Internet of Things Security and Privacy

The Internet of Things is becoming more and more popular with time. The extremely low cost of sensors is putting the growth of the Internet of Things on steroids. Many industries such as healthcare, construction, agriculture, and transportation are increasingly leveraging this technology. However, security and privacy are two big concerns when it comes to the future of the Internet of Things. Since most of these “things” that are connected to the Internet are simple devices with limited hardware capabilities, it is nearly impossible to harden them via traditional resource-heavy defenses. In this chapter, we discuss the importance of securing the Internet of Things networks, layout the challenges of the Internet of Things security, and briefly discuss potential solutions in the literature

Internet of Things (IoT): Cybersecurity Risks in Healthcare

The rapid growth and investment in the Internet of Things (IoT) has significantly impacted how individuals and industries operate. The Internet of Things (IoT) refers to a network of physical, technology-embedded objects that communicate, detect, and interact with their external environment or internal state (Hung, 2017). According to Tankovska (2020), IoT devices are estimated to reach 21.5 billion units by 2025. This technological boom is leading various industrial sectors to notice a quick increase in cybersecurity risks and threats. One industrial sector has been particularly vulnerable to numerous cyber threats across the globe: healthcare. Oliver Noble (2020), a data encryption specialist at NordLocker, suggests that cybercriminals target healthcare institutions because they store an overwhelming amount of patient information that is private, personal, and unchangeable. Healthcare organizations have a difficult time securing their cybersecurity infrastructure and the reasons for this will be further discussed in this paper

Securing the Internet of Things Infrastructure - Standards and Techniques

The Internet of Things (IoT) infrastructure is a conglomerate of electronic devices interconnected through the Internet, with the purpose of providing prompt and effective service to end-users. Applications running on an IoT infrastructure generally handle sensitive information such as a patient’s healthcare record, the position of a logistic vehicle, or the temperature readings obtained through wireless sensor nodes deployed in a bushland. The protection of such information from unlawful disclosure, tampering or modification, as well as the unscathed presence of IoT devices, in adversarial environments, is of prime concern. In this paper, a descriptive analysis of the security of standards and technologies for protecting the IoT communication channel from adversarial threats is provided. In addition, two paradigms for securing the IoT infrastructure, namely, common key based and paired key based, are proposed

Energy-Efficient IoT e-Health Using Artificial Intelligence Model with Homomorphic Secret Sharing

[EN] Internet of Things (IoT) is a developing technology for supporting heterogeneous physical objects into smart things and improving the individuals living using wireless communication systems. Recently, many smart healthcare systems are based on the Internet of Medical Things (IoMT) to collect and analyze the data for infectious diseases, i.e., body fever, flu, COVID-19, shortness of breath, etc. with the least operation cost. However, the most important research challenges in such applications are storing the medical data on a secured cloud and make the disease diagnosis system more energy efficient. Additionally, the rapid explosion of IoMT technology has involved many cyber-criminals and continuous attempts to compromise medical devices with information loss and generating bogus certificates. Thus, the increase in modern technologies for healthcare applications based on IoMT, securing health data, and offering trusted communication against intruders is gaining much research attention. Therefore, this study aims to propose an energy-efficient IoT e-health model using artificial intelligence with homomorphic secret sharing, which aims to increase the maintainability of disease diagnosis systems and support trustworthy communication with the integration of the medical cloud. The proposed model is analyzed and proved its significance against relevant systems.Prince Sultan University, Riyadh Saudi Arabia, (SEED-CCIS-2021{85}) under Artificial Intelligence & Data Analytics Research Lab. CCIS.Rehman, A.; Saba, T.; Haseeb, K.; Marie-Sainte, SL.; Lloret, J. (2021). Energy-Efficient IoT e-Health Using Artificial Intelligence Model with Homomorphic Secret Sharing. Energies. 14(19):1-15. https://doi.org/10.3390/en14196414S115141

