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Interconnecting Smart Objects with IP: The Next Internet explains why the Internet Protocol (IP) has become the protocol of choice for smart object networks.IP has successfully demonstrated the ability to interconnect billions of digital systems on the global Internet and in private IP networks.

Skillfully navigate through the complex realm of implementing scalable, trustworthy industrial systems and architectures in a hyper-connected business world. Key Features * Gain practical insight into security concepts in the Industrial Internet of Things (IIoT) architecture * Demystify complex topics such as cryptography and blockchain * Comprehensive references to industry standards and security frameworks when developing IIoT blueprints Book Description Securing connected industries and autonomous systems is a top concern for the Industrial Internet of Things (IIoT) community. Unlike cybersecurity, cyber-physical security is an intricate discipline that directly ties to system reliability as well as human and environmental safety. Practical Industrial Internet of Things Security enables you to develop a comprehensive understanding of the entire spectrum of securing connected industries, from the edge to the cloud. This book establishes the foundational concepts and tenets of IIoT security by presenting real-world case studies, threat models, and reference architectures. You'll work with practical tools to design risk-based security controls for industrial use cases and gain practical know-how on the multi-layered defense techniques including Identity and Access Management (IAM), endpoint security, and communication infrastructure. Stakeholders, including developers, architects, and business leaders, can gain practical insights in securing IIoT lifecycle processes, standardization, governance and assess the applicability of emerging technologies, such as blockchain, Artificial Intelligence, and Machine Learning, to design and implement resilient connected systems and harness significant industrial opportunities. What you will learn * Understand the crucial concepts of a multi-layered IIoT security framework * Gain insight on securing identity, access, and configuration management for large-scale IIoT deployments * Secure your machine-to-machine (M2M) and machine-to-cloud (M2C) connectivity * Build a concrete security program for your IIoT deployment * Explore techniques from case studies on industrial IoT threat modeling and mitigation approaches * Learn risk management and mitigation planning Who this book is for Practical Industrial Internet of Things Security is for the IIoT community, which includes IIoT researchers, security professionals, architects, developers, and business stakeholders. Anyone who needs to have a comprehensive understanding of the unique safety and security challenges of connected industries and practical methodologies to secure industrial assets will find this book immensely helpful. This book is uniquely designed to benefit professionals from both IT and industrial operations backgrounds.

Mobile phone forensics is the science of retrieving data from a mobile phone under forensically sound conditions. This book is an update to Practical Mobile Forensics, Second Edition and it delves into the concepts of mobile forensics and its importance in today's world.

Alternaria leaf blotch, and rust are two common types of apple leaf diseases that severely affect apple yield. A timely and effective detection of apple leaf diseases is crucial for ensuring the healthy development of the apple industry. In general, these diseases are inspected by experienced experts one by one. This is a time-consuming task with unstable precision. Therefore, in this paper, we proposed a LOW-COST, STABLE, HIGH precision apple leaf diseases identification method. This is achieved by employing MobileNet model. Firstly, comparing with general deep learning model, it is a LOW-COST model because it can be easily deployed on mobile devices. Secondly, instead of experienced experts, everyone can finish the apple leaf diseases inspection STABLELY by the help of our algorithm. Thirdly, the precision of MobileNet is nearly the same with existing complicated deep learning models. Finally, in order to demonstrated the effectiveness of our proposed method, several experiments have been carried out for apple leaf diseases identification. We have compared the efficiency and precision with the famous CNN models: i.e. ResNet152 and InceptionV3. Here, the apple disease datasets (including classes: Alternaria leaf blotch and rust leaf) were collected by the agriculture experts in Shaanxi Province, China.

