Hands On Artificial Intelligence For Cybersecurity

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Hands On Artificial Intelligence For Cybersecurity

Author : Alessandro Parisi
ISBN : 9781789805178
Genre : Computers
File Size : 44.4 MB
Format : PDF, Docs
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Build smart cybersecurity systems with the power of machine learning and deep learning to protect your corporate assets Key Features Identify and predict security threats using artificial intelligence Develop intelligent systems that can detect unusual and suspicious patterns and attacks Learn how to test the effectiveness of your AI cybersecurity algorithms and tools Book Description Today's organizations spend billions of dollars globally on cybersecurity. Artificial intelligence has emerged as a great solution for building smarter and safer security systems that allow you to predict and detect suspicious network activity, such as phishing or unauthorized intrusions. This cybersecurity book presents and demonstrates popular and successful AI approaches and models that you can adapt to detect potential attacks and protect your corporate systems. You'll learn about the role of machine learning and neural networks, as well as deep learning in cybersecurity, and you'll also learn how you can infuse AI capabilities into building smart defensive mechanisms. As you advance, you'll be able to apply these strategies across a variety of applications, including spam filters, network intrusion detection, botnet detection, and secure authentication. By the end of this book, you'll be ready to develop intelligent systems that can detect unusual and suspicious patterns and attacks, thereby developing strong network security defenses using AI. What you will learn Detect email threats such as spamming and phishing using AI Categorize APT, zero-days, and polymorphic malware samples Overcome antivirus limits in threat detection Predict network intrusions and detect anomalies with machine learning Verify the strength of biometric authentication procedures with deep learning Evaluate cybersecurity strategies and learn how you can improve them Who this book is for If you’re a cybersecurity professional or ethical hacker who wants to build intelligent systems using the power of machine learning and AI, you’ll find this book useful. Familiarity with cybersecurity concepts and knowledge of Python programming is essential to get the most out of this book.
Category: Computers

Hands On Machine Learning For Cybersecurity

Author : Soma Halder
ISBN : 9781788990967
Genre : Computers
File Size : 46.30 MB
Format : PDF, Docs
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Get into the world of smart data security using machine learning algorithms and Python libraries Key Features Learn machine learning algorithms and cybersecurity fundamentals Automate your daily workflow by applying use cases to many facets of security Implement smart machine learning solutions to detect various cybersecurity problems Book Description Cyber threats today are one of the costliest losses that an organization can face. In this book, we use the most efficient tool to solve the big problems that exist in the cybersecurity domain. The book begins by giving you the basics of ML in cybersecurity using Python and its libraries. You will explore various ML domains (such as time series analysis and ensemble modeling) to get your foundations right. You will implement various examples such as building system to identify malicious URLs, and building a program to detect fraudulent emails and spam. Later, you will learn how to make effective use of K-means algorithm to develop a solution to detect and alert you to any malicious activity in the network. Also learn how to implement biometrics and fingerprint to validate whether the user is a legitimate user or not. Finally, you will see how we change the game with TensorFlow and learn how deep learning is effective for creating models and training systems What you will learn Use machine learning algorithms with complex datasets to implement cybersecurity concepts Implement machine learning algorithms such as clustering, k-means, and Naive Bayes to solve real-world problems Learn to speed up a system using Python libraries with NumPy, Scikit-learn, and CUDA Understand how to combat malware, detect spam, and fight financial fraud to mitigate cyber crimes Use TensorFlow in the cybersecurity domain and implement real-world examples Learn how machine learning and Python can be used in complex cyber issues Who this book is for This book is for the data scientists, machine learning developers, security researchers, and anyone keen to apply machine learning to up-skill computer security. Having some working knowledge of Python and being familiar with the basics of machine learning and cybersecurity fundamentals will help to get the most out of the book
Category: Computers

