Smart Anomaly Detection for Sensor Systems PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Smart Anomaly Detection for Sensor Systems PDF full book. Access full book title Smart Anomaly Detection for Sensor Systems by Antonio Liotta. Download full books in PDF and EPUB format.
Author: Antonio Liotta
Publisher: Springer
ISBN: 9783319001630
Category : Technology & Engineering
Languages : en
Pages : 0
Get Book Here
Book Description
Like in the ecosystems of Nature, raw sensing is of little use unless we are also able to form higher-level interpretations of the collected data. How can we assess whether the sensed data is accurate? How can we tell whether a peculiar set of data arises from genuine conditions or is due to a faulty set of sensors? What is the normal operating condition of a digital sensor system? When is a deviation from normality to be interpreted as anomaly? This book explores the emerging area of sensor systems and applications from the particular perspective of anomaly detection. It gives the reader a head start on methods applicable to embedded sensor systems, showing the benefits of a range of computational approaches. After pinpointing the limitations of ‘deterministic’ anomaly detection, it becomes clear why the more promising approaches are those based on computational intelligence. The reader of this book will gain an in-depth understanding of anomaly detection in complex and unpredictable sensor systems, familiarizing with the most suitable machine learning techniques.
Author: Antonio Liotta
Publisher: Springer
ISBN: 9783319001630
Category : Technology & Engineering
Languages : en
Pages : 0
Get Book Here
Book Description
Like in the ecosystems of Nature, raw sensing is of little use unless we are also able to form higher-level interpretations of the collected data. How can we assess whether the sensed data is accurate? How can we tell whether a peculiar set of data arises from genuine conditions or is due to a faulty set of sensors? What is the normal operating condition of a digital sensor system? When is a deviation from normality to be interpreted as anomaly? This book explores the emerging area of sensor systems and applications from the particular perspective of anomaly detection. It gives the reader a head start on methods applicable to embedded sensor systems, showing the benefits of a range of computational approaches. After pinpointing the limitations of ‘deterministic’ anomaly detection, it becomes clear why the more promising approaches are those based on computational intelligence. The reader of this book will gain an in-depth understanding of anomaly detection in complex and unpredictable sensor systems, familiarizing with the most suitable machine learning techniques.
Author: Muhammad Usman
Publisher: Springer
ISBN: 9811074674
Category : Computers
Languages : en
Pages : 154
Get Book Here
Book Description
This book presents the latest developments regarding a detailed mobile agent-enabled anomaly detection and verification system for resource constrained sensor networks; a number of algorithms on multi-aspect anomaly detection in sensor networks; several algorithms on mobile agent transmission optimization in resource constrained sensor networks; an algorithm on mobile agent-enabled in situ verification of anomalous sensor nodes; a detailed Petri Net-based formal modeling and analysis of the proposed system, and an algorithm on fuzzy logic-based cross-layer anomaly detection and mobile agent transmission optimization. As such, it offers a comprehensive text for interested readers from academia and industry alike.
Author: V. Çağrı Güngör
Publisher: CRC Press
ISBN: 1466500522
Category : Computers
Languages : en
Pages : 406
Get Book Here
Book Description
The collaborative nature of industrial wireless sensor networks (IWSNs) brings several advantages over traditional wired industrial monitoring and control systems, including self-organization, rapid deployment, flexibility, and inherent intelligent processing. In this regard, IWSNs play a vital role in creating more reliable, efficient, and productive industrial systems, thus improving companies’ competitiveness in the marketplace. Industrial Wireless Sensor Networks: Applications, Protocols, and Standards examines the current state of the art in industrial wireless sensor networks and outlines future directions for research. What Are the Main Challenges in Developing IWSN Systems? Featuring contributions by researchers around the world, this book explores the software and hardware platforms, protocols, and standards that are needed to address the unique challenges posed by IWSN systems. It offers an in-depth review of emerging and already deployed IWSN applications and technologies, and outlines technical issues and design objectives. In particular, the book covers radio technologies, energy harvesting techniques, and network and resource management. It also discusses issues critical to industrial applications, such as latency, fault tolerance, synchronization, real-time constraints, network security, and cross-layer design. A chapter on standards highlights the need for specific wireless communication standards for industrial applications. A Starting Point for Further Research Delving into wireless sensor networks from an industrial perspective, this comprehensive work provides readers with a better understanding of the potential advantages and research challenges of IWSN applications. A contemporary reference for anyone working at the cutting edge of industrial automation, communication systems, and networks, it will inspire further exploration in this promising research area.