Recently, more and more mobile apps are employed in the marketing field with technical advances. Mobile marketing apps have become a prevalent way for enterprise marketing. Therefore, it has been an important and urgent problem to provide personalized and accurate recommendation in mobile marketing, with a large number of items and limited capability of mobile devices. Recommendation have been investigated widely, however, most existing approaches fail to consider the stability or change of users’ behaviors over time. In this paper, we first propose to mine the periodic trends of users’ consuming behavior from historical records by KNN(K-nearest neighbor) and SVR (support vector regression) based time series prediction, and predict the next time when a user re-purchases the item, so that we can recommend the items which users have purchased before at proper time. Second, we aim to find the regularity of users’ purchasing behavior during different life stages and recommend the new items that are needed and proper for their current life stage. In order to solve this, we mine the mapping model from items to user’s life stage first. Based on the model, users’ current life stage can be estimated from their recent behaviors. Finally, users will be recommended with new items which are proper to their estimated life stage. Experimental results show that it has improved the effectiveness of recommendation obviously by mining users’ consuming behaviors with temporal evolution.

Kotlin greatly reduces the verbosity of source code. With Google having announced their support for Kotlin as a first-class language for writing Android apps, now's the time learn how to create apps from scratch with Kotlin. Kotlin Programming By Example takes you through the building blocks of Kotlin, such as functions and classes. You’ll explore various features of Kotlin by building three applications of varying complexity. For a quick start to Android development, we look at building a classic game, Tetris, and elaborate on object-oriented programming in Kotlin. Our next application will be a messenger app, a level up in terms of complexity. Before moving onto the third app, we take a look at data persistent methods, helping us learn about the storage and retrieval of useful applications. Our final app is a place reviewer: a web application that will make use of the Google Maps API and Place Picker. By the end of this book, you will have gained experience of of creating and deploying Android applications using Kotlin.

Connect things to create amazing IoT applications in minutesAbout This Book• Use Blynk cloud and Blynk server to connect devices• Build IoT applications on Android and iOS platforms• A practical guide that will show how to connect devices using Blynk and Raspberry Pi 3Who This Book Is ForThis book is targeted at any stakeholder working in the IoT sector who wants to understand how Blynk works and build exciting IoT projects. Prior understanding of Raspberry Pi, C/C++, and electronics is a must.What You Will Learn• Build devices using Raspberry Pi and various sensors and actuators• Use Blynk cloud to connect and control devices through the Blynk app• Connect devices to Blynk cloud and server through Ethernet and Wi-Fi• Make applications using Blynk apps (App Builder) on Android and iOS platforms• Run Blynk personal server on the Windows, MAC, and Raspberry Pi platformsIn DetailBlynk, known as the most user-friendly IoT platform, provides a way to build mobile applications in minutes. With the Blynk drag-n-drop mobile app builder, anyone can build amazing IoT applications with minimal resources and effort, on hardware ranging from prototyping platforms such as Arduino and Raspberry Pi 3 to industrial-grade ESP8266, Intel, Sierra Wireless, Particle, Texas Instruments, and a few others.This book uses Raspberry Pi as the main hardware platform and C/C++ to write sketches to build projects. The first part of this book shows how to set up a development environment with various hardware combinations and required software. Then you will build your first IoT application with Blynk using various hardware combinations and connectivity types such as Ethernet and Wi-Fi. Then you'll use and configure various widgets (control, display, notification, interface, time input, and some advanced widgets) with Blynk App Builder to build applications. Towards the end, you will learn how to connect with and use built-in sensors on Android and iOS mobile devices. Finally you will learn how to build a robot that can be controlled with a Blynk app through the Blynk cloud and personal server.By the end of this book, you will have hands-on experience building IoT applications using Blynk.Style and approachA step-by-step guide that will help you build simple yet exciting project in no time.

