The Internet of Medical Things (IoMT) has revolutionized the healthcare industry by enabling physiological data collection using sensors, which are transmitted to remote servers for continuous analysis by physicians and healthcare professionals. This technology offers numerous benefits, including early disease detection and automatic medication for patients with chronic illnesses. However, IoMT technology also presents significant security risks, such as violating patient privacy or exposing sensitive data to interception attacks due to wireless communication, which could be fatal for the patient. Additionally, traditional security measures, such as cryptography, are challenging to implement in medical equipment due to the heterogeneous communication and their limited computation, storage, and energy capacity. These protection methods are also ineffective against new and zero-day attacks. It is essential to adopt robust security measures to ensure data integrity, confidentiality, and availability during data collection, transmission, storage, and processing. In this context, using Intrusion Detection Systems (IDS) based on Machine Learning (ML) can bring a complementary security solution adapted to the unique characteristics of IoMT systems. Therefore, this paper investigates how IDS based on ML can address security and privacy issues in IoMT systems. First, the generic three-layer architecture of IoMT is provided, and the security requirements of IoMT systems are outlined. Then, the various threats that can affect IoMT security are identified, and the advantages, disadvantages, methods, and datasets used in each solution based on ML at the three layers that make up IoMT are presented. Finally, the paper discusses the challenges and limitations of applying IDS based on ML at each layer of IoMT, which can serve as a future research direction.
Western University（韦仕敦大学）；S2E Technologies（S2E科技公司）
Modern vehicles, including autonomous vehicles and connected vehicles, have adopted an increasing variety of functionalities through connections and communications with other vehicles, smart devices, and infrastructures. However, the growing connectivity of the Internet of Vehicles (IoV) also increases the vulnerabilities to network attacks. To protect IoV systems against cyber threats, Intrusion Detection Systems (IDSs) that can identify malicious cyber-attacks have been developed using Machine Learning (ML) approaches. To accurately detect various types of attacks in IoV networks, we propose…
Howard University（霍华德大学）；African Institute for Mathematical Sciences（非洲数学科学研究所）
With the growing rates of cyber-attacks and cyber espionage, the need for better and more powerful intrusion detection systems (IDS) is even more warranted nowadays. The basic task of an IDS is to act as the first line of defense, in detecting attacks on the internet. As intrusion tactics from intruders become more sophisticated and difficult to detect, researchers have started to apply novel Machine Learning (ML) techniques to effectively detect intruders and hence preserve internet users' information and overall trust in the entire internet network security. Over the last decade, there has b…
Machine Learning-Assisted Intrusion Detection for Enhancing Internet of Things Security
University of New Mexico（新墨西哥大学）；Florida International University（佛罗里达国际大学）；Florida Atlantic University（佛罗里达大西洋大学）；University of Washington（华盛顿大学）；Islamic Azad University（伊斯兰阿扎德大学）
HybridGuard: Enhancing Minority-Class Intrusion Detection in Dew-Enabled Edge-of-Things Networks
Department of Computer Science and Information Engineering, National Taiwan University of Science and Technology（计算机科学与信息工程系，台湾科技大学）；Department of Computer Science and Engineering, Digital University Kerala（计算机科学与工程系，数字大学喀拉拉）
Western University（西部大学）；National Research Council (NRC)（国家研究委员会）
The use of autonomous vehicles (AVs) is a promising technology in Intelligent Transportation Systems (ITSs) to improve safety and driving efficiency. Vehicle-to-everything (V2X) technology enables communication among vehicles and other infrastructures. However, AVs and Internet of Vehicles (IoV) are vulnerable to different types of cyber-attacks such as denial of service, spoofing, and sniffing attacks. In this paper, an intelligent intrusion detection system (IDS) is proposed based on tree-structure machine learning models. The results from the implementation of the proposed intrusion detecti…
Cyber Security Strategic Technology Centre, ST Engineering Singapore（新加坡ST工程公司网络安全战略技术中心）
