scholarly journals A systematic review of security and privacy issues in the internet of medical things; the role of machine learning approaches

2021 ◽  
Vol 7 ◽  
pp. e414
Author(s):  
Shilan S. Hameed ◽  
Wan Haslina Hassan ◽  
Liza Abdul Latiff ◽  
Fahad Ghabban
Keyword(s):  
Machine Learning ◽  
Attack Detection ◽  
Security Requirements ◽  
Security And Privacy ◽  
The Internet ◽  
Learning Approaches ◽  
Systems Quality ◽  
Internet Of Medical Things ◽  
Privacy Issues

Background The Internet of Medical Things (IoMTs) is gradually replacing the traditional healthcare system. However, little attention has been paid to their security requirements in the development of the IoMT devices and systems. One of the main reasons can be the difficulty of tuning conventional security solutions to the IoMT system. Machine Learning (ML) has been successfully employed in the attack detection and mitigation process. Advanced ML technique can also be a promising approach to address the existing and anticipated IoMT security and privacy issues. However, because of the existing challenges of IoMT system, it is imperative to know how these techniques can be effectively utilized to meet the security and privacy requirements without affecting the IoMT systems quality, services, and device’s lifespan. Methodology This article is devoted to perform a Systematic Literature Review (SLR) on the security and privacy issues of IoMT and their solutions by ML techniques. The recent research papers disseminated between 2010 and 2020 are selected from multiple databases and a standardized SLR method is conducted. A total of 153 papers were reviewed and a critical analysis was conducted on the selected papers. Furthermore, this review study attempts to highlight the limitation of the current methods and aims to find possible solutions to them. Thus, a detailed analysis was carried out on the selected papers through focusing on their methods, advantages, limitations, the utilized tools, and data. Results It was observed that ML techniques have been significantly deployed for device and network layer security. Most of the current studies improved traditional metrics while ignored performance complexity metrics in their evaluations. Their studies environments and utilized data barely represent IoMT system. Therefore, conventional ML techniques may fail if metrics such as resource complexity and power usage are not considered.

A Survey of Authentication Schemes in the Internet of Things

2019 ◽  
Vol 6 (1) ◽  
pp. 15-30 ◽  
Author(s):  
Yasmine Labiod ◽  
Abdelaziz Amara Korba ◽  
Nacira Ghoualmi-Zine
Keyword(s):  
Internet Of Things ◽  
Security Requirements ◽  
Security And Privacy ◽  
The Internet ◽  
Privacy And Security ◽  
Depth Study ◽  
Authentication Schemes ◽  
Iot Devices ◽  
Privacy Issues ◽  
The Internet Of Things

In the recent years, the Internet of Things (IoT) has been widely deployed in different daily life aspects such as home automation, electronic health, the electric grid, etc. Nevertheless, the IoT paradigm raises major security and privacy issues. To secure the IoT devices, many research works have been conducted to counter those issues and discover a better way to remove those risks, or at least reduce their effects on the user's privacy and security requirements. This article mainly focuses on a critical review of the recent authentication techniques for IoT devices. First, this research presents a taxonomy of the current cryptography-based authentication schemes for IoT. In addition, this is followed by a discussion of the limitations, advantages, objectives, and attacks supported of current cryptography-based authentication schemes. Finally, the authors make in-depth study on the most relevant authentication schemes for IoT in the context of users, devices, and architecture that are needed to secure IoT environments and that are needed for improving IoT security and items to be addressed in the future.

scholarly journals Review on Data Securing Techniques for Internet of Medical Things

2021 ◽  
Vol 3 (3) ◽  
pp. 177-191
Author(s):  
R. Kanthavel
Keyword(s):  
Machine Learning ◽  
Health Care ◽  
Internet Of Things ◽  
Healthcare System ◽  
System Performance ◽  
Learning Approaches ◽  
Wide Range ◽  
Security Problem ◽  
Internet Of Medical Things ◽  
Privacy Issues

In recent days Internet of Things (IOT) has grown up dramatically. It has wide range of applications. One of its applications is Health care system. IOT helps in managing and optimizing of healthcare system. Though it helps in all ways it also brings security problem in account. There is lot of privacy issues aroused due to IOT. In some cases it leads to risk the patient’s life. To overcome this issue we need an architecture named Internet of Medical Things (IOMT). In this paper we have discussed the problems faced by healthcare system and the authentication approaches used by Internet of Medical Things. Machine learning approaches are used to improvise the system performance.