Learn to build end-to-end AI apps from scratch for Android and iOS using TensorFlow Lite, CoreML, and PyTorch Key Features * Build practical, real-world AI projects on Android and iOS * Implement tasks such as recognizing handwritten digits, sentiment analysis, and more * Explore the core functions of machine learning, deep learning, and mobile vision Book Description We're witnessing a revolution in Artificial Intelligence, thanks to breakthroughs in deep learning. Mobile Artificial Intelligence Projects empowers you to take part in this revolution by applying Artificial Intelligence (AI) techniques to design applications for natural language processing (NLP), robotics, and computer vision. This book teaches you to harness the power of AI in mobile applications along with learning the core functions of NLP, neural networks, deep learning, and mobile vision. It features a range of projects, covering tasks such as real-estate price prediction, recognizing hand-written digits, predicting car damage, and sentiment analysis. You will learn to utilize NLP and machine learning algorithms to make applications more predictive, proactive, and capable of making autonomous decisions with less human input. In the concluding chapters, you will work with popular libraries, such as TensorFlow Lite, CoreML, and PyTorch across Android and iOS platforms. By the end of this book, you will have developed exciting and more intuitive mobile applications that deliver a customized and more personalized experience to users. What you will learn * Explore the concepts and fundamentals of AI, deep learning, and neural networks * Implement use cases for machine vision and natural language processing * Build an ML model to predict car damage using TensorFlow * Deploy TensorFlow on mobile to convert speech to text * Implement GAN to recognize hand-written digits * Develop end-to-end mobile applications that use AI principles * Work with popular libraries, such as TensorFlow Lite, CoreML, and PyTorch Who this book is for Mobile Artificial Intelligence Projects is for machine learning professionals, deep learning engineers, AI engineers, and software engineers who want to integrate AI technology into mobile-based platforms and applications. Sound knowledge of machine learning and experience with any programming language is all you need to get started with this book.

Get to grips with modern software demands by learning the effective uses of Rust's powerful memory safety.About This Book• Learn and improve the sequential performance characteristics of your software• Understand the use of operating system processes in a high-scale concurrent system• Learn of the various coordination methods available in the Standard libraryWho This Book Is ForThis book is aimed at software engineers with a basic understanding of Rust who want to exploit the parallel and concurrent nature of modern computing environments, safely.What You Will Learn• Probe your programs for performance and accuracy issues• Create your own threading and multi-processing environment in Rust• Use coarse locks from Rust's Standard library• Solve common synchronization problems or avoid synchronization using atomic programming• Build lock-free/wait-free structures in Rust and understand their implementations in the crates ecosystem• Leverage Rust's memory model and type system to build safety properties into your parallel programs• Understand the new features of the Rust programming language to ease the writing of parallel programsIn DetailMost programming languages can really complicate things, especially with regard to unsafe memory access. The burden on you, the programmer, lies across two domains: understanding the modern machine and your language's pain-points. This book will teach you to how to manage program performance on modern machines and build fast, memory-safe, and concurrent software in Rust. It starts with the fundamentals of Rust and discusses machine architecture concepts. You will be taken through ways to measure and improve the performance of Rust code systematically and how to write collections with confidence. You will learn about the Sync and Send traits applied to threads, and coordinate thread execution with locks, atomic primitives, data-parallelism, and more.The book will show you how to efficiently embed Rust in C++ code and explore the functionalities of various crates for multithreaded applications. It explores implementations in depth. You will know how a mutex works and build several yourself. You will master radically different approaches that exist in the ecosystem for structuring and managing high-scale systems.By the end of the book, you will feel comfortable with designing safe, consistent, parallel, and high-performance applications in Rust.Style and approachReaders will be taken through various ways to improve the performance of their Rust code.

Device-to-Device (D2D) communications have emerged as a promising technology for the next generation mobile communication networks and wireless systems (5G). As an underlay network of conventional cellular networks (LTE or LTE-Advanced), D2D communications have shown great potential in improving communication capability, erasing communication delay, reducing power dissipation, and fostering multifarious new applications and services. However, security in D2D communications, which is essential for the success of D2D services, has not yet been seriously studied in the literature. In this paper, we explore a security architecture for D2D communications under the framework of 3GPP LTE. We further investigate potential security threats and specify security requirements accordingly. Existing security solutions in D2D communications are seriously surveyed and evaluated based on the specified security architecture and requirements in order to figure out open research issues and motivate future research efforts.