In the rapidly evolving landscape of the IoT, the security of connected devices has become a paramount concern. This paper explores the concept of proactive threat hunting as a pivotal strategy for enhancing the security and sustainability of IoT systems. Proactive threat hunting is an alternative to traditional reactive security measures that analyses IoT networks continuously and in advance to find and eliminate threats before they occure. By improving the security posture of IoT devices this approach significantly contributes to extending IoT operational lifespan and reduces environmental impact. By integrating security metrics similar to the Common Vulnerability Scoring System (CVSS) into consumer platforms, this paper argues that proactive threat hunting can elevate user awareness about the security of IoT devices. This has the potential to impact consumer choices and encourage a security-conscious mindset in both the manufacturing and user communities. Through a comprehensive analysis, this study demonstrates how proactive threat hunting can contribute to the development of a more secure, sustainable, and user-aware IoT ecosystem.

In an era dominated by the Internet of Things, ensuring the longevity and sustainability of IoT devices has emerged as a pressing concern. This study explores the various complex difficulties which contributed to the early decommissioning of IoT devices and suggests methods to improve their lifespan management. By examining factors such as security vulnerabilities, user awareness gaps, and the influence of fashion-driven technology trends, the paper underscores the need for legislative interventions, consumer education, and industry accountability. Additionally, it explores innovative approaches to improving IoT longevity, including the integration of sustainability considerations into architectural design through requirements engineering methodologies. Furthermore, the paper discusses the potential of distributed ledger technology, or blockchain, to promote transparent and decentralized processes for device provisioning and tracking. This study promotes a sustainable IoT ecosystem by integrating technology innovation, legal change, and social awareness to reduce environmental impact and enhance resilience for the digital future

In an era where the Internet of Things (IoT) intersects increasingly with generative Artificial Intelligence (AI), this article scrutinizes the emergent security risks inherent in this integration. We explore how generative AI drives innovation in IoT and we analyze the potential for data breaches when using generative AI and the misuse of generative AI technologies in IoT ecosystems. These risks not only threaten the privacy and efficiency of IoT systems but also pose broader implications for trust and safety in AI-driven environments. The discussion in this article extends to strategic approaches for mitigating these risks, including the development of robust security protocols, the multi-layered security approaches, and the adoption of AI technological solutions. Through a comprehensive analysis, this article aims to shed light on the critical balance between embracing AI advancements and ensuring stringent security in IoT, providing insights into the future direction of these intertwined technologies.

The internet of things (IoT) is a huge market, with a forecast of 23.6 billion connections by 2026, according to ABI Research. This growth entails a wide range of devices and applications, opening up opportunities for different wireless connectivity technologies, improved security, and enhanced features with artificial intelligence. This month's issue covers all of it: wireless technologies, security, and AI in IoT. The Eclipse Foundation's 2021 IoT & Edge Developer survey revealed that the top three concerns of IoT developers are security, connectivity, and deployment. The significant increase in both security and connectivity concerns highlights the challenges that developers face in determining the right technologies for their applications, according to the report.

An IoT ecosystem is dependent on its building blocks to ensure round-the-clock functionality. IoT architecture is responsible for rounding up these different layers of devices, communication protocols, and the cloud, among other factors. In this article, we will examine the concept of IoT architecture more meticulously, differentiate between IoT ecosystem and IoT architecture, demonstrate its ten different components, and finally provide an example to give more context. IoT architecture comprises several IoT building blocks connected to ensure that sensor-generated data is collected, transferred, stored, and processed in order for the actuators to perform their designated tasks. IoT ecosystem is the encompassing term attributed to the five general components of devices, communication protocols, the cloud, monitoring, and the end-user in the IoT system. IoT architecture is the meticulous breakdown of how exactly the aforementioned building blocks function to make the system work.

This work explores the evaluation of a machine learning anomaly detector using custom-made parameterizable malware in an Internet of Things (IoT) Ecosystem. It is assumed that the malware has infected, and resides on, the Linux router that serves other devices on the network, as depicted in Figure 1. This IoT Ecosystem was developed as a testbed to evaluate the efficacy of a behavior-based anomaly detector. The malware consists of three types of custom-made malware: ransomware, cryptominer, and keylogger, which all have exfiltration capabilities to the network. The parameterization of the malware gives the malware samples multiple degrees of freedom, specifically relating to the rate and size of data exfiltration. The anomaly detector uses feature sets crafted from system calls and network traffic, and uses a Support Vector Machine (SVM) for behavioral-based anomaly detection. The custom-made malware is used to evaluate the situations where the SVM is effective, as well as the situations where it is not effective.

While digital transformation has remained a focus for industries all over the world for a long time now, the Covid-19 pandemic has brought it into the limelight again. In fact, reimagining a tech-enabled future using technologies like artificial intelligence (AI) and Internet of Things ( IoT) devices will be beneficial and equally challenging for all businesses. Because people are now depending upon tech companies for most aspects of their everyday life -- from checking their fitness levels and procuring education to managing huge monetary funds and data -- business leaders must realize that just one leakcould cause their companies to lose millions of dollars and see a huge dent in their integrity and reputation. An increasing number of people are working remotely, and cloud collaboration has almost become the norm, so companies will have to get even more vigilant when it comes to securing crucial data spread across thousands of devices unrestricted by geographic locations. As of late, IoT and AI have been used together in a new piece of jargon.

IoT is drastically changing the world for the better. There was a time when internet connectivity was available only on phones and computers. In the past decade, this focus has shifted to all technologies. Gradually, we are seeing the development of devices that connect to the internet. All these devices collect and share data to make our lives easier. You must know what IoT is by now, but for general understanding IoT is a broad umbrella.

AIoT is the major emerging trend from the survey, demonstrating the beginning of the process to build a true IoT ecosystem. Research showed that almost half (49%) of respondents already use AI in their IoT applications, with Machine Learning (ML) the most used technology (28%) followed by cloud-based AI (19%). This adoption of AI within IoT design is coupled with a growing confidence to take the lead on IoT development and an increasing number of respondents seeing themselves as innovators. However, it is still evident that some engineers (51%) are hesitant to adopt AI due to being new to the technology or because they require specialized expertise in how to implement AI in IoT applications. Other results from element14's second Global IoT Survey show that security continues to be the biggest concern designers consider in IoT implementation.

As the internet evolves, what will be the impact of the convergence of the current IoT infrastructure with blockchain and artificial intelligence? The internet is evolving beyond its technical infrastructure. As we move towards creating an integrated cyberspace, aquaspace, geospace and space (CAGS) internet of everything (IoE) ecosystem that benefits from the fast-tracking technology, application trend paradigm shifts, and convergence beyond blockchain and artificial intelligence, it raises more questions than answers. The reason behind that is the existing and emerging technologies that have created the internet of things (IoT) are not changing just the internet, but they are instead altering the very things connected to the internet: the devices, sensors, and gateways on the edge of the distributed network that can request a service or start an action without human intervention. As a result, the evolution of the internet is happening at many levels considering artificial intelligence (AI) can now take the petabytes of data they have from a distributed network and extract meaningful information from it.