Related papers: Anomalous Communications Detection in IoT Networks…
The amount of connected devices in the industrial environment is growing continuously, due to the ongoing demands of new features like predictive maintenance. New business models require more data, collected by IIoT edge node sensors based…
The Internet of Things (IoT) presents a unique cybersecurity challenge due to its vast network of interconnected, resource-constrained devices. These vulnerabilities not only threaten data integrity but also the overall functionality of IoT…
The fundamental communication problem in the wireless Internet of Things (IoT) is to discover a massive number of devices and to allow them reliable access to shared channels. Oftentimes these devices transmit short messages randomly and…
Securing the Internet of Things (IoT) is a necessary milestone toward expediting the deployment of its applications and services. In particular, the functionality of the IoT devices is extremely dependent on the reliability of their message…
The widespread integration of IoT devices has greatly improved connectivity and computational capabilities, facilitating seamless communication across networks. Despite their global deployment, IoT devices are frequently targeted for…
The integration of IoT devices in healthcare introduces significant security and reliability challenges, increasing susceptibility to cyber threats and operational anomalies. This study proposes a machine learning-driven framework for (1)…
Many IoT devices are vulnerable to attacks due to flawed security designs and lacking mechanisms for firmware updates or patches to eliminate the security vulnerabilities. Device-type identification combined with data from vulnerability…
The Internet of Things(IoT) paradigm provides persistent sensing and data collection capabilities and is becoming increasingly prevalent across many market sectors. However, most IoT devices emphasize usability and function over security,…
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 increasing popularity of specialized Internet-connected devices and appliances, dubbed the Internet-of-Things (IoT), promises both new conveniences and new privacy concerns. Unlike traditional web browsers, many IoT devices have…
Digitalization leads to data transparency for production systems that we can benefit from with data-driven analysis methods like neural networks. For example, automated anomaly detection enables saving resources and optimizing the…
In order to detect unknown intrusions and runtime errors of computer programs, the cyber-security community has developed various detection techniques. Anomaly detection is an approach that is designed to profile the normal runtime behavior…
Current IoT networks are characterized by an ultra-high density of devices with different energy budget constraints, typically having sparse and sporadic activity patterns. Access points require an efficient strategy to identify the active…
In recent years, networked IoT systems have revolutionized connectivity, portability, and functionality, offering a myriad of advantages. However, these systems are increasingly targeted by adversaries due to inherent security…
Intrusion detection has become one of the most critical tasks in a wireless network to prevent service outages that can take long to fix. The sheer variety of anomalous events necessitates adopting cognitive anomaly detection methods…
The Internet of Things (IoT) has revolutionized connectivity by linking billions of devices worldwide. However, this rapid expansion has also introduced severe security vulnerabilities, making IoT devices attractive targets for malware such…
Consumer Internet of Things (IoT) devices are extremely popular, providing users with rich and diverse functionalities, from voice assistants to home appliances. These functionalities often come with significant privacy and security risks,…
With the rapid growth of the Internet-of-Things (IoT), concerns about the security of IoT devices have become prominent. Several vendors are producing IP-connected devices for home and small office networks that often suffer from flawed…
The generalization of deep learning has helped us, in the past, address challenges such as malware identification and anomaly detection in the network security domain. However, as effective as it is, scarcity of memory and processing power…
Massive device connectivity is a crucial communication challenge for Internet of Things (IoT) networks, which consist of a large number of devices with sporadic traffic. In each coherence block, the serving base station needs to identify…