Related papers: Classification of Encrypted IoT Traffic Despite Pa…
The rapid growth of Internet of Things (IoT) devices has introduced significant challenges to privacy, particularly as network traffic analysis techniques evolve. While encryption protects data content, traffic attributes such as packet…
Despite encryption, the packet size is still visible, enabling observers to infer private information in the Internet of Things (IoT) environment (e.g., IoT device identification). Packet padding obfuscates packet-length characteristics…
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)…
The growing market for smart home IoT devices promises new conveniences for consumers while presenting new challenges for preserving privacy within the home. Many smart home devices have always-on sensors that capture users' offline…
The rapid proliferation of Internet of Things (IoT) devices introduces significant security challenges due to limited visibility and weak device-level guarantees. Accurate and timely identification of devices is essential for enforcing…
Internet of Things (IoT) is one of the technological advancements of the twenty-first century which can improve living standards. However, it also imposes new types of security challenges, including device authentication, traffic types…
The Internet traffic data produced by the Internet of Things (IoT) devices are collected by Internet Service Providers (ISPs) and device manufacturers, and often shared with their third parties to maintain and enhance user services.…
The various types of communication technologies and mobility features in Internet of Things (IoT) on the one hand enable fruitful and attractive applications, but on the other hand facilitates malware propagation, thereby raising new…
Device fingerprinting can be used by Internet Service Providers (ISPs) to identify vulnerable IoT devices for early prevention of threats. However, due to the wide deployment of middleboxes in ISP networks, some important data, e.g.,…
Matter is the most recent application-layer standard for the Internet of Things (IoT). As one of its major selling points, Matter's design imposes particular attention to security and privacy: it provides validated secure session…
Machine learning models have demonstrated strong performance in classifying network traffic and identifying Internet-of-Things (IoT) devices, enabling operators to discover and manage IoT assets at scale. However, many existing approaches…
The growing popularity of Internet-of-Things (IoT) has created the need for network-based traffic anomaly detection systems that could identify misbehaving devices. In this work, we propose a lightweight technique, IoT-guard, for…
The rapid expansion of internet of things (IoT) devices has created a pervasive ecosystem where encrypted wireless communications serve as the primary privacy and security protection mechanism. While encryption effectively protects message…
The rapid increase in the use of IoT devices brings many benefits to the digital society, ranging from improved efficiency to higher productivity. However, the limited resources and the open nature of these devices make them vulnerable to…
Device identification is the process of identifying a device on Internet without using its assigned network or other credentials. The sharp rise of usage in Internet of Things (IoT) devices has imposed new challenges in device…
The IoT (Internet of Things) technology has been widely adopted in recent years and has profoundly changed the people's daily lives. However, in the meantime, such a fast-growing technology has also introduced new privacy issues, which need…
Online anonymity and privacy has been based on confusing the adversary by creating indistinguishable network elements. Tor is the largest and most widely deployed anonymity system, designed against realistic modern adversaries. Recently,…
The machine learning approach is vital in Internet of Things (IoT) malware traffic detection due to its ability to keep pace with the ever-evolving nature of malware. Machine learning algorithms can quickly and accurately analyze the vast…
The number and variety of Internet-connected devices have grown enormously in the past few years, presenting new challenges to security and privacy. Research has shown that network adversaries can use traffic rate metadata from consumer IoT…
A myriad of IoT devices such as bulbs, switches, speakers in a smart home environment allow users to easily control the physical world around them and facilitate their living styles through the sensors already embedded in these devices.…