A Survey of Authentication Schemes in the Internet of Things

2021 ◽  
pp. 1715-1732
Author(s):  
Yasmine Labiod ◽  
Abdelaziz Amara Korba ◽  
Nacira Ghoualmi-Zine
Keyword(s):  
Internet Of Things ◽  
Security Requirements ◽  
Security And Privacy ◽  
The Internet ◽  
Privacy And Security ◽  
Depth Study ◽  
Authentication Schemes ◽  
Iot Devices ◽  
Privacy Issues ◽  
The Internet Of Things

In the recent years, the Internet of Things (IoT) has been widely deployed in different daily life aspects such as home automation, electronic health, the electric grid, etc. Nevertheless, the IoT paradigm raises major security and privacy issues. To secure the IoT devices, many research works have been conducted to counter those issues and discover a better way to remove those risks, or at least reduce their effects on the user's privacy and security requirements. This article mainly focuses on a critical review of the recent authentication techniques for IoT devices. First, this research presents a taxonomy of the current cryptography-based authentication schemes for IoT. In addition, this is followed by a discussion of the limitations, advantages, objectives, and attacks supported of current cryptography-based authentication schemes. Finally, the authors make in-depth study on the most relevant authentication schemes for IoT in the context of users, devices, and architecture that are needed to secure IoT environments and that are needed for improving IoT security and items to be addressed in the future.

scholarly journals Detection of Username Enumeration Attack on SSH Protocol: Machine Learning Approach

Symmetry ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 2192
Author(s):  
Abel Z. Agghey ◽  
Lunodzo J. Mwinuka ◽  
Sanket M. Pandhare ◽  
Mussa A. Dida ◽  
Jema D. Ndibwile
Keyword(s):  
Machine Learning ◽  
Nearest Neighbor ◽  
Attack Detection ◽  
The Internet ◽  
Learning Approaches ◽  
K Nearest Neighbor ◽  
Machine Learning Approach ◽  
Brute Force Attack ◽  
Malicious Behaviors ◽  
Closed Environment

Over the last two decades (2000–2020), the Internet has rapidly evolved, resulting in symmetrical and asymmetrical Internet consumption patterns and billions of users worldwide. With the immense rise of the Internet, attacks and malicious behaviors pose a huge threat to our computing environment. Brute-force attack is among the most prominent and commonly used attacks, achieved out using password-attack tools, a wordlist dictionary, and a usernames list—obtained through a so-called an enumeration attack. In this paper, we investigate username enumeration attack detection on SSH protocol by using machine-learning classifiers. We apply four asymmetrical classifiers on our generated dataset collected from a closed-environment network to build machine-learning-based models for attack detection. The use of several machine-learners offers a wider investigation spectrum of the classifiers’ ability in attack detection. Additionally, we investigate how beneficial it is to include or exclude network ports information as features-set in the process of learning. We evaluated and compared the performances of machine-learning models for both cases. The models used are k-nearest neighbor (K-NN), naïve Bayes (NB), random forest (RF) and decision tree (DT) with and without ports information. Our results show that machine-learning approaches to detect SSH username enumeration attacks were quite successful, with KNN having an accuracy of 99.93%, NB 95.70%, RF 99.92%, and DT 99.88%. Furthermore, the results improve when using ports information.

Security and Privacy Issues in the Internet of Things – A Survey

2021 ◽  
Author(s):  
Martin Victor K ◽  
J. Immanuel Johnraja ◽  
Getzi Jeba Leelipushpam ◽  
J. Jebaveerasingh Jebadurai ◽  
I. Bildass Santhosam
Keyword(s):  
Internet Of Things ◽  
Security And Privacy ◽  
The Internet ◽  
Privacy Issues ◽  
The Internet Of Things

CYBERSECURITY ARCHITECTURE FOR THE INTERNET OF MEDICAL THINGS AND CONNECTED DEVICES USING BLOCKCHAIN

2021 ◽  
pp. 2150013
Author(s):  
Muhammad Elsayeh ◽  
Kadry Ali Ezzat ◽  
Hany El-Nashar ◽  
Lamia Nabil Omran
Keyword(s):  
Healthcare Providers ◽  
Vital Signs ◽  
Third Party ◽  
Security And Privacy ◽  
The Internet ◽  
Security Architecture ◽  
Healthcare Organizations ◽  
Blockchain Technology ◽  
Huge Data ◽  
Internet Of Medical Things