Author: Subhas Chandra Mukhopadhyay
Publisher: Springer
ISBN: 3319216716
Category : Technology & Engineering
Languages : en
Pages : 340
Get Book Here
Book Description
Written by experts in their area of research, this book has outlined the current status of the fundamentals and analytical concepts, modelling and design issues, technical details and practical applications of different types of sensors and discussed about the trends of next generation of sensors and systems happening in the area of Sensing technology. This book will be useful as a reference book for engineers and scientist especially the post-graduate students find will this book as reference book for their research on wearable sensors, devices and technologies.
Author: Arun Abhishek Imayakumar
Publisher:
ISBN:
Category : Anomaly detection (Computer security)
Languages : en
Pages :
Get Book Here
Book Description
Sensor measurements of distribution system are uncertain due to sensor malfunctions, communication failure and cyber attacks. This thesis aims to perform anomaly detection on measurements utilizing data-driven approaches. The measurements considered are individual smart meter real power measurements and network-wide primary voltage magnitudes. Anomaly detection in individual smart meter measurements using gaussian probabilistic thresholds is explored. It flags non-anomalous data as verified by the comparison of smart meter real power and individual appliance consumption. To perform a real-time comparison for detection, Non-Intrusive Load Monitoring (NILM) is needed, which is difficult due to the associated consumer privacy issues. Alternatively, forecasting can be used for anomaly detection. So, single layer neural network models such as Multi-Layer Perceptron (MLP), and Long Short Term Memory (LSTM) with different features are tried. Even in training data, a poor performance is seen in these models, due to the smart meter profile variability. Hence, aggregated smart meter forecasting using neural networks can be used to detect anomaly in such aggregated measurements with a reasonable accuracy. Network-wide primary voltage measurements are correlated for a phase of feeder for different buses at a given time-step; this is extensively validated empirically. To leverage this, Principal Component Analysis (PCA) is used to reduce the dimensionality of this input data. Further, residual and subspace based methods are explored for network-level anomaly detection and identification. The results for the residual approach on missing and bad data cases are detailed for IEEE 13 bus and IEEE 8500 node test feeders. It is validated through simulations that residual-based approach on subspace projection matrix for the measurement data successfully performs anomaly detection and identification for primary network voltage measurements for the selected test cases. Further research is needed to validate the applicability and accuracy of the proposed framework during changes in the system operating conditions (topology changes, capacitor bank switching, etc.), and on real-world measurements form sensors deployed in the field.
Author: Giancarlo Fortino
Publisher: Springer Science & Business Media
ISBN: 3319004913
Category : Technology & Engineering
Languages : en
Pages : 203
Get Book Here
Book Description
The Internet of Things (IoT) usually refers to a world-wide network of interconnected heterogeneous objects (sensors, actuators, smart devices, smart objects, RFID, embedded computers, etc) uniquely addressable, based on standard communication protocols. Beyond such a definition, it is emerging a new definition of IoT seen as a loosely coupled, decentralized system of cooperating smart objects (SOs). A SO is an autonomous, physical digital object augmented with sensing/actuating, processing, storing, and networking capabilities. SOs are able to sense/actuate, store, and interpret information created within themselves and around the neighbouring external world where they are situated, act on their own, cooperate with each other, and exchange information with other kinds of electronic devices and human users. However, such SO-oriented IoT raises many in-the-small and in-the-large issues involving SO programming, IoT system architecture/middleware and methods/methodologies for the development of SO-based applications. This Book will specifically focus on exploring recent advances in architectures, algorithms, and applications for an Internet of Things based on Smart Objects. Topics appropriate for this Book include, but are not necessarily limited to: - Methods for SO development - IoT Networking - Middleware for SOs - Data Management for SOs - Service-oriented SOs - Agent-oriented SOs - Applications of SOs in Smart Environments: Smart Cities, Smart Health, Smart Buildings, etc. Advanced IoT Projects.
