On the feasibility of attribute-based encryption on Internet of Things devices

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

Offloading SLAM for Indoor Mobile Robots with Edge, Fog, Cloud Computing

Indoor mobile robots are widely used in industrial environments such as large logistic warehouses. They are often in charge of collecting or sorting products. For such robots, computation-intensive operations account for a significant per- centage of the total energy consumption and consequently affect battery life. Besides, in order to keep both the power con- sumption and hardware complexity low, simple micro-controllers or single-board computers are used as onboard local control units. This limits the computational capabilities of robots and consequently their performance. Offloading heavy computation to Cloud servers has been a widely used approach to solve this problem for cases where large amounts of sensor data such as real-time video feeds need to be analyzed. More recently, Fog and Edge computing are being leveraged for offloading tasks such as image processing and complex navigation algorithms involving non-linear mathematical operations. In this paper, we present a system architecture for offloading computationally expensive localization and mapping tasks to smart Edge gateways which use Fog services. We show how Edge computing brings computational capabilities of the Cloud to the robot environment without compromising operational reliability due to connection issues. Furthermore, we analyze the power consumption of a prototype robot vehicle in different modes and show how battery life can be significantly improved by moving the processing of data to the Edge layer

Offloading SLAM for Indoor Mobile Robots with Edge-Fog-Cloud Computing

Indoor mobile robots are widely used in industrial environments such as large logistic warehouses. They are often in charge of collecting or sorting products. For such robots, computation-intensive operations account for a significant per- centage of the total energy consumption and consequently affect battery life. Besides, in order to keep both the power con- sumption and hardware complexity low, simple micro-controllers or single-board computers are used as onboard local control units. This limits the computational capabilities of robots and consequently their performance. Offloading heavy computation to Cloud servers has been a widely used approach to solve this problem for cases where large amounts of sensor data such as real-time video feeds need to be analyzed. More recently, Fog and Edge computing are being leveraged for offloading tasks such as image processing and complex navigation algorithms involving non-linear mathematical operations. In this paper, we present a system architecture for offloading computationally expensive localization and mapping tasks to smart Edge gateways which use Fog services. We show how Edge computing brings computational capabilities of the Cloud to the robot environment without compromising operational reliability due to connection issues. Furthermore, we analyze the power consumption of a prototype robot vehicle in different modes and show how battery life can be significantly improved by moving the processing of data to the Edge layer

Systematic Review of Internet of Things Security

The Internet of Things has become a new paradigm of current communications technology that requires a deeper overview to map its application domains, advantages, and disadvantages. There have been a number of in-depth research efforts to study various aspects of IoT. However, to the best of our knowledge, there is no literature that have discussed specifically and deeply about the security and privacy aspects of IoT. To that end, this paper aims at providing a more comprehensive and systematic review of IoT security based on the survey result of the most recent literature over the past three years (2015 to 2017). We have classified IoT security research based on the research objectives, application domains, vulner-abilities/threats, countermeasures, platforms, proto-cols, and performance measurements. We have also provided some security challenges for further research

Improving efficiency and security of IIoT communications using in-network validation of server certificate

