ASSERT: A Blockchain-Based Architectural Approach for Engineering Secure Self-Adaptive IoT Systems

Abstract

Internet of Things (IoT) systems are complex systems that can manage mission-critical, costly operations or the collection, storage, and processing of sensitive data. Therefore, security represents a primary concern that should be considered when engineering IoT systems. Additionally, several challenges need to be addressed, including the following ones. IoT systems’ environments are dynamic and uncertain. For instance, IoT devices can be mobile or might run out of batteries, so they can become suddenly unavailable. To cope with such environments, IoT systems can be engineered as goal-driven and self-adaptive systems. A goal-driven IoT system is composed of a dynamic set of IoT devices and services that temporarily connect and cooperate to achieve a specific goal. Several approaches have been proposed to engineer goal-driven and self-adaptive IoT systems. However, none of the existing approaches enable goal-driven IoT systems to automatically detect security threats and autonomously adapt to mitigate them. Toward bridging these gaps, this paper proposes a distributed architectural Approach for engineering goal-driven IoT Systems that can autonomously SElf-adapt to secuRity Threats in their environments (ASSERT). ASSERT exploits techniques and adopts notions, such as agents, federated learning, feedback loops, and blockchain, for maintaining the systems’ security and enhancing the trustworthiness of the adaptations they perform. The results of the experiments that we conducted to validate the approach’s feasibility show that it performs and scales well when detecting security threats, performing autonomous security adaptations to mitigate the threats and enabling systems’ constituents to learn about security threats in their environments collaboratively.

ART4FL: An Agent-Based Architectural Approach for Trustworthy Federated Learning in the IoT

“…Several (open-source) FL frameworks have been developed [14]. TensorFlow FL (TFF) 1 is a client-server based framework that supports the simulation of distributed training of FL models but runs only on a single machine. FATE 2 is another framework that adopts a distributed client-server architecture that can be deployed over a Kubernetes cluster.…”

“…This component registers agents in the blockchain network. As blockchain networks have performance and scalability issues when deployed in fully decentralized settings or when having a large number of nodes (i.e., agents) [1], [11], this component maintains updated clones of agents' profles in its knowledge base for performance purposes.…”

“…Therefore, the trade-offs between qualities (e.g., performance, security, and trustworthiness) should be considered when refning the ART4FL architecture. Further, in large-scale FL, maintaining knowledge about agents and their commitments in the blockchain can lead to scalability issues [1]. To address this problem, the knowledge can be automatically cloned from the blockchain and stored in an external knowledge base (e.g., a NoSQL database), which is used as the main knowledge provider to the other components.…”

Data Quality in Human-Centric Sensing-Based Next-Generation IoT Systems: A Comprehensive Survey of Models, Issues, and Challenges

“…Specifically, smart contracts, as immutable codes, can permit and establish trusted transactions to be carried out among Requestors and Workers without the need for explicit trust connections with each other. A smart contract authenticates users and enables secure data sharing between them [141]. Moreover, there is no way to modify or alter the data in any block of information; data provided by a device can be identified, constituting data more accurate, reliable and transparent to store in a blockchain.…”

Enhanced Homomorphic Encryption and Dual Blockchain Authentication for Securing Medical Data on the Internet of Things

“…Additionally, the proposed solution uses blockchain to isolate the IP addresses of real devices, while earlier research has scalability problems [11] since it stores all data, harmful or not. In addition, in contrast to other study studies that have just employed blockchain technology as a record-keeping system, our proposed technique leverages blockchain approach as a first step to validate and verify IoT devices [12,13]. Furthermore, the verification process is not discussed in depth in the research; yet, this architecture defines and almost executes the communication and authentication methods.…”