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Journal ArticleDOI

Review on Data Securing Techniques for Internet of Medical Things

11 Sep 2021-Journal of Social and Clinical Psychology (Inventive Research Organization)-Vol. 3, Iss: 3, pp 177-191
About: This article is published in Journal of Social and Clinical Psychology.The article was published on 2021-09-11 and is currently open access. It has received None citations till now. The article focuses on the topics: The Internet.

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Journal ArticleDOI
TL;DR: The security and privacy challenges, requirements, threats, and future research directions in the domain of IoMT are reviewed providing a general overview of the state-of-the-art approaches.
Abstract: With the increasing demands on quality healthcare and the raising cost of care, pervasive healthcare is considered as a technological solutions to address the global health issues. In particular, the recent advances in Internet of Things have led to the development of Internet of Medical Things (IoMT). Although such low cost and pervasive sensing devices could potentially transform the current reactive care to preventative care, the security and privacy issues of such sensing system are often overlooked. As the medical devices capture and process very sensitive personal health data, the devices and their associated communications have to be very secured to protect the user’s privacy. However, the miniaturized IoMT devices have very limited computation power and fairly limited security schemes can be implemented in such devices. In addition, with the widespread use of IoMT devices, managing and ensuring the security of IoMT systems are very challenging and which are the major issues hindering the adoption of IoMT for clinical applications. In this paper, the security and privacy challenges, requirements, threats, and future research directions in the domain of IoMT are reviewed providing a general overview of the state-of-the-art approaches.

141 citations

Journal ArticleDOI
TL;DR: A survey on what can be called post-quantum IoT systems (IoT systems protected from the currently known quantum computing attacks): the main post-Quantum cryptosystems and initiatives are reviewed, the most relevant IoT architectures and challenges are analyzed, and the expected future trends are indicated.
Abstract: Although quantum computing is still in its nascent age, its evolution threatens the most popular public-key encryption systems. Such systems are essential for today’s Internet security due to their ability for solving the key distribution problem and for providing high security in insecure communications channels that allow for accessing websites or for exchanging e-mails, financial transactions, digitally signed documents, military communications or medical data. Cryptosystems like Rivest–Shamir–Adleman (RSA), elliptic curve cryptography (ECC) or Diffie–Hellman have spread worldwide and are part of diverse key Internet standards like Transport Layer Security (TLS), which are used both by traditional computers and Internet of Things (IoT) devices. It is especially difficult to provide high security to IoT devices, mainly because many of them rely on batteries and are resource constrained in terms of computational power and memory, which implies that specific energy-efficient and lightweight algorithms need to be designed and implemented for them. These restrictions become relevant challenges when implementing cryptosystems that involve intensive mathematical operations and demand substantial computational resources, which are often required in applications where data privacy has to be preserved for the long term, like IoT applications for defense, mission-critical scenarios or smart healthcare. Quantum computing threatens such a long-term IoT device security and researchers are currently developing solutions to mitigate such a threat. This article provides a survey on what can be called post-quantum IoT systems (IoT systems protected from the currently known quantum computing attacks): the main post-quantum cryptosystems and initiatives are reviewed, the most relevant IoT architectures and challenges are analyzed, and the expected future trends are indicated. Thus, this article is aimed at providing a wide view of post-quantum IoT security and give useful guidelines to the future post-quantum IoT developers.