Internet of Things (IoT) has become a popular paradigm to fulfil needs of the industry such as asset tracking, resource monitoring and automation. As security mechanisms are often neglected during the deployment of IoT devices, they are more easily attacked by complicated and large volume intrusion attacks using advanced techniques. Artificial Intelligence (AI) has been used by the cyber security community in the past decade to automatically identify such attacks. However, deep learning methods have yet to be extensively explored for Intrusion Detection Systems (IDS) specifically for IoT. Most…
An increasing amount of processes are becoming automated for increased efficiency and safety. Common examples are in automotive, industrial control systems or healthcare. Automation usually relies on a network of sensors to provide key data to control systems. One potential risk to these automated processes comes from fraudulent data injected in the network by malicious actors. In this article we propose a new mechanism of data tampering detection that does not depend on secret cryptographic keys - that can be lost or stolen - or accurate modelling of the network as is the case with existing m…
Internet of Things (IoT) has brought along immense benefits to our daily lives encompassing a diverse range of application domains that we regularly interact with, ranging from healthcare automation to transport and smart environments. However, due to the limitation of constrained resources and computational capabilities, IoT networks are prone to various cyber attacks. Thus, defending the IoT network against adversarial attacks is of vital importance. In this paper, we present a novel intrusion detection approach for IoT networks through the application of a deep learning technique. We adopt …
The rapid growth of technology has led to the creation of computing networks. The applications of the Internet of Things are becoming more and more visible with the expansion and development of sensors and the use of a series of equipment to connect to the Internet. Of course, the growth of any network will also provide some challenges. The main challenge of IoT like any other network is its security. In the field of security, there are issues such as attack detection, authentication, encryption and the so on. One of the most important attack is cyber-attacks that disrupt the network usage. On…
The growing interest in the Internet of Things (IoT) applications is associated with an augmented volume of security threats. In this vein, the Intrusion detection systems (IDS) have emerged as a viable solution for the detection and prevention of malicious activities. Unlike the signature-based detection approaches, machine learning-based solutions are a promising means for detecting unknown attacks. However, the machine learning models need to be accurate enough to reduce the number of false alarms. More importantly, they need to be trained and evaluated on realistic datasets such that their…
University of Murcia（穆尔西亚大学）；European Commission, Joint Research Centre（欧盟委员会联合研究中心）
The application of Machine Learning (ML) techniques to the well-known intrusion detection systems (IDS) is key to cope with increasingly sophisticated cybersecurity attacks through an effective and efficient detection process. In the context of the Internet of Things (IoT), most ML-enabled IDS approaches use centralized approaches where IoT devices share their data with data centers for further analysis. To mitigate privacy concerns associated with centralized approaches, in recent years the use of Federated Learning (FL) has attracted a significant interest in different sectors, including hea…
To reap the benefits of the Internet of Things (IoT), it is imperative to secure the system against cyber attacks in order to enable mission critical and real-time applications. To this end, intrusion detection systems (IDSs) have been widely used to detect anomalies caused by a cyber attacker in IoT systems. However, due to the large-scale nature of the IoT, an IDS must operate in a distributed manner with minimum dependence on a central controller. Moreover, in many scenarios such as health and financial applications, the datasets are private and IoTDs may not intend to share such data. To t…
The emerging trend of ubiquitous and pervasive computing aims at embedding everyday devices such as wristwatches, smart phones, home video systems, autofocus cameras, intelligent vehicles, musical instruments, kitchen appliances etc. with microprocessors and imparts them with wireless communication capability. This advanced computing paradigm, also known as the Internet of Things or cyber-physical computing, leads internet and computing to appear everywhere and anywhere using any device and location. With maximum appreciation and due regards to the evolutionary arc, depth and scope of ceaseles…