Hands On Cybersecurity For Finance

Author : Dr. Erdal Ozkaya
ISBN : 9781788831734
Genre : Computers
File Size : 23.43 MB
Format : PDF, Mobi
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A comprehensive guide that will give you hands-on experience to study and overcome financial cyber threats Key Features Protect your financial environment with cybersecurity practices and methodologies Identify vulnerabilities such as data manipulation and fraudulent transactions Provide end-to-end protection within organizations Book Description Organizations have always been a target of cybercrime. Hands-On Cybersecurity for Finance teaches you how to successfully defend your system against common cyber threats, making sure your financial services are a step ahead in terms of security. The book begins by providing an overall description of cybersecurity, guiding you through some of the most important services and technologies currently at risk from cyber threats. Once you have familiarized yourself with the topic, you will explore specific technologies and threats based on case studies and real-life scenarios. As you progress through the chapters, you will discover vulnerabilities and bugs (including the human risk factor), gaining an expert-level view of the most recent threats. You'll then explore information on how you can achieve data and infrastructure protection. In the concluding chapters, you will cover recent and significant updates to procedures and configurations, accompanied by important details related to cybersecurity research and development in IT-based financial services. By the end of the book, you will have gained a basic understanding of the future of information security and will be able to protect financial services and their related infrastructures. What you will learn Understand the cyber threats faced by organizations Discover how to identify attackers Perform vulnerability assessment, software testing, and pentesting Defend your financial cyberspace using mitigation techniques and remediation plans Implement encryption and decryption Understand how Artificial Intelligence (AI) affects cybersecurity Who this book is for Hands-On Cybersecurity for Finance is for you if you are a security architect, cyber risk manager, or pentester looking to secure your organization. Basic understanding of cybersecurity tools and practices will help you get the most out of this book.
Category: Computers

Ai In Cybersecurity

Author : Leslie F. Sikos
ISBN : 3319988417
Genre : Computers
File Size : 57.96 MB
Format : PDF, ePub
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This book presents a collection of state-of-the-art AI approaches to cybersecurity and cyberthreat intelligence, offering strategic defense mechanisms for malware, addressing cybercrime, and assessing vulnerabilities to yield proactive rather than reactive countermeasures. The current variety and scope of cybersecurity threats far exceed the capabilities of even the most skilled security professionals. In addition, analyzing yesterday’s security incidents no longer enables experts to predict and prevent tomorrow’s attacks, which necessitates approaches that go far beyond identifying known threats. Nevertheless, there are promising avenues: complex behavior matching can isolate threats based on the actions taken, while machine learning can help detect anomalies, prevent malware infections, discover signs of illicit activities, and protect assets from hackers. In turn, knowledge representation enables automated reasoning over network data, helping achieve cybersituational awareness. Bringing together contributions by high-caliber experts, this book suggests new research directions in this critical and rapidly growing field.
Category: Computers

Hands On Cybersecurity With Blockchain

Author : Rajneesh Gupta
ISBN : 9781788991858
Genre : Computers
File Size : 79.6 MB
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Develop blockchain application with step-by-step instructions, working example and helpful recommendations Key Features Understanding the blockchain technology from the cybersecurity perspective Developing cyber security solutions with Ethereum blockchain technology Understanding real-world deployment of blockchain based applications Book Description Blockchain technology is being welcomed as one of the most revolutionary and impactful innovations of today. Blockchain technology was first identified in the world’s most popular digital currency, Bitcoin, but has now changed the outlook of several organizations and empowered them to use it even for storage and transfer of value. This book will start by introducing you to the common cyberthreat landscape and common attacks such as malware, phishing, insider threats, and DDoS. The next set of chapters will help you to understand the workings of Blockchain technology, Ethereum and Hyperledger architecture and how they fit into the cybersecurity ecosystem. These chapters will also help you to write your first distributed application on Ethereum Blockchain and the Hyperledger Fabric framework. Later, you will learn about the security triad and its adaptation with Blockchain. The last set of chapters will take you through the core concepts of cybersecurity, such as DDoS protection, PKI-based identity, 2FA, and DNS security. You will learn how Blockchain plays a crucial role in transforming cybersecurity solutions. Toward the end of the book, you will also encounter some real-world deployment examples of Blockchain in security cases, and also understand the short-term challenges and future of cybersecurity with Blockchain. What you will learn Understand the cyberthreat landscape Learn about Ethereum and Hyperledger Blockchain Program Blockchain solutions Build Blockchain-based apps for 2FA, and DDoS protection Develop Blockchain-based PKI solutions and apps for storing DNS entries Challenges and the future of cybersecurity and Blockchain Who this book is for The book is targeted towards security professionals, or any stakeholder dealing with cybersecurity who wants to understand the next-level of securing infrastructure using Blockchain. Basic understanding of Blockchain can be an added advantage.
Category: Computers

