Related papers: Contrastive Learning for Privacy Enhancements in I…
Collaborative inference has recently emerged as an attractive framework for applying deep learning to Internet of Things (IoT) applications by splitting a DNN model into several subpart models among resource-constrained IoT devices and the…
Advancements in wearable medical devices in IoT technology are shaping the modern healthcare system. With the emergence of the Internet of Healthcare Things (IoHT), we are witnessing how efficient healthcare services are provided to…
Distributed optimization and learning has recently garnered great attention due to its wide applications in sensor networks, smart grids, machine learning, and so forth. Despite rapid development, existing distributed optimization and…
Intrusion detection systems are evolving into intelligent systems that perform data analysis searching for anomalies in their environment. The development of deep learning technologies opened the door to build more complex and effective…
With the emergence of smart cities, Internet of Things (IoT) devices as well as deep learning technologies have witnessed an increasing adoption. To support the requirements of such paradigm in terms of memory and computation, joint and…
Contrastive learning has become a leading self- supervised approach to representation learning across domains, including vision, multimodal settings, graphs, and federated learning. However, recent studies have shown that contrastive…
The integration of the Internet of Things (IoT) connects a number of intelligent devices with a minimum of human interference that can interact with one another. IoT is rapidly emerging in the areas of computer science. However, new…
Internet of Things (IoT) is a whole new ecosystem comprised of heterogeneous connected devices -i.e. computers, laptops, smart-phones and tablets as well as embedded devices and sensors-that communicate to deliver capabilities making our…
Recently, the artificial intelligence of things (AIoT) has been gaining increasing attention, with an intriguing vision of providing highly intelligent services through the network connection of things, leading to an advanced AI-driven…
Machine learning models are vulnerable to both security attacks (e.g., adversarial examples) and privacy attacks (e.g., private attribute inference). We take the first step to mitigate both the security and privacy attacks, and maintain…
In recent years, there has been a significant proliferation of industrial Internet of Things (IoT) applications, with a wide variety of use cases being developed and put into operation. As the industrial IoT landscape expands, the…
The proliferation of smart home Internet of Things (IoT) devices presents unprecedented challenges for preserving privacy within the home. In this paper, we demonstrate that a passive network observer (e.g., an Internet service provider)…
Federated Learning (FL) represents a paradigm shift in machine learning, allowing collaborative model training while keeping data localized. This approach is particularly pertinent in the Industrial Internet of Things (IIoT) context, where…
Privacy preserving in machine learning is a crucial issue in industry informatics since data used for training in industries usually contain sensitive information. Existing differentially private machine learning algorithms have not…
In a decentralized Internet of Things (IoT) network, a fusion center receives information from multiple sensors to infer a public hypothesis of interest. To prevent the fusion center from abusing the sensor information, each sensor…
Internet of Things (IoT) is being considered as the growth engine for industrial revolution 4.0. The combination of IoT, cloud computing and healthcare can contribute in ensuring well-being of people. One important challenge of IoT network…
In intelligent industry, autonomous driving and other environments, the Internet of Things (IoT) highly integrated with robotic to form the Internet of Robotic Things (IoRT). However, network intrusion to IoRT can lead to data leakage,…
We consider the future cyber security of industrial control systems. As best as we can see, much of this future unfolds in the context of the Internet of Things (IoT). In fact, we envision that all industrial and infrastructure…
The Internet of Things (IoT) and massive IoT systems are key to sixth-generation (6G) networks due to dense connectivity, ultra-reliability, low latency, and high throughput. Artificial intelligence, including deep learning and machine…
This paper presents a new privacy negotiation mechanism for an IoT environment that is both efficient and practical to cope with the IoT special need of seamlessness. This mechanism allows IoT users to express and enforce their personal…