The use of advanced communications and smart mechanisms in industry is growing rapidly, making cybersecurity a critical aspect. Currently, most industrial communication protocols rely on the Transport Layer Security (TLS) protocol to build their secure version, providing confidentiality, integrity and authentication. In the case of UDP-based communications, frequently used in Industrial Internet of Things (IIoT) scenarios, the counterpart of TLS is Datagram Transport Layer Security (DTLS), which includes some mechanisms to deal with the high unreliability of the transport layer. However, the (D)TLS handshake is a heavy process, specially for resource-deprived IIoT devices and frequently, security is sacrificed in favour of performance. More specifically, the validation of digital certificates is an expensive process from the time and resource consumption point of view. For this reason, digital certificates are not always properly validated by IIoT devices, including the verification of their revocation status; and when it is done, it introduces an important delay in the communications. In this context, this paper presents the design and implementation of an in-network server certificate validation system that offloads this task from the constrained IIoT devices to a resource-richer network element, leveraging data plane programming (DPP). This approach enhances security as it guarantees that a comprehensive server certificate verification is always performed. Additionally, it increases performance as resource-expensive tasks are moved from IIoT devices to a resource-richer network element. Results show that the proposed solution reduces DTLS handshake times by 50–60 %. Furthermore, CPU use in IIoT devices is also reduced, resulting in an energy saving of about 40 % in such devices.This work was financially supported by the Spanish Ministry of Science and Innovation through the TRUE-5G project PID2019-108713RB-C54/AEI/10.13039/501100011033. It was also partially supported by the Ayudas Cervera para Centros Tecnológicos grant of the Spanish Centre for the Development of Industrial Technology (CDTI) under the project EGIDA (CER-20191012), and by the Basque Country Government under the ELKARTEK Program, project REMEDY - Real tiME control and embeddeD securitY (KK-2021/00091)

Security for networked smart healthcare systems: A systematic review

Background and Objectives Smart healthcare systems use technologies such as wearable devices, Internet of Medical Things and mobile internet technologies to dynamically access health information, connect patients to health professionals and health institutions, and to actively manage and respond intelligently to the medical ecosystem's needs. However, smart healthcare systems are affected by many challenges in their implementation and maintenance. Key among these are ensuring the security and privacy of patient health information. To address this challenge, several mitigation measures have been proposed and some have been implemented. Techniques that have been used include data encryption and biometric access. In addition, blockchain is an emerging security technology that is expected to address the security issues due to its distributed and decentralized architecture which is similar to that of smart healthcare systems. This study reviewed articles that identified security requirements and risks, proposed potential solutions, and explained the effectiveness of these solutions in addressing security problems in smart healthcare systems. Methods This review adhered to the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) guidelines and was framed using the Problem, Intervention, Comparator, and Outcome (PICO) approach to investigate and analyse the concepts of interest. However, the comparator is not applicable because this review focuses on the security measures available and in this case no comparable solutions were considered since the concept of smart healthcare systems is an emerging one and there are therefore, no existing security solutions that have been used before. The search strategy involved the identification of studies from several databases including the Cumulative Index of Nursing and Allied Health Literature (CINAL), Scopus, PubMed, Web of Science, Medline, Excerpta Medical database (EMBASE), Ebscohost and the Cochrane Library for articles that focused on the security for smart healthcare systems. The selection process involved removing duplicate studies, and excluding studies after reading the titles, abstracts, and full texts. Studies whose records could not be retrieved using a predefined selection criterion for inclusion and exclusion were excluded. The remaining articles were then screened for eligibility. A data extraction form was used to capture details of the screened studies after reading the full text. Of the searched databases, only three yielded results when the search strategy was applied, i.e., Scopus, Web of science and Medline, giving a total of 1742 articles. 436 duplicate studies were removed. Of the remaining articles, 801 were excluded after reading the title, after which 342 after were excluded after reading the abstract, leaving 163, of which 4 studies could not be retrieved. 159 articles were therefore screened for eligibility after reading the full text. Of these, 14 studies were included for detailed review using the formulated research questions and the PICO framework. Each of the 14 included articles presented a description of a smart healthcare system and identified the security requirements, risks and solutions to mitigate the risks. Each article also summarized the effectiveness of the proposed security solution. Results The key security requirements reported were data confidentiality, integrity and availability of data within the system, with authorisation and authentication used to support these key security requirements. The identified security risks include loss of data confidentiality due to eavesdropping in wireless communication mediums, authentication vulnerabilities in user devices and storage servers, data fabrication and message modification attacks during transmission as well as while the data is at rest in databases and other storage devices. The proposed mitigation measures included the use of biometric accessing devices; data encryption for protecting the confidentiality and integrity of data; blockchain technology to address confidentiality, integrity, and availability of data; network slicing techniques to provide isolation of patient health data in 5G mobile systems; and multi-factor authentication when accessing IoT devices, servers, and other components of the smart healthcare systems. The effectiveness of the proposed solutions was demonstrated through their ability to provide a high level of data security in smart healthcare systems. For example, proposed encryption algorithms demonstrated better energy efficiency, and improved operational speed; reduced computational overhead, better scalability, efficiency in data processing, and better ease of deployment. Conclusion This systematic review has shown that the use of blockchain technology, biometrics (fingerprints), data encryption techniques, multifactor authentication and network slicing in the case of 5G smart healthcare systems has the potential to alleviate possible security risks in smart healthcare systems. The benefits of these solutions include a high level of security and privacy for Electronic Health Records (EHRs) systems; improved speed of data transaction without the need for a decentralized third party, enabled by the use of blockchain. However, the proposed solutions do not address data protection in cases where an intruder has already accessed the system. This may be potential avenues for further research and inquiry