Hands On Machine Learning With Ml Net

Author : Jarred Capellman
ISBN : 9781789804294
Genre : Computers
File Size : 73.66 MB
Format : PDF, Mobi
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Create, train, and evaluate various machine learning models such as regression, classification, and clustering using ML.NET, Entity Framework, and ASP.NET Core Key Features Get well-versed with the ML.NET framework and its components and APIs using practical examples Learn how to build, train, and evaluate popular machine learning algorithms with ML.NET offerings Extend your existing machine learning models by integrating with TensorFlow and other libraries Book Description Machine learning (ML) is widely used in many industries such as science, healthcare, and research and its popularity is only growing. In March 2018, Microsoft introduced ML.NET to help .NET enthusiasts in working with ML. With this book, you’ll explore how to build ML.NET applications with the various ML models available using C# code. The book starts by giving you an overview of ML and the types of ML algorithms used, along with covering what ML.NET is and why you need it to build ML apps. You’ll then explore the ML.NET framework, its components, and APIs. The book will serve as a practical guide to helping you build smart apps using the ML.NET library. You’ll gradually become well versed in how to implement ML algorithms such as regression, classification, and clustering with real-world examples and datasets. Each chapter will cover the practical implementation, showing you how to implement ML within .NET applications. You’ll also learn to integrate TensorFlow in ML.NET applications. Later you’ll discover how to store the regression model housing price prediction result to the database and display the real-time predicted results from the database on your web application using ASP.NET Core Blazor and SignalR. By the end of this book, you’ll have learned how to confidently perform basic to advanced-level machine learning tasks in ML.NET. What you will learn Understand the framework, components, and APIs of ML.NET using C# Develop regression models using ML.NET for employee attrition and file classification Evaluate classification models for sentiment prediction of restaurant reviews Work with clustering models for file type classifications Use anomaly detection to find anomalies in both network traffic and login history Work with ASP.NET Core Blazor to create an ML.NET enabled web application Integrate pre-trained TensorFlow and ONNX models in a WPF ML.NET application for image classification and object detection Who this book is for If you are a .NET developer who wants to implement machine learning models using ML.NET, then this book is for you. This book will also be beneficial for data scientists and machine learning developers who are looking for effective tools to implement various machine learning algorithms. A basic understanding of C# or .NET is mandatory to grasp the concepts covered in this book effectively.
Category: Computers

Data Science In Cybersecurity And Cyberthreat Intelligence

Author : Leslie F. Sikos
ISBN : 9783030387884
Genre : Computers
File Size : 22.74 MB
Format : PDF, Mobi
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This book presents a collection of state-of-the-art approaches to utilizing machine learning, formal knowledge bases and rule sets, and semantic reasoning to detect attacks on communication networks, including IoT infrastructures, to automate malicious code detection, to efficiently predict cyberattacks in enterprises, to identify malicious URLs and DGA-generated domain names, and to improve the security of mHealth wearables. This book details how analyzing the likelihood of vulnerability exploitation using machine learning classifiers can offer an alternative to traditional penetration testing solutions. In addition, the book describes a range of techniques that support data aggregation and data fusion to automate data-driven analytics in cyberthreat intelligence, allowing complex and previously unknown cyberthreats to be identified and classified, and countermeasures to be incorporated in novel incident response and intrusion detection mechanisms.
Category: Computers

Hands On Artificial Intelligence On Google Cloud Platform

Author : Anand Deshpande
ISBN : 9781789536485
Genre : Computers
File Size : 58.92 MB
Format : PDF, Mobi
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Develop robust AI applications with TensorFlow, Cloud AutoML, TPUs, and other GCP services Key Features Focus on AI model development and deployment in GCP without worrying about infrastructure Manage feature processing, data storage, and trained models using Google Cloud Dataflow Access key frameworks such as TensorFlow and Cloud AutoML to run your deep learning models Book Description With a wide range of exciting tools and libraries such as Google BigQuery, Google Cloud Dataflow, and Google Cloud Dataproc, Google Cloud Platform (GCP) enables efficient big data processing and the development of smart AI models on the cloud. This GCP book will guide you in using these tools to build your AI-powered applications with ease and managing thousands of AI implementations on the cloud to help save you time. Starting with a brief overview of Cloud AI and GCP features, you'll learn how to deal with large volumes of data using auto-scaling features. You'll then implement Cloud AutoML to demonstrate the use of streaming components for performing data analytics and understand how Dialogflow can be used to create a conversational interface. As you advance, you'll be able to scale out and speed up AI and predictive applications using TensorFlow. You'll also leverage GCP to train and optimize deep learning models, run machine learning algorithms, and perform complex GPU computations using TPUs. Finally, you'll build and deploy AI applications to production with the help of an end-to-end use case. By the end of this book, you'll have learned how to design and run experiments and be able to discover innovative solutions without worrying about infrastructure, resources, and computing power. What you will learn Understand the basics of cloud computing and explore GCP components Work with the data ingestion and preprocessing techniques in GCP for machine learning Implement machine learning algorithms with Google Cloud AutoML Optimize TensorFlow machine learning with Google Cloud TPUs Get to grips with operationalizing AI on GCP Build an end-to-end machine learning pipeline using Cloud Storage, Cloud Dataflow, and Cloud Datalab Build models from petabytes of structured and semi-structured data using BigQuery ML Who this book is for If you're an artificial intelligence developer, data scientist, machine learning engineer, or deep learning engineer looking to build and deploy smart applications on Google Cloud Platform, you'll find this book useful. A fundamental understanding of basic data processing and machine learning concepts is necessary. Though not mandatory, familiarity with Google Cloud Platform will help you make the most of this book.
Category: Computers

