Over the last few decades, sustainable computing has been widely used in areas like social computing, artificial intelligence-based agent systems, mobile computing, and Internet of Things (IoT). There are social, economic, and commercial impacts of IoT on human lives. However, IoT nodes are generally power-constrained with data transmission using an open channel, i.e., Internet which opens the gates for various types of attacks on them. In this context, several efforts are initiated to deal with the evolving security issues in IoT systems and make them self-sufficient to harvest energy for smooth functioning. Motivated by these facts, in this paper, we explore the evolving vulnerabilities in IoT devices. We provide a state-of-the-art survey that addresses multiple dimensions of the IoT realm. Moreover, we provide a general overview of IoT, Sustainable IoT, its architecture, and the Internet Engineering Task Force (IETF) protocol suite. Subsequently, we explore the open-source tools and datasets for the proliferation in research and growth of IoT. A detailed taxonomy of attacks associated with various vulnerabilities is also presented in the text. Then we have specifically focused on the IoT Vulnerability Assessment techniques followed by a case study on sustainability of Smart Agriculture. Finally, this paper outlines the emerging challenges related to IoT and its sustainability, and opening the doors for the beginners to start research in this promising area.
The lifetime of a node in wireless sensor networks (WSN) is directly responsible for the longevity of the wireless network. The routing of packets is the most energy-consuming activity for a sensor node. Thus, finding an energy-efficient routing strategy for transmission of packets becomes of utmost importance. The opportunistic routing (OR) protocol is one of the new routing protocol that promises reliability and energy efficiency during transmission of packets in wireless sensor networks (WSN). In this paper, we propose an intelligent opportunistic routing protocol (IOP) using a machine learning technique, to select a relay node from the list of potential forwarder nodes to achieve energy efficiency and reliability in the network. The proposed approach might have applications including e-healthcare services. As the proposed method might achieve reliability in the network because it can connect several healthcare network devices in a better way and good healthcare services might be offered. In addition to this, the proposed method saves energy, therefore, it helps the remote patient to connect with healthcare services for a longer duration with the integration of IoT services.
In recent years, people have witnessed numerous Internet of Things (IoT)-based attacks with the exponential increase in the number of IoT devices. Alongside this, the means to secure IoT-based applications are maturing slower than our budding dependence on them. Moreover, the vulnerabilities in an IoT system are exploited in chains to penetrate deep into the network and yield more adverse aftereffects. To mitigate these issues, this paper gives unique insights for handling the growing vulnerabilities in common IoT devices and proposes a threat architecture for IoT, addressing threats in the context of a three-layer IoT reference architecture. Furthermore, the vulnerabilities exploited at the several IoT attack surfaces and the challenges they exert are explored. Thereafter, the challenges in quantifying the IoT vulnerabilities with the existing framework are also analyzed. The study also covers a case study on the Intelligent Transportation System, covering road transport and traffic control specifically in terms of threats and vulnerabilities. Another case study on secure energy management in the Smart Grid is also presented. This case study covers the applications of Internet of Vulnerable Things (IoVT) in Smart energy Grid solutions, as there will be tremendous use of IoT in future Smart Grids to save energy and improve overall distribution. The analysis shows that the integration of the proposed architecture in existing applications alarms the developers about the embedded threats in the system.
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