Author: Maryam Etezadbrojerdi
Publisher:
ISBN:
Category :
Languages : en
Pages :
Get Book Here
Book Description
Author: Víctor Garcia Font
Publisher:
ISBN:
Category :
Languages : en
Pages : 162
Get Book Here
Book Description
Aquesta tesi proposa una plataforma de detecció d'intrusions per a revelar atacs a les xarxes de sensors sense fils (WSN, per les sigles en anglès) de les ciutats intel·ligents (smart cities). La plataforma està dissenyada tenint en compte les necessitats dels administradors de la ciutat intel·ligent, els quals necessiten accés a una arquitectura centralitzada que pugui gestionar alarmes de seguretat en un sistema altament heterogeni i distribuït. En aquesta tesi s'identifiquen els diversos passos necessaris des de la recollida de dades fins a l'execució de les tècniques de detecció d'intrusions i s'avalua que el procés sigui escalable i capaç de gestionar dades típiques de ciutats intel·ligents. A més, es comparen diversos algorismes de detecció d'anomalies i s'observa que els mètodes de vectors de suport d'una mateixa classe (one-class support vector machines) resulten la tècnica multivariant més adequada per a descobrir atacs tenint en compte les necessitats d'aquest context. Finalment, es proposa un esquema per a ajudar els administradors a identificar els tipus d'atacs rebuts a partir de les alarmes disparades.
Author: Yuanyuan Li
Publisher:
ISBN:
Category :
Languages : en
Pages : 135
Get Book Here
Book Description
This dissertation addresses the problem of distributed anomaly detection in Wireless Sensor Networks (WSN). A challenge of designing such systems is that the sensor nodes are battery powered, often have different capabilities and generally operate in dynamic environments. Programming such sensor nodes at a large scale can be a tedious job if the system is not carefully designed. Data modeling in distributed systems is important for determining the normal operation mode of the system. Being able to model the expected sensor signatures for typical operations greatly simplifies the human designer's job by enabling the system to autonomously characterize the expected sensor data streams. This, in turn, allows the system to perform autonomous anomaly detection to recognize when unexpected sensor signals are detected. This type of distributed sensor modeling can be used in a wide variety of sensor networks, such as detecting the presence of intruders, detecting sensor failures, and so forth. The advantage of this approach is that the human designer does not have to characterize the anomalous signatures in advance. The contributions of this approach include: (1) providing a way for a WSN to autonomously model sensor data with no prior knowledge of the environment; (2) enabling a distributed system to detect anomalies in both sensor signals and temporal events online; (3) providing a way to automatically extract semantic labels from temporal sequences; (4) providing a way for WSNs to save communication power by transmitting compressed temporal sequences; (5) enabling the system to detect time-related anomalies without prior knowledge of abnormal events; and, (6) providing a novel missing data estimation method that utilizes temporal and spatial information to replace missing values. The algorithms have been designed, developed, evaluated, and validated experimentally in synthesized data, and in real-world sensor network applications.
Author: D. Hawkins
Publisher: Springer Science & Business Media
ISBN: 9401539944
Category : Science
Languages : en
Pages : 194
Get Book Here
Book Description
The problem of outliers is one of the oldest in statistics, and during the last century and a half interest in it has waxed and waned several times. Currently it is once again an active research area after some years of relative neglect, and recent work has solved a number of old problems in outlier theory, and identified new ones. The major results are, however, scattered amongst many journal articles, and for some time there has been a clear need to bring them together in one place. That was the original intention of this monograph: but during execution it became clear that the existing theory of outliers was deficient in several areas, and so the monograph also contains a number of new results and conjectures. In view of the enormous volume ofliterature on the outlier problem and its cousins, no attempt has been made to make the coverage exhaustive. The material is concerned almost entirely with the use of outlier tests that are known (or may reasonably be expected) to be optimal in some way. Such topics as robust estimation are largely ignored, being covered more adequately in other sources. The numerous ad hoc statistics proposed in the early work on the grounds of intuitive appeal or computational simplicity also are not discussed in any detail.
