Trusted Computing Architectures for IoT Devices

The Internet of Things (IoT) which creates a hyper-connected society is playing a major role in the 4th industrial revolution. The IoT is being leveraged across various fields of business globally and the number of IoT devices is causing serious security concerns. Since the firmware update of an IoT device is necessary for its lifecycle, secure firmware update of the IoT device is being brought as the first step in IoT security. The Internet Engineering Task Force (IETF) Software Updates for Internet of Things (SUIT) working group has started to specify a software update architecture for IoT devices. However, the current SUIT working group adopts a traditional client-server model to distribute firmware images, which potentially causes security risks. The current approach of the SUIT working group is unable to solve a targeting issue and an author-disappearing issue, which is suggested in this paper. Therefore, in this work, we introduce a distributed firmware update architecture based on the SUIT firmware update architecture applying blockchain. Our update architecture can prevent the issues we concern through the characteristics of blockchain, such as decentralization, transparency, and irreversibility. The blockchain network has registration nodes that process registration of manifest and firmware image files from authors, and retrieval nodes that process downloading manifest and firmware image files. The firmware image files are stored in a distributed file system and the hash values of firmware image chunks are stored on the blockchain with manifest files. The proposed architecture in this paper enables the irreversible downloads even in the author-disappearing state and tolerant to a single point of failure.

This paper explores the integration of Internet of Things (IoT) devices into modern cybersecurity frameworks, and it is intended to be a binder for the incorporation of these devices into emerging cybersecurity paradigms. Most IoT devices rely on WPA2-personal protocol, a wireless protocol with known security flaws, being effortless to penetrate by using various specific tools. Through this paper, we proposed the use of two Raspberry Pi platforms, with the help of which we created a secure wireless connection by implementing the 802.1X protocol and using digital certificates. Implementing this type of architecture and the devices used, we obtained huge benefits from the point of view of security and energy consumption. We tested multiple authentication methods, including EAP-TLS and EAP-MSCHAPv2, with the Raspberry Pi acting as an authentication server and certificate manager. Performance metrics such as power consumption, latency, and network throughput were analysed, confirming the architecture’s effectiveness and scalability for larger IoT deployments.

With the development of Internet of Things (IoT) technology, the transaction behavior of IoT devices has gradually increased, which also brings the problem of transaction data security and transaction processing efficiency. As one of the research hotspots in the field of data security, blockchain technology has been widely applied in the maintenance of transaction records and the construction of financial payment systems. However, the proportion of microtransactions in the Internet of Things poses challenges to the coupling of blockchain and IoT devices. This paper proposes a three-party scalable architecture based on “IoT device-edge server-blockchain”. In view of the characteristics of micropayment, the verification mechanism of the execution results of the off-chain transaction is designed, and the bridge node is designed in the off-chain architecture, which ensures the finality of the blockchain to the transaction. According to system evaluation, this scalable architecture improves the processing efficiency of micropayments on blockchain, while ensuring its decentration equal to that of blockchain. Compared with other blockchain-based IoT device payment schemes, our architecture is more excellent in activity.

The Internet of Things (IoT) paradigm aims to enhance human society and living standards with the vast deployment of smart and autonomous devices, which requires seamless collaboration. The number of connected devices increases daily, introducing identity management requirements for edge IoT devices. Due to IoT devices' heterogeneity and resource-constrained configuration, traditional identity management systems are not feasible. As a result, identity management for IoT devices is still an open issue. Distributed Ledger Technology (DLT) and blockchain-based security solutions are becoming popular in different application domains. This paper presents a novel DLT-based distributed identity management architecture for edge IoT devices. The model can be adapted with any IoT solution for secure and trustworthy communication between devices. We have comprehensively reviewed popular consensus mechanisms used in DLT implementations and their connection to IoT research, specifically identity management for Edge IoT devices. Our proposed location-based identity management model is generic, distributed, and decentralized. The proposed model is verified using the Scyther formal verification tool for security performance measurement. SPIN model checker is employed for different state verification of our proposed model. The open-source simulation tool FobSim is used for fog and edge/user layer DTL deployment performance analysis. The results and discussion section represents how our proposed decentralized identity management solution should enhance user data privacy and secure and trustworthy communication in IoT.

