IoT healthcare system, is transforming everyday physical objects, medical devices that surround us into an embedded smart healthcare system. Public healthcare has been paid an increasing attention given the human population and medical expenses exponential growth. It is well known that an effective monitoring healthcare system can detect abnormalities of health conditions in time and make diagnoses according to sensing (WBSN) data. This paper propose a general architecture of a smart mobile IoT healthcare system for monitoring patients risk using a smart phone and 5G. The design of multi-protocol unit for universal connectivity. Web and mobile applications developed to meet the needs of patients, doctors, laboratories analysis and hospitals services. The system advises and alerts in real time the doctors/medical assistants about the changing of vital parameters of the patients, such as body temperature, pulse and Oxygen in Blood etc… and also about important changes on environmental parameters, in order to take preventive measures, save lives in critical care and emergency situations.

Smart healthcare systems have received increasing attention in recent years; however, a bibliometric analysis of the research on smart healthcare systems for the elderly is lacking. This study aimed to identify scientific results and emerging themes related to smart healthcare systems for older adults. Articles and reviews related to smart healthcare systems for older adults, published between 2013 and 2022, were obtained from the Web of Science Core Collection database using a keyword search. Data collected included the number of publications per year, country/region, institution, author, journal, reference, citation frequency, and keywords. Bibliometric analysis and visualization were performed using the scientometric software VOSviewer and CiteSpace, as well as the bibliometric online analysis platform. In total, 486 articles were retrieved. The number of papers in the field of smart healthcare systems research for older adults has increased every year since 2013. China and the US led in both the number of papers published and total citations. King Saud University was the most prolific institution, while Deen published the highest number of articles and had the highest number of citations. Papers related to smart healthcare systems for the elderly were mainly published in Sensors, IEEE Access, and Applied Sciences-Basel journals. The keyword co-occurrence analysis showed that keywords related to ‘smart home’ appeared most frequently. The top ten common keywords were system, health, smart home, smart homes, Internet of Things, care, older adults, technology, healthcare, and people. The most recent keyword to gather attention was ‘artificial intelligence’. The research on smart healthcare systems for the elderly continues to increase steadily. China and the US maintain a leading position in the world, and institutions such as King Saud University have contributed significantly to the field of smart healthcare for older people. The smart home is the current research hotspot in the field of smart healthcare for older people, and artificial intelligence is likely to be the focus of research in the coming years. There is a need for greater collaboration between countries and institutions to help older people benefit from smart healthcare.

At the present time, the healthcare system is facing great challenges, such as ever growing healthcare cost, limited healthcare resources, inconsistent healthcare quality and population aging, while the transformation into the smart healthcare system, enabled by new technologies and algorithms, further aggravates these problems and introduces new challenges, such as privacy, safety and security issues. Furthermore, the lifestyle supported by environmental degradation and soaring resource consumption jeopardizes people's health and wellbeing. In this paper, we evaluate, from the UV perspective, the challenges of the healthcare system and the current status of the smart healthcare system based on the framework of closed feedback control loop: data acquisition, communication, decision making and action. We propose that an effective smart healthcare system should take into consideration of the interaction between the smart healthcare system and other seven smart city subsystems: smart home, intelligent transportation, urban planning and crowd management, smart energy management, smart city infrastructure, smart response system for city emergency, smart environmental protection and smart humanity, and also study how the smart healthcare system would be affected by four major impacting factors of smart cities: information flow, material cycle, lifestyle and community. This systematic study will help us explore in depth the complicated dynamic relationship between multiple impacting factors and propose a UV-oriented, integrated, re-silient, inclusive and sustainable development framework design to address current imminent challenges and to improve human health through patient-oriented monitoring, life-long healthcare data management, personalized lifestyle guidance and suggestions, preventive healthcare, and timely treatment

The demand for real-time, affordable, and efficient smart healthcare services is increasing exponentially due to the technological revolution and burst of population. To meet the increasing demands on this critical infrastructure, there is a need for intelligent methods to cope with the existing related challenges. In this regard, edge computing technology can reduce latency and energy consumption by moving processes closer to the data sources in comparison to the traditional centralized cloud and IoT-based healthcare systems. In addition, by bringing automated insights into the smart healthcare systems, artificial intelligence (AI) provides the possibility of detecting and predicting high-risk diseases in advance, decreasing medical costs for patients, and offering efficient treatments. The objective of this article is to highlight the benefits of the adoption of the edge intelligent technology, along with the use of AI in smart healthcare systems. Moreover, a novel smart healthcare model is proposed to boost the utilization of AI and edge technology in smart healthcare systems. Additionally, we discuss potential challenges and future research directions arising when integrating these different technologies.