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Examines the design and use of Intrusion Detection Systems (IDS) to secure Supervisory Control and Data Acquisition (SCADA) systemsCyber-attacks on SCADA systems-the control system architecture that uses computers, networked data communications, and graphical user interfaces for high-level process supervisory management-can lead to costly financial consequences or even result in loss of life. Minimizing potential risks and responding to malicious actions requires innovative approaches for monitoring SCADA systems and protecting them from targeted attacks. SCADA Security: Machine Learning Concepts for Intrusion Detection and Prevention is designed to help security and networking professionals develop and deploy accurate and effective Intrusion Detection Systems (IDS) for SCADA systems that leverage autonomous machine learning.Providing expert insights, practical advice, and up-to-date coverage of developments in SCADA security, this authoritative guide presents a new approach for efficient unsupervised IDS driven by SCADA-specific data. Organized into eight in-depth chapters, the text first discusses how traditional IT attacks can also be possible against SCADA, and describes essential SCADA concepts, systems, architectures, and main components. Following chapters introduce various SCADA security frameworks and approaches, including evaluating security with virtualization-based SCADAVT, using SDAD to extract proximity-based detection, finding a global and efficient anomaly threshold with GATUD, and more. This important book:* Provides diverse perspectives on establishing an efficient IDS approach that can be implemented in SCADA systems* Describes the relationship between main components and three generations of SCADA systems* Explains the classification of a SCADA IDS based on its architecture and implementation* Surveys the current literature in the field and suggests possible directions for future researchSCADA Security: Machine Learning Concepts for Intrusion Detection and Prevention is a must-read for all SCADA security and networking researchers, engineers, system architects, developers, managers, lecturers, and other SCADA security industry practitioners.

Summarizes the current state and upcoming trends within the area of fog computingWritten by some of the leading experts in the field, Fog Computing: Theory and Practice focuses on the technological aspects of employing fog computing in various application domains, such as smart healthcare, industrial process control and improvement, smart cities, and virtual learning environments. In addition, the Machine-to-Machine (M2M) communication methods for fog computing environments are covered in depth.Presented in two parts--Fog Computing Systems and Architectures, and Fog Computing Techniques and Application--this book covers such important topics as energy efficiency and Quality of Service (QoS) issues, reliability and fault tolerance, load balancing, and scheduling in fog computing systems. It also devotes special attention to emerging trends and the industry needs associated with utilizing the mobile edge computing, Internet of Things (IoT), resource and pricing estimation, and virtualization in the fog environments.* Includes chapters on deep learning, mobile edge computing, smart grid, and intelligent transportation systems beyond the theoretical and foundational concepts* Explores real-time traffic surveillance from video streams and interoperability of fog computing architectures* Presents the latest research on data quality in the IoT, privacy, security, and trust issues in fog computingFog Computing: Theory and Practice provides a platform for researchers, practitioners, and graduate students from computer science, computer engineering, and various other disciplines to gain a deep understanding of fog computing.

A comprehensive guide to Fog and Edge applications, architectures, and technologiesRecent years have seen the explosive growth of the Internet of Things (IoT): the internet-connected network of devices that includes everything from personal electronics and home appliances to automobiles and industrial machinery. Responding to the ever-increasing bandwidth demands of the IoT, Fog and Edge computing concepts have developed to collect, analyze, and process data more efficiently than traditional cloud architecture.Fog and Edge Computing: Principles and Paradigms provides a comprehensive overview of the state-of-the-art applications and architectures driving this dynamic field of computing while highlighting potential research directions and emerging technologies.Exploring topics such as developing scalable architectures, moving from closed systems to open systems, and ethical issues rising from data sensing, this timely book addresses both the challenges and opportunities that Fog and Edge computing presents. Contributions from leading IoT experts discuss federating Edge resources, middleware design issues, data management and predictive analysis, smart transportation and surveillance applications, and more. A coordinated and integrated presentation of topics helps readers gain thorough knowledge of the foundations, applications, and issues that are central to Fog and Edge computing. This valuable resource:* Provides insights on transitioning from current Cloud-centric and 4G/5G wireless environments to Fog Computing* Examines methods to optimize virtualized, pooled, and shared resources* Identifies potential technical challenges and offers suggestions for possible solutions* Discusses major components of Fog and Edge computing architectures such as middleware, interaction protocols, and autonomic management* Includes access to a website portal for advanced online resourcesFog and Edge Computing: Principles and Paradigms is an essential source of up-to-date information for systems architects, developers, researchers, and advanced undergraduate and graduate students in fields of computer science and engineering.

Defines the notion of an activity model learned from sensor data and presents key algorithms that form the core of the field Activity Learning: Discovering, Recognizing and Predicting Human Behavior from Sensor Data provides an in-depth look at computational approaches to activity learning from sensor data.

Addresses innovations in technology relating to the energy efficiency of a wide variety of contemporary computer systems and networks With concerns about global energy consumption at an all-time high, improving computer networks energy efficiency is becoming an increasingly important topic.

