Related papers: Anomaly Detection and Modeling in 802.11 Wireless …

Cross Technology Interference (CTI) is a prevalent phenomenon in the 2.4 GHz unlicensed spectrum causing packet losses and increased channel contention. In particular, WiFi interference is a severe problem for low-power wireless networks as…

The paper investigates the problems of quickest change detection in Markov models and hidden Markov models (HMMs). Sequential observations are taken from a (hidden) Markov model. At some unknown time, an event occurs in the system and…

With the increasing volume of streaming data in industrial systems, online anomaly detection has become a critical task. The diverse and rapidly evolving data patterns pose significant challenges for online anomaly detection. Many existing…

We develop a supervised machine learning model that detects anomalies in systems in real time. Our model processes unbounded streams of data into time series which then form the basis of a low-latency anomaly detection model. Moreover, we…

Mobile ad hoc networking (MANET) has become an exciting and important technology in recent years because of the rapid proliferation of wireless devices. MANETs are highly vulnerable to attacks due to the open medium, dynamically changing…

Most anomaly detection systems try to model normal behavior and assume anomalies deviate from it in diverse manners. However, there may be patterns in the anomalies as well. Ideally, an anomaly detection system can exploit patterns in both…

One of the main challenges when designing a new self-powered wireless sensor network (WSN) technology is the vast operational dependence on its scarce energy resources. Therefore, a thorough identification and characterisation of the main…

Deviations from expected behavior during runtime, known as anomalies, have become more common due to the systems' complexity, especially for microservices. Consequently, analyzing runtime monitoring data, such as logs, traces for…

The aim of the present work is to provide the theoretical fundamentals needed to monitor power grids using high frequency sensors. In our context, network monitoring refers to the harvesting of different kinds of information: topology of…

With the increasing availability of flexible wireless 802.11 devices, the potential exists for users to selfishly manipulate their channel access parameters and gain a performance advantage. Such practices can have a severe negative impact…

We apply several machine learning algorithms to the problem of anomaly detection in operational data for large-scale, high-voltage electric power grids. We observe important differences in the performance of the algorithms. Neural networks…

Anomaly detection methods are part of the systems where rare events may endanger an operation's profitability, safety, and environmental aspects. Although many state-of-the-art anomaly detection methods were developed to date, their…

Due to the recent increase in the number of connected devices, the need to promptly detect security issues is emerging. Moreover, the high number of communication flows creates the necessity of processing huge amounts of data. Furthermore,…

Detecting anomalies on network traffic is a complex task due to the massive amount of traffic flows in today's networks, as well as the highly-dynamic nature of traffic over time. In this paper, we propose the use of Graph Neural Networks…

Focusing on the increasing market of the sensors and actuators networks, the IEEE 802.11ah Task Group is currently working on the standardization of a new amendment. This new amendment will operate at the sub-1GHz band, ensure transmission…

The rapidly evolving cloud platforms and the escalating complexity of network traffic demand proper network traffic monitoring and anomaly detection to ensure network security and performance. This paper introduces a large language model…

WiFi was designed just to replace the wired connections, but it has changed the Internet as a whole. WiFi users are increasing day by day and the traffic from wireless devices is dominating the Internet. With an increasing number of users…

Time-series anomaly detection, which detects errors and failures in a workflow, is one of the most important topics in real-world applications. The purpose of time-series anomaly detection is to reduce potential damages or losses. However,…

EEE 802.11ah is a novel WiFi-based protocol, aiming to provide an access solution for the machine-to-machine (M2M) communications. In this paper, we propose an adaptive access mechanism that can be seamlessly incorporated into IEEE 802.11ah…

The identification of anomalies is a critical component of operating complex, and possibly large-scale and geo-graphically distributed cyber-physical systems. While designing anomaly detectors, it is common to assume Gaussian noise models…