The Internet of Things has received a lot of research attention. It is considered part of the Internet of the future and is made up of billions of intelligent communication. The future of the Internet will consist of heterogeneously connected devices that expand the world boundaries with physical entities and virtual components. It provides new functionality for related things. This study systematically examines the definition, architecture, essential technologies, and applications of the Internet of Things. We will introduce various definitions of the Internet of Things. Then, it will be disc…
Modern vehicles, including autonomous vehicles and connected vehicles, are increasingly connected to the external world, which enables various functionalities and services. However, the improving connectivity also increases the attack surfaces of the Internet of Vehicles (IoV), causing its vulnerabilities to cyber-threats. Due to the lack of authentication and encryption procedures in vehicular networks, Intrusion Detection Systems (IDSs) are essential approaches to protect modern vehicle systems from network attacks. In this paper, a transfer learning and ensemble learning-based IDS is propos…
The growth in the number of devices connected to the Internet of Things (IoT) poses major challenges in security. The integrity and trustworthiness of data and data analytics are increasingly important concerns in IoT applications. These are compounded by the highly distributed nature of IoT devices, making it infeasible to prevent attacks and intrusions on all data sources. Adversaries may hijack devices and compromise their data. As a result, reactive countermeasures, such as intrusion detection and resilient analytics, become vital components of security. This paper overviews algorithms for…
As a solution to protect and defend a system against inside attacks, many intrusion detection systems (IDSs) have been developed to identify and react to them for protecting a system. However, the core idea of an IDS is a reactive mechanism in nature even though it detects intrusions which have already been in the system. Hence, the reactive mechanisms would be way behind and not effective for the actions taken by agile and smart attackers. Due to the inherent limitation of an IDS with the reactive nature, intrusion prevention systems (IPSs) have been developed to thwart potential attackers an…
Centralized systems in the Internet of Things---be it local middleware or cloud-based services---fail to fundamentally address privacy of the collected data. We propose an architecture featuring secure multiparty computation at its core in order to realize data processing systems which already incorporate support for privacy protection in the architecture.
The Internet of Things (IoT), the Industrial Internet of Things (IIoT), and Cyber-Physical Systems (CPS) have become essential for our daily lives in contexts such as our homes, buildings, cities, health, transportation, manufacturing, infrastructure, and agriculture. However, they have become popular targets of attacks, due to their inherent limitations which create vulnerabilities. Honeypots and honeynets can prove essential to understand and defend against attacks on IoT, IIoT, and CPS environments by attracting attackers and deceiving them into thinking that they have gained access to the …
This paper is a general survey of all the security issues existing in the Internet of Things (IoT) along with an analysis of the privacy issues that an end-user may face as a consequence of the spread of IoT. The majority of the survey is focused on the security loopholes arising out of the information exchange technologies used in Internet of Things. No countermeasure to the security drawbacks has been analyzed in the paper.
With the rapid development of the Internet of Things, there are many interacting devices and applications. One crucial challenge is how to provide security. Our proposal for a new direction is to create "smart buttons" and collections of them called "smart blankets" as hardware/software security patches rather than software-only patches.
The Internet of Things makes possible to connect each everyday object to the Internet, making computing pervasive like never before. From a security and privacy perspective, this tsunami of connectivity represents a disaster, which makes each object remotely hackable. We claim that, in order to tackle this issue, we need to address a new challenge in security: education.