With recent changes in multicore and general-purpose computing on graphics processing units, the way parallel computers are used and programmed has drastically changed. It is important to provide a comprehensive study on how to use such machines written by specialists of the domain.

While other books on the market provide limited coverage of advanced CDNs and streaming technologies, concentrating solely on the fundamentals, this book provides an up-to-date comprehensive coverage of the state-of-the-art advancements in CDNs, with a special focus on Cloud-based CDNs.

Scalable Computing and Communications reviews the latest advances in the all-important field of scalable computing.

This book presents the most up-to-date opportunities and challenges emerging in knowledge discovery, helping readers develop the technical skills to design and develop data-intensive methods and processes.

New techniques (z-transform, graphic, algebraic) for studying and analyzing parallel algorithms and how to use them Case studies throughout th book Problems at the end of each chapter and available solutions manual A companion website to include lecture notes .

A critical work covering high-performance heterogeneous computing Analyzes issues encountered when programming heterogeneous networks Overviews software for parallel and distributed programming for heterogeneous networks The authors efforts provided the first large-scale robust infrastructure for distributed computing and communication.

Complex systems modeling and simulation approaches are being adopted in a growing number of sectors, including finance, economics, biology, astronomy, and many more.

* Explains and analyzes complex topics to an unprecedented degree * Provides a useful reference to graduate students and a jump-off point for new research * In-depth coverage takes reader from ground level hardware issues up to highly advanced application and network discussions .

The energy consumption issue in distributed computing systems raises various monetary, environmental and system performance concerns. Electricity consumption in the US doubled from 2000 to 2005.

In the near future, wireless sensor networks will become an integral part of our day-to-day life. To solve different sensor networking related issues, researchers have been putting various efforts and coming up with innovative ideas.

Captures state-of-the-art in Cloud Computing Indentifies potential research directions and technologies Chapters written by industry experts and contain real world case studies Example illustrating problems and review questions for each chapter .

Mobile Intelligence is divided into eight distinct sections with several contributions in each representing leading edge research within the area of mobile computing and computational intelligence.

The rapid expansion of the Internet has made parallel and distributed stimulation (PADS) a hot technology indeed. It is now used not only to analyze the behavior of such systems as air traffic control or future communication networks, but also in computer generated "virtual worlds" such as flight simulation training devices and computer wargames.

High Performance Parallel Database Processing and Grid Databases targets the theoretical/conceptual details needed to form a base of understanding and then delivers information on development, implementations, and analytical modeling of parallel databases. This includes key information on new developments with grid databases.

This book provides a step-by-step interactive introduction to formal verification of systems and circuits. In view of the complexity of current parallel digital systems, a formal approach to their analysis and verification becomes essential. This text makes use of two powerful analysis tool sets: LOTOS-based CADP & Petri-Net based PETRIFY.

New automated, application-independent methodology for designing and deploying sensor networks Following this book's clear explanations, examples, and illustrations, domain experts can design and deploy nontrivial networked sensing applications without much knowledge of the low-level networking aspects of deployment.

Covers the continuous advances in wireless and mobile communications through the use of algorithms and protocols. Focuses on wireless ad hoc and sensor networks with a concentration on algorithms and protocols. Written by a well-known and an established international researcher in the field of wireless mobile networks and distributed systems. .

* Focuses on several aspects of wireless ad hoc networks, particularly algorithmic methods and distributed computing with mobility and computation capability. * This book provides the crucial building foundation for the design and construction of the future generation of ad hoc networks.

Advanced computational infrastructures provide programming, execution and runtime management support for large-scale adaptive implementations. Investigates the design, architectures and implementations of advanced computional infrastructures.

Internet-based business transactions can be broken down into a series of independent steps. This workflow often involves tools from an array of fields, such as network modeling, scheduling, distributed systems, artificial intelligence, software agents, and Java. This book deals with this topic.

This book offers comprehensive coverage of wireless networks and mobile computing with an emphasis on computer science and system considerations rather than devices. It offers detailed, practical discussion of topics such as cellular networks, channel assignment, queuing, power optimization, and more.

The first single-source reference covering the state of the art in grid and utility computing economy researchThis book presents the first integrated, single-source reference on market-oriented grid and utility computing.

The complexity of today's information processing requirements, coupled with the availability of powerful computers, have boosted the interest in the study, design, and analysis of parallel algorithms. Introduction to Parallel Algorithms responds to the need in the field for an easy-to-understand text in this growth area of computer science.

Parallel Computing for Bioinformatics is the first book to deal with the topic of parallel computing and bioinformatics. Written by renowned experts and well-reputed researchers in this emerging field, it provides an opportunity for researchers to explore the rich and complex subject of ?Bioinformatics?.

Real-world problems and modern optimization techniques to solve them Here, a team of international experts brings together core ideas for solving complex problems in optimization across a wide variety of real-world settings, including computer science, engineering, transportation, telecommunications, and bioinformatics.