Securing the internet of things infrastructure – standards and techniques

The Internet of Things (IoT) infrastructure is a conglomerate of electronic devices interconnected through the Internet, with the purpose of providing prompt and effective service to end-users. Applications running on an IoT infrastructure generally handle sensitive information such as a patient’s healthcare record, the position of a logistic vehicle, or the temperature readings obtained through wireless sensor nodes deployed in a bushland. The protection of such information from unlawful disclosure, tampering or modification, as well as the unscathed presence of IoT devices, in adversarial environments, is of prime concern. In this paper, a descriptive analysis of the security of standards and technologies for protecting the IoT communication channel from adversarial threats is provided. In addition, two paradigms for securing the IoT infrastructure, namely, common key based and paired key based, are proposed

Using the Big Data and IoT Technologies in the Field of Healthcare

This paper presents the main approaches of new IT technologies used in healthcare. These technologies refer to Big Data, Big Data Analytics (BDA) and Internet of Things (IoT). The new Big Data technologies can help physicians choose the correct and faster treatment, based on information collected by another healthcare professional. Patients can benefit from more appropriate and on time treatment to be better informed about health care providers. The BDA addresses the challenges generated by: the increasing share of unstructured and multi-structured data generated by highly prolific and widespread data sources (such as social networks, sensor networks, the Internet of Things) and the growing gap in the amount of important data and the ability to process them in time for decision support. The Internet of Things (IoT) refers to the network of devices that consist of sensors that measure the environment, elements that send response reaction, processors that manage and store generated data, nodes that coordinate the management of these. IoT stands for smart home appliance applications and services, healthcare applications, and more. For the efficient processing of information generated by IoT infrastructures, it is essential to use the Big Data and BDA solutions in order to capitalize on their decisions in beneficiary communities. These solutions, BD and BDA, relate to capturing and analyzing data, examining and storing large volumes of data, and securing confidential data. The paper also includes authors’ suggestions on developing strategic measures / recommendations for using Big Data in Health domain

ETEASH-An Enhanced Tiny Encryption Algorithm for Secured Smart Home

The proliferation of the "Internet of Things" (IoT) and its applications have affected every aspect of human endeavors from smart manufacturing, agriculture, healthcare, and transportation to homes. The smart home is vulnerable to malicious attacks due to memory constraint which inhibits the usage of traditional antimalware and antivirus software. This makes the application of traditional cryptography for its security impossible. This work aimed at securing Smart home devices, by developing an enhanced Tiny Encryption Algorithm (TEA). The enhancement on TEA was to get rid of its vulnerabilities of related-key attacks and weakness of predictable keys to be usable in securing smart devices through entropy shifting, stretching, and mixing technique. The Enhanced Tiny Encryption Algorithm for Smart Home devices (ETEASH) technique was benchmarked with the original TEA using the Runs test and avalanche effect. ETEASH successfully passed the Runs test with the significance level of 0.05 for the null hypothesis, and the ETEASH avalanche effect of 58.44% was achieved against 52.50% for TEA. These results showed that ETEASH is more secured in securing smart home devices than the standard TEA

AUTHENTICATED KEY ESTABLISHMENT PROTOCOL FOR CONSTRAINED SMART HEALTHCARE SYSTEMS BASED ON PHYSICAL UNCLONABLE FUNCTION

Smart healthcare systems are one of the critical applications of the internet of things. They benefit many categories of the population and provide significant improvement to healthcare services. Smart healthcare systems are also susceptible to many threats and exploits because they run without supervision for long periods of time and communicate via open channels. Moreover, in many implementations, healthcare sensor nodes are implanted or miniaturized and are resource-constrained. The potential risks on patients/individuals’ life from the threats necessitate that securing the connections in these systems is of utmost importance. This thesis provides a solution to secure end-to-end communications in such systems by proposing an authenticated key establishment protocol. The main objective of the protocol is to examine how physical unclonable functions could be utilized as a lightweight root of trust. The protocol’s design is based on rigid security requirements and inspired by the vulnerability of physical unclonable function to machine learning modeling attacks as well as the use of a ratchet technique. The proposed protocol verification and analysis revealed that it is a suitable candidate for resource-constrained smart healthcare systems. The proposed protocol’s design also has an impact on other important aspects such as anonymity of sensor nodes and gateway-lose scenario