Internet-of-Things IoT devices are increasingly targeted Uy adversaries due to their unique characteristics such as constant online connection, lack of protection, and full integration in people’s daily life. As attackers shift their targets towards IoT devices, malware has been developed to compromise IoT devices equipped with different CPU architectures. While malware detection has been a well-studied area for desktop PCs, heterogeneous processor architecture in IoT devices brings in unique challenges. Existing approaches utilize static or dynamic binary analysis for identifying malware characteristics, Uut they all fall short when dealing with IoT malware compiled for different architectures. In this paper, we propose an efficient signature generation method for IoT malware, which generates distinguishable signatures based on high-level structural, statistical and string feature vectors, as high-level features are more robust against code variations across different architectures. The generated signatures for each malware family can be used for developing lightweight malware detection tools to secure IoT devices. Extensive experiments with two datasets of 5,150 recent IoT malware samples show that our scheme can achieve 95.5% detection rate with 0% false positive rate. Moreover, the proposed scheme can achieve 85.2% detection rate in detecting novel IoT malware.

The difficulty of further downscaling CMOS technology arises from the restriction of feature size reduction. Quantum-dot cellular automata (QCA) emerges as a paradigm-shifting successor to CMOS, heralding a new era of effective digital design at the nanoscale. It stands as an enticing frontier in nanoscale computing, with limited exploration into the realms of smaller QCA cells, elevated processing speeds, and more compact area requirements across diverse circuits. Within the intricate landscape of decoding circuits and process controllers, the binary comparator assumes a role of paramount significance. On the other hand, the quickly developing Internet of Things (IoT) market aims to produce high-speed, low-power gadgets. A comparator is a crucial component in the analog-to-digital conversion process used by IoT devices. In order to meet the power and latency requirements of IoT devices, a high-speed, low-power comparator is greatly required. Consequently, the strategic design of comparators within the QCA framework has ascended to a position of heightened importance in cutting-edge research. This study undertakes the formidable task of conceiving QCA-centric designs for MV32, the majority gate, and the inverter gate, thereby contributing to the development of a sophisticated multi-layered comparator architecture for IoT devices. In the realization of a three-layer comparator implemented in QCA, we attain an impressive feat—a minimal clock zone demanding only a singular clock pulse coupled with exceptional compaction (measuring at a mere 0.03 μm2). Experimental revelations corroborate the substantial advancement of the proposed design over traditional methodologies, particularly in terms of circuit area, cell count, and clock efficiency.

The Internet of Things (IoT) contributes to the advancement and optimization of systems in different contexts by reducing human effort, cost, and time. It is estimated that by 2020 there will be more than 20 billion connected IoT devices. Though justified by emerging IoT applications, such growth requires the implementation of more robust, and consequently, more complex IoT systems. Hence, the optimization of IoT hardware and software design is fundamental towards achieving scalability. It allows for the control and capture of increased data from more connected devices. For this purpose, this work analyzes and compares the scalability of three architectures for IoT devices abstraction of IoT management platforms, and for this, two experiments were carried out. The results show that the Architecture NxN has made better use of computing resources, obtained the average latency value close to zero and connected 100,000 physical emulated devices. Also, being the most optimized architecture for IoT device abstraction of IoT management platforms, in the context of big data, it works in real time.

Wearable and Internet of Things (IoT) devices have the potential to improve lifestyle, personalize receiving treatments or introduce assisted living for elderly people. However, service delivery depends on maintaining and troubleshooting device connectivity to smartphones, where user engagement and technology proficiency represent a possible barrier that prevents a wider adoption, especially in the elderly and disabled population. Low-cost and low-power wearable and IoT devices face challenges when operating out of range of known home networks or pared devices. We propose an architecture and methods to provide seamless connectivity (Se-Co) between devices and wireless networks while maintaining low-power, low-cost and standards compatibility. Through Se-Co, the devices connect without user interaction both in home and in unknown roaming networks while maintaining anonymity, privacy and security. Roaming networks approve data limited connectivity to unknown devices that are able to provide a valid anonymized certificate of compliance and no harm through a home provider. Se-Co enables shifting data processing, such as pattern processing using artificial intelligence, from a wearable device or smartphone towards the cloud. The proposed Se-Co architecture could provide solutions to increase usability of wearable devices and improve their wider adoption, while keeping low the costs of devices, development and services.

As the number of IoT devices increases, sustainability is becoming a bottleneck of the production process in industrial systems. As a matter of fact, inefficient management and scarce resources significantly impeded the development of sustainability. In recent years, it has been observed that the digital twin (DT) technology plays a promising role in facilitating the interaction between the Internet of Things (IoT) assets and digital services. However, high-fidelity models of DTs raise the requirement of efficient data flows, which is limited by realistic constraints, such as data collection strategy and energy supply. We propose a sustainable data collection and management approach to construct DTs for physical assets. With this approach, data packets are uploaded to the data brokers, namely, agents, by a large number of IoT devices. The challenge lies in the balance between enduring data collection and the information loss associated with the stale data. In this article, we aim to optimize the metrics of data fidelity and reveal delay while guaranteeing both sustainable energy and sustainable information. Additionally, a shareable and sustainable blockchain-based DT management architecture is proposed, which does not rely on data exchanges with a single centralized server. Our analytical and simulation results demonstrate the applicability of our proposed architecture.