The Internet of Things paradigm envisions the pervasive interconnection and cooperation of smart things over the current and future Internet infrastructure. The Internet of Things is, thus, the evolution of the Internet to cover the real-world, enabling many new services that will improve people's everyday lives, spawn new businesses and make buildings, cities and transport smarter. Smart things allow indeed for ubiquitous data collection or tracking, but these useful features are also examples of privacy threats that are already now limiting the success of the Internet of Things vision when n…
Internet of Things (IoT) is a disruptive technology with applications across diverse domains such as transportation and logistics systems, smart grids, smart homes, connected vehicles, and smart cities. Alongside the growth of these infrastructures, the volume and variety of attacks on these infrastructures has increased highlighting the significance of distinct protection mechanisms. Intrusion detection is one of the distinguished protection mechanisms with notable recent efforts made to establish effective intrusion detection for IoT and IoV. However, unique characteristics of such infrastru…
The new generation of security threats has been promoted by digital currencies and real-time applications, where all users develop new ways to communicate on the Internet. Security has evolved in the need of privacy and anonymity for all users and his portable devices. New technologies in every field prove that users need security features integrated into their communication applications, parallel systems for mobile devices, internet, and identity management. This review presents the key concepts of the main areas in computer security and how it has evolved in the last years. This work focuses…
The rapid growth of the Internet of Things technology in healthcare domain led to the appearance of many security threats and risks. It became very challenging to provide full protection with the expansion in using sensor objects in medical field, this led to the Internet of Medical Things definition, the security part in IoMT poses a perilous problem that keeps growing, because of the data sensitivity and critical information. The lack of providing a secure environment in IoMT may lead to patients privacy issues, not only leaving the data privacy of the patients at risk but also their lives c…
Given the tremendous success of the Internet of Things in interconnecting consumer devices, we observe a natural trend to likewise interconnect devices in industrial settings, referred to as Industrial Internet of Things or Industry 4.0. While this coupling of industrial components provides many benefits, it also introduces serious security challenges. Although sharing many similarities with the consumer Internet of Things, securing the Industrial Internet of Things introduces its own challenges but also opportunities, mainly resulting from a longer lifetime of components and a larger scale of…
This paper studies the effect of various hyper-parameters and their selection for the best performance of the deep learning model proposed in [1] for distributed attack detection in the Internet of Things (IoT). The findings show that there are three hyper-parameters that have more influence on the best performance achieved by the model. As a consequence, this study shows that the model's accuracy as reported in the paper is not achievable, based on the best selections of parameters, which is also supported by another recent publication [2].
Attribute-Based Encryption (ABE) could be an effective cryptographic tool for the secure management of Internet-of-Things (IoT) devices, but its feasibility in the IoT has been under-investigated thus far. This article explores such feasibility for well-known IoT platforms, namely, Intel Galileo Gen 2, Intel Edison, Raspberry Pi 1 Model B, and Raspberry Pi Zero, and concludes that adopting ABE in the IoT is indeed feasible.
Internet of Things (IoT), also referred to as the Internet of Objects, is envisioned as a holistic and transformative approach for providing numerous services. The rapid development of various communication protocols and miniaturization of transceivers along with recent advances in sensing technologies offer the opportunity to transform isolated devices into communicating smart things. Smart things, that can sense, store, and even process electrical, thermal, optical, chemical, and other signals to extract user-/environment-related information, have enabled services only limited by human imagi…
A massive current research effort focuses on combining pre-existing 'Intranets' of Things into one Internet of Things. However, this unification is not a panacea; it will expose new attack surfaces and vectors, just as it enables new applications. We therefore urgently need a model of security in the Internet of Things. In this regard, we note that IoT descends directly from pre-existing research (in embedded Internet and pervasive intelligence), so there exist several bodies of related work: security in RFID, sensor networks, cyber-physical systems, and so on. In this paper, we survey the exi…
No significant research has been conducted so far on Intrusion detection due to data availability since, network traffic within companies is private information and no available logs can be found on the Internet for independent research. This paper aims to answer the question whether open-sourced data, that is usually simulated network traffic can assist in developing a robust model that will effectively recognize and deter possible denial of service or infiltration attacks.
Denial of service attacks are especially pertinent to the internet of things as devices have less computing power, memory and security mechanisms to defend against them. The task of mitigating these attacks must therefore be redirected from the device onto a network monitor. Network intrusion detection systems can be used as an effective and efficient technique in internet of things systems to offload computation from the devices and detect denial of service attacks before they can cause harm. However the solution of implementing a network intrusion detection system for internet of things netw…
This paper analyses the various authentication systems implemented for enhanced security and private re-position of an individual's log-in credentials. The first part of the paper describes the multi-factor authentication (MFA) systems, which, though not applicable to the field of Internet of Things, provides great security to a user's credentials. MFA is followed by a brief description of the working mechanism of interaction of third party clients with private resources over the OAuth protocol framework and a study of the delegation based authentication system in IP-based IoT.
