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The involvement of the Internet of things (IoT) in the development of technology makes systems automated and peoples' lives easier. The IoT is taking part in many applications, from smart homes to smart industries, in order to make a city smart. One of the major applications of the IoT is the Internet of medical things (IoMT) which deals with patients' sensitive information. This confidential information needs to be properly transferred and securely authenticated. For successful data protection and preserving privacy, this paper proposes multidevice authentication for the in-hospital segment using a physical unclonable function (PUF) and machine learning (ML). The proposed method authenticates multiple devices using a single message. Most of the protocols require PUF keys to be stored at the server, which is not required in the proposed framework. Moreover, authentication, as well as data, is sent to the server in the same message, which results in faster processing. Furthermore, a single ML model authenticates a group of devices at the same time. The proposed method shows 99.54% accuracy in identifying the group of devices. Moreover, the proposed method takes 2.6 ms and 104 bytes to complete the authentication of a device and takes less time with the increment of devices in the group. The proposed algorithm is analyzed using a formal analysis to show its resistance against various vulnerabilities. [ABSTRACT FROM AUTHOR]

The recent advancement of the Internet of Things (IoT) in the fields of smart vehicles and integration empowers all cars to join to the internet and transfer sensitive traffic information. To enhance the security for the Internet of Vehicles (IoV) and maintain privacy, this paper proposes an ultralight authentication scheme. Physical unclonable function (PUF), supervised machine learning (SML), and XOR functions are used to authenticate both server and device in a two message flow. The proposed framework can authenticate devices with a low computation time (3 ms) compared to other proposed frameworks while protecting against existing potential threats. Furthermore, the proposed framework needs low overhead (21 bytes) that avoids adding to the IoV network's workload. Moreover, SML makes weak PUF responses as random numbers to provide the functionality of a strong PUF for the framework. In addition, both formal (Burrows, Abadi, Needham (BAN) logic) and informal analysis are presented to show the resistance against known attacks. [ABSTRACT FROM AUTHOR]

The overwhelming acceptance and growing need for Internet of Things (IoT) products in each aspect of everyday living is creating a promising prospect for the involvement of humans, data, and procedures. The vast areas create opportunities from home to industry to make an automated lifecycle. Human life is involved in enormous applications such as intelligent transportation, intelligent healthcare, smart grid, smart city, etc. A thriving surface is created that can affect society, the economy, the environment, politics, and health through diverse security threats. Generally, IoT devices are susceptible to security breaches, and the development of industrial systems could pose devastating security vulnerabilities. To build a reliable security shield, the challenges encountered must be embraced. Therefore, this survey paper is primarily aimed to assist researchers by classifying attacks/vulnerabilities based on objects. The method of attacks and relevant countermeasures are provided for each kind of attack in this work. Case studies of the most important applications of the IoT are highlighted concerning security solutions. The survey of security solutions is not limited to traditional secret key-based cryptographic solutions, moreover physical unclonable functions (PUF)-based solutions and blockchain are illustrated. The pros and cons of each security solution are also discussed here. Furthermore, challenges and recommendations are presented in this work. [ABSTRACT FROM AUTHOR]

With the widespread and increasing use of Internet-of-Things (IoT) devices in all aspects of daily life, a hopeful future for people, data, and processes is emerging. Extensive spans allow for an integrated life cycle to be created from home to enterprise. The Internet of Medical Things (IoMT) forms a flourishing surface that incorporates the sensitive information of human life being sent to doctors or hospitals. These open an enormous space for hackers to utilize flaws of the IoMT network to make a profit. This creates a demand for standardizing regulations and a secure system. Though many authorities are making standards, there are some lacking in the system which makes the product vulnerable. Although many established mechanisms are present for the IoT network, there are a number of obstacles preventing its general implementation in the IoMT network. One of the adoption challenges is the IoMT devices itself, because many IoMT networks consist of battery-powered devices with constrained processing capability. A general overview of the different security integrations with IoT applications has been presented in several papers. Therefore, this paper aims to provide an overview of the IoMT ecosystem, regulations, challenges of standards, security mechanisms using cryptographic solutions, physical unclonable functions (PUF)-based solutions, blockchain, and named data networking (NDN) as well, with pros and cons. [ABSTRACT FROM AUTHOR]