The internet of medical things (IoMT) has a great role in improving the health around the world. IoMT is having a great impact in our life in which the clinical data of the patient is observed and checked and then can be transferred to the third party for using in the future such as the cloud. IoMT is a huge data system with a continuous developing rate, which implies that we should keep a lot of data secure. We propose a combined security architecture that fuses the standard architecture and new blockchain technology. Blockchain is a temper digital ledger which gives peer-to-peer communication and provides communication between non-trust individuals. Using standard in-depth strategy and blockchain, we are able to develop a method to collect vital signs data from IoMT and connected devices and use blockchain to store and retrieve the collected data in a secure and decentralized fashion within a closed system, suitable for healthcare providers such as private clinics, hospitals, and healthcare organizations were sharing data with each other is required. Right now initially examine the innovation behind Blockchain then propose IoMT-based security architecture utilizing Blockchain to guarantee the security of information transmission between associated nodes. Experimental analysis shows that the proposed scheme presents a non-significant overhead; yet it brings major advantages to meet the standard security and privacy requirements in IoMT.

Trade or Trick?

2021 ◽  
Vol 5 (3) ◽  
pp. 1-26
Author(s):  
Pengcheng Xia ◽  
Haoyu Wang ◽  
Bingyu Gao ◽  
Weihang Su ◽  
Zhou Yu ◽  
...  
Keyword(s):  
Machine Learning ◽  
Security And Privacy ◽  
Smart Contracts ◽  
Early Stages ◽  
Asset Trading ◽  
Digital Asset ◽  
Guilt By Association ◽  
Privacy Issues ◽  
Digital Assets

The prosperity of the cryptocurrency ecosystem drives the need for digital asset trading platforms. Beyond centralized exchanges (CEXs), decentralized exchanges (DEXs) are introduced to allow users to trade cryptocurrency without transferring the custody of their digital assets to the middlemen, thus eliminating the security and privacy issues of traditional CEX. Uniswap, as the most prominent cryptocurrency DEX, is continuing to attract scammers, with fraudulent cryptocurrencies flooding in the ecosystem. In this paper, we take the first step to detect and characterize scam tokens on Uniswap. We first collect all the transactions related to Uniswap V2 exchange and investigate the landscape of cryptocurrency trading on Uniswap from different perspectives. Then, we propose an accurate approach for flagging scam tokens on Uniswap based on a guilt-by-association heuristic and a machine-learning powered technique. We have identified over 10K scam tokens listed on Uniswap, which suggests that roughly 50% of the tokens listed on Uniswap are scam tokens. All the scam tokens and liquidity pools are created specialized for the "rug pull" scams, and some scam tokens have embedded tricks and backdoors in the smart contracts. We further observe that thousands of collusion addresses help carry out the scams in league with the scam token/pool creators. The scammers have gained a profit of at least $16 million from 39,762 potential victims. Our observations in this paper suggest the urgency to identify and stop scams in the decentralized finance ecosystem, and our approach can act as a whistleblower that identifies scam tokens at their early stages.

The adaptability of assistive mobility devices and the role of the internet of medical things: A literature review (Preprint)

2021 ◽  
Author(s):  
Daniel OLADELE ◽  
Elisha Didam Markus ◽  
Adnan M. Abu-Mahfouz
Keyword(s):  
Sensor Fusion ◽  
Autonomous Navigation ◽  
The Internet ◽  
Training Time ◽  
Mobility Devices ◽  
The Status ◽  
Internet Of Medical Things ◽  
And Performance ◽  
Human Device

UNSTRUCTURED With the projected upsurge in the percentage of persons with some form of disability, there is a significant increase in the need for assistive mobility devices. However, these mobility aids are hardly effective without their ability to adapt to the user’s needs. This is achieved by improving the confidence of the information used or interaction between the user and his device also referred to as adaptation. In the recent past, there has been little effort to provide literature reviews on the adaptability of assistive mobility devices (AMDs). This paper systematically reviews the recent assistive mobility technologies, over the past decade, according to their adaptation and the role that the Internet of Medical Things (IoMT) has played in the adaptability of these technologies. The information gathered in the study provides awareness of the status of adaptive mobility technology and serves as a source and reference of information to healthcare professionals, and researchers. The paper starts by highlighting recent technologies according to the user system interface (human/device interface), then presents some recent technologies in perception and sensor fusion (autonomous navigation) for adaptability, and finally, IoMT frameworks for AMDs. Some notable limitations are also discussed. The findings of the review reveal that an improvement in the adaptation of assistive mobility systems would require a reduction in the training time and avoidance of cognitive overload. Furthermore, sensor fusion and classification accuracy are critical to achieving real-world testing requirements. Finally, the trade-off between cost and performance needs to be considered in the commercialization of these devices.

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