Versatile Internet of Things (IoT) applications call for re-configurable IoT devices that can easily extend new functionality on demand. However, the heterogeneity of functional chips brings difficulties in device customization, leading to inadequate flexibility. In this paper, we propose LEGO, a novel architecture for chip-level re-configurable IoT devices that supports plug-and-play with Commercial Off-The-Shelf (COTS) chips. To combat the heterogeneity of functional chips, we first design a novel Unified Chip Description Language (UCDL) with meta-operation and chip specifications to access various types of functional chips uniformly. Then, to achieve chips plug-and-play, we build up a novel platform and shift all chip control logic to the gateway, which makes IoT devices entirely decoupled from specific applications and does not need to make any changes when plugging in new functional chips. Finally, to handle communications overheads, we built up a novel orchestration architecture for gateway instructions, which minimizes instruction transmission frequency in remote chip control. We implement the prototype and conduct extensive evaluations with 100+ types of COTS functional chips. The results show that new functional chips can be automatically accessed by the system within 0.13 seconds after being plugged in, and only bringing 0.53 kb of communication load on average, demonstrating the efficacy of LEGO design.

The author considers the question of the effect of VLSI on computer architecture. This question can be interpreted in two ways. The first is the effect of VLSI on the science (ART.) of computer architecture. The second is the effect of VLSI on the architecture of computers and digital devices. In this paper, the author considers the second interpretation. 14 references.

The Internet of Things (IoT) is generally acknowledged as a dramatic change spearheaded by scientists and business executives. The IoT has the potential to improve our daily lives by connecting smart devices to the internet. Due to the limited resources and distant deployment of these IoT devices, securing them is a significant challenge today. This paper focuses primarily on mitigating threats and attacks on realistic artificial intelligence, such as network architecture for smart devices. The text on mitigating attacks in networks, especially those involving mobile nodes, is discussed. We develop and test a new countermeasure against all mitigated attack variants. The proposed approach combines node location and trust-based parent selection. The result demonstrates the viability of the suggested countermeasure. In addition, demonstrating the superiority of the suggested countermeasure involves considering the precision of detecting the attack and the delay in isolating the attacker.

The exponential growth of the Internet of Things (IoT) has introduced considerable security and forensic challenges due to the rising complexity and heterogeneity of connected devices. As the adoption of the Internet of Things (IoT) continues to expand, so too do the vulnerabilities inherent to this technology, with threats ranging from the exploitation of individual devices to large-scale breaches of network security. It is imperative that IoT security frameworks undergo continuous evolution to address weaknesses in cryptography, authentication, and communication protocols. Concurrently, the field of IoT forensics encounters obstacles in the gathering and analysis of evidence due to the restricted memory and heterogeneous architectures of IoT devices. This chapter examines the critical aspects of IoT security, highlighting prevalent attacks, mitigation techniques, and the forensic methodologies employed to investigate compromised devices. Particular attention is given to the role of device heterogeneity, emerging forensic tools, and the impact of artificial intelligence on both security and forensic efforts. The discussion underscores the necessity for ongoing advancements to create a resilient IoT ecosystem capable of mitigating threats and enhancing forensic investigations.

Recent advancements in energy-harvesting techniques provide an alternative to batteries for resource-constrained IoT devices and lead to a new computing paradigm, the intermittent computing model. In this model, a software module continues its execution from where it left off when an energy shortage occurred. Enforcing security of an intermittent software module is challenging because its power-off state has to be protected from a malicious adversary in addition to its power-on state, while the security mechanisms put in place must have a low overhead on the performance, resource consumption, and cost of a device.In this paper, we propose SIA (Secure Intermittent Architecture), a security architecture for resource-constrained IoT devices. SIA leverages low-cost security features available in commercial off-the-shelf microcontrollers to protect both the power-on and power-off state of an intermittent software module. Therefore, SIA enables a host of secure intermittent computing applications such as self-attestation, remote attestation, and secure communication. Moreover, our architecture provides confidentiality and integrity guarantees to an intermittent computing module at no cost compared to previous approaches in the literature that impose significant overheads. The salient characteristic of SIA is that it does not require any hardware modifications, and hence, it can be directly applied to existing IoT devices.We implemented and evaluated SIA on a resource-constrained IoT device based on an MSP430 processor. Besides being secure, SIA is simple and efficient. We confirm the feasibility of SIA for resource-constrained IoT devices with experimental results of several intermittent computing applications. Our prototype implementation outperforms by two to three orders of magnitude the secure intermittent computing solution of Suslowicz et al. presented at IGSC 2018.

A Study on Routing-based Mobile Architecture for IoT devices in Cellular Networks