112 citations

Proceedings ArticleDOI
29 May 2019
TL;DR: This paper presents an overview of the core security and privacy controls that must be deployed in modern IoMT settings in order to safeguard the involved users and stakeholders.
Abstract: Day-by-day modern circular economy (CE) models gain ground and penetrate the traditional business sectors. The Internet of Medical Things (IoMT) is the main enabler for this interplay of CE with healthcare. Novel services, like remote sensing, assisting of elder people, and e-visit, enhance the people's health and convenience, while reducing the per-patient cost for the medical institutions. However, the rise of mobile, wearable, and telemedicine solutions means that security can no longer be examined within the neat, physical walls as it was considered before. The problem for a healthcare system further increases as the Bring Your Own Device (BYOD) reality, affects the way that the health services are accommodated nowadays. Both patients and healthcare staff utilize their personal devices (e.g. smart phones or tablets) in order to access, deliver, and process medical data. As the IoMT is materialized and the underlying devices maintain so valuable data, they become a popular target for ransomware and other attacks. In the CE case, the problem is further emerging as several of these assets can be used over-and-over by many actuators. However, medical users and vendors are less aware of the underlying vulnerabilities and spend less on the IoMT security. Nevertheless, the risk from exploiting vulnerabilities can be drastically reduced when the known and relevant controls are placed. This paper presents an overview of the core security and privacy controls that must be deployed in modern IoMT settings in order to safeguard the involved users and stakeholders. The overall approach can be considered as a best-practices guide towards the safe implementation of IoMT systems, featuring CE.

95 citations

Journal ArticleDOI
TL;DR: In this paper, the authors presented an efficient, lightweight encryption algorithm to develop a secure image encryption technique for the healthcare industry, which employs two permutation techniques to secure medical images.
Abstract: The importance of image security in the field of medical imaging is challenging. Several research works have been conducted to secure medical healthcare images. Encryption, not risking loss of data, is the right solution for image confidentiality. Due to data size limitations, redundancy, and capacity, traditional encryption techniques cannot be applied directly to e-health data, especially when patient data are transferred over the open channels. Therefore, patients may lose the privacy of data contents since images are different from the text because of their two particular factors of loss of data and confidentiality. Researchers have identified such security threats and have proposed several image encryption techniques to mitigate the security problem. However, the study has found that the existing proposed techniques still face application-specific several security problems. Therefore, this paper presents an efficient, lightweight encryption algorithm to develop a secure image encryption technique for the healthcare industry. The proposed lightweight encryption technique employs two permutation techniques to secure medical images. The proposed technique is analyzed, evaluated, and then compared to conventionally encrypted ones in security and execution time. Numerous test images have been used to determine the performance of the proposed algorithm. Several experiments show that the proposed algorithm for image cryptosystems provides better efficiency than conventional techniques.

92 citations

Journal ArticleDOI
16 Mar 2021
TL;DR: The recent adaptive image-based classification techniques and it comparing existing classification methods to predict CAD earlier for a higher accurate value are provided and the decision-making of classified output provides better accurate results in the proposed algorithm.
Abstract: Coronary Artery Disease (CAD) prediction is a very hard and challenging task in the medical field. The early prediction in the medical field especially the cardiovascular sector is one of the virtuosi. The prior studies about the construction of the early prediction model developed an understanding of the recent techniques to find the variation in medical imaging. The prevention of cardiovascular can be fulfilled through a diet chart prepared by the concerned physician after early prediction. Our research paper consists of the prediction of CAD by the proposed algorithm by constructing of pooled area curve (PUC) in the machine learning method. This knowledgebased identification is an important factor for accurate prediction. This significant approach provides a good impact to determine variation in medical images although weak pixels surrounding it. This pooled area construction in our machine learning algorithm is bagging shrinking veins and tissues with the help of clogging and plaque of blood vessels. Besides, the noisy type database is used in this article for better clarity about identifying the classifier. This research article provides the recent adaptive image-based classification techniques and it comparing existing classification methods to predict CAD earlier for a higher accurate value. This proposed method is taking as Journal of Artificial Intelligence and Capsule Networks (2021) Vol.03/ No.01 Pages: 17-33 http://irojournals.com/aicn/ DOI: https://doi.org/10.36548/jaicn.2021.1.002 18 ISSN: 2582-2012 (online) Submitted: 5.01.2021 Revised: 10.02.2021 Accepted: 2.03.2021 Published: 16.03.2021 evidence to diagnosis any heart disease earlier. The decision-making of classified output provides better accurate results in our proposed algorithm.

84 citations