Amlan Chakrabarti

The book commences with an introductory section on reconfigurable computing and thereafter delves into its applications in critical infrastructures. This book analyzes how such systems may be affected due to vulnerabilities and also discusses how these can be attacked by adversaries or cybercriminals. This book also discusses protection mechanisms related to such threats. It initially starts with an introduction to the various industrial revolutions and the changes in security needs, followed by a basic description of reconfigurable hardware based critical infrastructures. Further, the book contains discussion on security administration and planning, auditing, monitoring and analysis, risk-response and recovery, control and countermeasures highlighting their need in reconfigurable hardware-based platforms. In addition to these, new concepts are introduced such as AI/ML for cybersecurity, digital forensics related to reconfigurable hardware based critical infrastructures. Finally, a hands on learning experience is presented to provide the readers with a practical flavour. The book will be useful to students (graduate and undergraduate), researchers, academicians and industry professionals.

Application of Artificial Intelligence in Early Detection of Lung Cancer presents the most up-to-date computer-aided diagnosis techniques used to effectively predict and diagnose lung cancer. The presence of pulmonary nodules on lung parenchyma is often considered an early sign of lung cancer, thus using machine and deep learning technologies to identify them is key to improve patients’ outcome and decrease the lethal rate of such disease. The book discusses topics such as basics of lung cancer imaging, pattern recognition techniques, deep learning, and nodule detection and localization. In addition, the book discusses risk prediction based on radiological analysis and 3D modeling. This is a valuable resource for cancer researchers, oncologists, graduate students, radiologists, and members of biomedical field who are interested in the potential of AI technologies in the diagnosis of lung cancer.

This book focuses on how real-time task schedules for reconfigurable hardware-based embedded platforms may be affected due to the vulnerability of hardware and proposes self-aware security strategies to counteract the various threats. The emergence of Industry 4.0 has witnessed the deployment of reconfigurable hardware or field programmable gate arrays (FPGAs) in diverse embedded applications. These are associated with the execution of several real-time tasks arranged in schedules. However, they are associated with several issues. Development of fully and partially reconfigurable task schedules are discussed that eradicates the existing problems. However, such real-time task schedules may be jeopardized due to hardware threats. Analysis of such threats is discussed and self-aware security techniques are proposed that can detect and mitigate such threats at runtime.

This book focuses on how real-time task schedules for reconfigurable hardware-based embedded platforms may be affected due to the vulnerability of hardware and proposes self-aware security strategies to counteract the various threats. The emergence of Industry 4.0 has witnessed the deployment of reconfigurable hardware or field programmable gate arrays (FPGAs) in diverse embedded applications. These are associated with the execution of several real-time tasks arranged in schedules. However, they are associated with several issues. Development of fully and partially reconfigurable task schedules are discussed that eradicates the existing problems. However, such real-time task schedules may be jeopardized due to hardware threats. Analysis of such threats is discussed and self-aware security techniques are proposed that can detect and mitigate such threats at runtime.

This book identifies the time-dependent network parameters: neighbour count, link load, path length, cluster count and delay, and presents a first-of-its-kind discussion on temporal parameters in mobile ad hoc networks. Frequent topology changes and multiple link failures occur in mobile ad hoc network due to arbitrary and random movement of nodes. This dynamic environment challenges the delivery of data and makes it essential to find better models for network parameters that are shifting with time. The parameters identified are put into the framework of time series because of their temporal characteristic, and when they are modelled using time series framework they exhibit a sound fit with Autoregressive AR(p) models of order p. The order p is evaluated for each fitted model and found to lie between one and three. The book also analyses the dependence of end-to-end delay of ad hoc network on various external factors such as the number of nodes, routing protocol, mobility models and path length and develops two prediction models. The book will be useful for researchers and professionals alike.

This book identifies the time-dependent network parameters: neighbour count, link load, path length, cluster count and delay, and presents a first-of-its-kind discussion on temporal parameters in mobile ad hoc networks. Frequent topology changes and multiple link failures occur in mobile ad hoc network due to arbitrary and random movement of nodes. This dynamic environment challenges the delivery of data and makes it essential to find better models for network parameters that are shifting with time. The parameters identified are put into the framework of time series because of their temporal characteristic, and when they are modelled using time series framework they exhibit a sound fit with Autoregressive AR(p) models of order p. The order p is evaluated for each fitted model and found to lie between one and three. The book also analyses the dependence of end-to-end delay of ad hoc network on various external factors such as the number of nodes, routing protocol, mobility models and path length and develops two prediction models. The book will be useful for researchers and professionals alike.