Towards end-to-end security in internet of things based healthcare

Healthcare IoT systems are distinguished in that they are designed to serve human beings, which primarily raises the requirements of security, privacy, and reliability. Such systems have to provide real-time notifications and responses concerning the status of patients. Physicians, patients, and other caregivers demand a reliable system in which the results are accurate and timely, and the service is reliable and secure. To guarantee these requirements, the smart components in the system require a secure and efficient end-to-end communication method between the end-points (e.g., patients, caregivers, and medical sensors) of a healthcare IoT system. The main challenge faced by the existing security solutions is a lack of secure end-to-end communication. This thesis addresses this challenge by presenting a novel end-to-end security solution enabling end-points to securely and efficiently communicate with each other. The proposed solution meets the security requirements of a wide range of healthcare IoT systems while minimizing the overall hardware overhead of end-to-end communication. End-to-end communication is enabled by the holistic integration of the following contributions. The first contribution is the implementation of two architectures for remote monitoring of bio-signals. The first architecture is based on a low power IEEE 802.15.4 protocol known as ZigBee. It consists of a set of sensor nodes to read data from various medical sensors, process the data, and send them wirelessly over ZigBee to a server node. The second architecture implements on an IP-based wireless sensor network, using IEEE 802.11 Wireless Local Area Network (WLAN). The system consists of a IEEE 802.11 based sensor module to access bio-signals from patients and send them over to a remote server. In both architectures, the server node collects the health data from several client nodes and updates a remote database. The remote webserver accesses the database and updates the webpage in real-time, which can be accessed remotely. The second contribution is a novel secure mutual authentication scheme for Radio Frequency Identification (RFID) implant systems. The proposed scheme relies on the elliptic curve cryptography and the D-Quark lightweight hash design. The scheme consists of three main phases: (1) reader authentication and verification, (2) tag identification, and (3) tag verification. We show that among the existing public-key crypto-systems, elliptic curve is the optimal choice due to its small key size as well as its efficiency in computations. The D-Quark lightweight hash design has been tailored for resource-constrained devices. The third contribution is proposing a low-latency and secure cryptographic keys generation approach based on Electrocardiogram (ECG) features. This is performed by taking advantage of the uniqueness and randomness properties of ECG's main features comprising of PR, RR, PP, QT, and ST intervals. This approach achieves low latency due to its reliance on reference-free ECG's main features that can be acquired in a short time. The approach is called Several ECG Features (SEF)-based cryptographic key generation. The fourth contribution is devising a novel secure and efficient end-to-end security scheme for mobility enabled healthcare IoT. The proposed scheme consists of: (1) a secure and efficient end-user authentication and authorization architecture based on the certificate based Datagram Transport Layer Security (DTLS) handshake protocol, (2) a secure end-to-end communication method based on DTLS session resumption, and (3) support for robust mobility based on interconnected smart gateways in the fog layer. Finally, the fifth and the last contribution is the analysis of the performance of the state-of-the-art end-to-end security solutions in healthcare IoT systems including our end-to-end security solution. In this regard, we first identify and present the essential requirements of robust security solutions for healthcare IoT systems. We then analyze the performance of the state-of-the-art end-to-end security solutions (including our scheme) by developing a prototype healthcare IoT system