There is a growing interest from both the academia and industry to employ distributed ledger technology in the Internet-of-Things domain for addressing security-related and performance challenges. Distributed ledger technology enables non-trusted entities to communicate and reach consensus in a fully distributed manner through a cryptographically secure and immutable ledger. However, significant challenges arise mainly related to transaction processing speed and user privacy. This work explores the interplay between Internet-of-Things and distributed ledger technology, analysing the fundamenta…
Internet of Things (IoT) is now omnipresent in all aspects of life and provides a large number of potentially critical services. For this, Internet of Things relies on the data collected by objects. Data integrity is therefore essential. Unfortunately, this integrity is threatened by a type of attack known as False Data Injection Attack. This consists of an attacker who injects fabricated data into a system to modify its behaviour. In this work, we dissect and present a method that uses a Domain-Specific Language (DSL) to generate altered data, allowing these attacks to be simulated and tested…
This paper provides a comprehensive and high level technical overview of BC technology by creating a common language through business and technology about BC. Then an overview of a BC technology, its architectures, classification, challenges, etc. is presented. Finally, some recommendations are provided to re-searchers that will have to be tackled before deploying the next generation of IoT applications based on BC technology.
In the Internet-of-Things, the number of connected devices is expected to be extremely huge, i.e., more than a couple of ten billion. It is however well-known that the security for the Internet-of-Things is still open problem. In particular, it is difficult to certify the identification of connected devices and to prevent the illegal spoofing. It is because the conventional security technologies have advanced for mainly protecting logical network and not for physical network like the Internet-of-Things. In order to protect the Internet-of-Things with advanced security technologies, we propose …
Modern vehicles, including connected vehicles and autonomous vehicles, nowadays involve many electronic control units connected through intra-vehicle networks to implement various functionalities and perform actions. Modern vehicles are also connected to external networks through vehicle-to-everything technologies, enabling their communications with other vehicles, infrastructures, and smart devices. However, the improving functionality and connectivity of modern vehicles also increase their vulnerabilities to cyber-attacks targeting both intra-vehicle and external networks due to the large at…
Key generation is a promising technique to bootstrap secure communications for the Internet of Things (IoT) devices that have no prior knowledge between each other. In the past few years, a variety of key generation protocols and systems have been proposed. In this survey, we review and categorise recent key generation systems based on a novel taxonomy. Then, we provide both quantitative and qualitative comparisons of existing approaches. We also discuss the security vulnerabilities of key generation schemes and possible countermeasures. Finally, we discuss the current challenges and point out…
The Internet of Things (IoT) is a new computing paradigm that spans wearable devices, homes, hospitals, cities, transportation, and critical infrastructure. Building security into this new computing paradigm is a major technical challenge today. However, what are the security problems in IoT that we can solve using existing security principles? And, what are the new problems and challenges in this space that require new security mechanisms? This article summarizes the intellectual similarities and differences between classic information technology security research and IoT security research.
Despite technological advances, most smart objects in the Internet of Things (IoT) cannot be accessed using technologies designed and developed for interacting with powerful Internet servers. IoT use cases involve devices that not only have limited resources, but also they are not always connected to the Internet and are physically exposed to tampering. In this paper, we describe the design, development, and evaluation of a smart contract-based solution that allows end-users to securely interact with smart devices. Our approach enables access control, Thing authentication, and payments in a fu…
The Internet of Things (IoT) is a global ecosystem of information and communication technologies aimed at connecting any type of object (thing), at any time and in any place, to each other and to the Internet. One of the major problems associated with the IoT is maintaining security; the heterogeneous nature of such deployments poses a challenge to many aspects of security, including security testing and analysis. In addition, there is no existing mechanism that performs security testing for IoT devices in different contexts. In this paper, we propose an innovative security testbed framework t…
Authentication forms the gateway to any secure system. Together with integrity, confidentiality and authorization it helps in preventing any sort of intrusions into the system. Up until a few years back password based authentication was the most common form of authentication to any secure network. But with the advent of more sophisticated technologies this form of authentication although still widely used has become insecure. Furthermore, with the rise of 'Internet of Things' where the number of devices would grow manifold it would be infeasible for user to remember innumerable passwords. Ther…