Revisiting the Feasibility of Public Key Cryptography in Light of IIoT Communications

Digital certificates are regarded as the most secure and scalable way of implementing authentication services in the Internet today. They are used by most popular security protocols, including Transport Layer Security (TLS) and Datagram Transport Layer Security (DTLS). The lifecycle management of digital certificates relies on centralized Certification Authority (CA)-based Public Key Infrastructures (PKIs). However, the implementation of PKIs and certificate lifecycle management procedures in Industrial Internet of Things (IIoT) environments presents some challenges, mainly due to the high resource consumption that they imply and the lack of trust in the centralized CAs. This paper identifies and describes the main challenges to implement certificate-based public key cryptography in IIoT environments and it surveys the alternative approaches proposed so far in the literature to address these challenges. Most proposals rely on the introduction of a Trusted Third Party to aid the IIoT devices in tasks that exceed their capacity. The proposed alternatives are complementary and their application depends on the specific challenge to solve, the application scenario, and the capacities of the involved IIoT devices. This paper revisits all these alternatives in light of industrial communication models, identifying their strengths and weaknesses, and providing an in-depth comparative analysis.This work was financially supported by the European commission through ECSEL-JU 2018 program under the COMP4DRONES project (grant agreement N∘ 826610), with national financing from France, Spain, Italy, Netherlands, Austria, Czech, Belgium and Latvia. It was also partially supported by the Ayudas Cervera para Centros Tecnológicos grant of the Spanish Centre for the Development of Industrial Technology (CDTI) under the project EGIDA (CER-20191012), and in part by the Department of Economic Development and Competitiveness of the Basque Government through the project TRUSTIND—Creating Trust in the Industrial Digital Transformation (KK-2020/00054)

Design for energy-efficient and reliable fog-assisted healthcare IoT systems

Cardiovascular disease and diabetes are two of the most dangerous diseases as they are the leading causes of death in all ages. Unfortunately, they cannot be completely cured with the current knowledge and existing technologies. However, they can be effectively managed by applying methods of continuous health monitoring. Nonetheless, it is difficult to achieve a high quality of healthcare with the current health monitoring systems which often have several limitations such as non-mobility support, energy inefficiency, and an insufficiency of advanced services. Therefore, this thesis presents a Fog computing approach focusing on four main tracks, and proposes it as a solution to the existing limitations. In the first track, the main goal is to introduce Fog computing and Fog services into remote health monitoring systems in order to enhance the quality of healthcare. In the second track, a Fog approach providing mobility support in a real-time health monitoring IoT system is proposed. The handover mechanism run by Fog-assisted smart gateways helps to maintain the connection between sensor nodes and the gateways with a minimized latency. Results show that the handover latency of the proposed Fog approach is 10%-50% less than other state-of-the-art mobility support approaches. In the third track, the designs of four energy-efficient health monitoring IoT systems are discussed and developed. Each energy-efficient system and its sensor nodes are designed to serve a specific purpose such as glucose monitoring, ECG monitoring, or fall detection; with the exception of the fourth system which is an advanced and combined system for simultaneously monitoring many diseases such as diabetes and cardiovascular disease. Results show that these sensor nodes can continuously work, depending on the application, up to 70-155 hours when using a 1000 mAh lithium battery. The fourth track mentioned above, provides a Fog-assisted remote health monitoring IoT system for diabetic patients with cardiovascular disease. Via several proposed algorithms such as QT interval extraction, activity status categorization, and fall detection algorithms, the system can process data and detect abnormalities in real-time. Results show that the proposed system using Fog services is a promising approach for improving the treatment of diabetic patients with cardiovascular disease