Artificial Intelligence For All

Author : Utpal Chakraborty
ISBN : 9789389328509
Genre : Computers
File Size : 62.90 MB
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Artificial Intelligence, the Revolutionary Transformation that no one can escape DESCRIPTION The book ‘Artificial Intelligence for All’ is a snapshot of AI applications in different industries, society, and everyday life. The book is written considering possibilities AI can bring in the Indian context and considering Indian industries and economy at the center stage. The book starts with describing the race for the supremacy of different countries in the field of Artificial Intelligence that has already taken a great momentum and how AI has managed to influence even mainstream politics and the world leaders. In the subsequent chapters, the book brings in AI applications primarily in the Banking and Finance sectors like Financial Crime detection using AI, Credit Risk Assessment, AI-powered conversational banking, Predictive Analytics, and recommendations in Banking and Finance. In few of the chapters, it goes deep into Machine Learning, Deep Learning, Neural Network and analogy with the human brain for readers who wants to go deeper into the subject, at the same time the content and explanations remain very simple for non-technical readers. How AI is powering the self-driving autonomous vehicles and its implication in the society, job, and the world economy, and it’s transforming the world of home automation, will be another area of interest in the book. A full chapter is dedicated for CIOs and CTOs to consider AI top in their priority list. Applications of AI in Sports are going to be interesting for sports lovers as well as professionals working in the Sports and Computer Games domain. The book also gives special emphasis on Conversational AI like Virtual Assistances and ChatBots and their utility in different sectors. A chapter dedicated for healthcare and medicine provides a complete overview of AI applications in the field and how it’s transforming clinical imaging, personalized medicines, drug discovery, and predictions and forecasting health-related events and many more. Cognitive Cyber Security using AI and Machine Learning would be an area of interest for the readers in the field of Cyber Security. The chapter talks about various modern cognitive cybersecurity tools and techniques to fight with the ever-evolving cybercrime space. ‘Journey of a Digital Traveler’ describes how AI is transforming the travel and tourism industry. The book also includes top 100 business use cases which illustrate possible applications in various fields. KEY FEATURES Provides perfect ‘playground’ for enterprises and institutions globally to develop Artificial Intelligence solutions The world has achieved an enormous amount of technological advancement and skyrocketing progress in mass Digitization, Data Science, and FinTech The gist of the golden era of AI and FinTech AI-powered autonomous vehicles are undoubtedly the future. Autonomous vehicles are the dawn of a whole new lifestyle Using Artificial Intelligence to redefine their products, processes and strategies Providing banking and financial services to the customers through a variety of digital channels A preliminary guide for enterprises and businesses to revisit their AI strategy WHAT WILL YOU LEARN This book is for both technical and non-technical readers, a cutting edge technology like Artificial Intelligence is simplified for all and a genuine effort has been made to democratize it as much as possible. The book will provide insights into the real applications of AI in different industries like health care and medicine, banking and finance, manufacturing, retail, sports, and many more, including how it’s transforming our life which probably many of us are not even aware of. And most importantly how a country like India can be benefited by embracing this groundbreaking technology and the huge opportunities and economic impact that AI can bring. Also, you will get to know how different countries like USA, CHINA, UK, EUROPE, RUSSIA, including INDIA is already in the race of being AI Superpower; because AI is the future and whoever becomes the leader in AI will become the ruler of the world. WHO THIS BOOK IS FOR This book is useful for AI Professionals, Data Scientists...... The content of the book is for both Technical and Non Technical readers who wants to know the applications of AI in different industries. No prior technical or programming experience is required to understand this book. This book can be used as a hand book for Data Scientist and Business SMEs who are in the process of identifying different use cases of Artificial Intelligence in their respective domains. TABLE OF CONTENTS 1. Super Powers of AI – The Leaders and the Contenders 2. AI – The Core Fabric for NextGen Banking 3. How an AI Framework can be a Game-Changer in Your AI Journey 4. Artificial Neural Networks 5. The Next Wave of Automation will Transform our Living Experience 6. Self-Driving Cars – Socio Economic Impact of Autonomous Vehicles 7. How Artificial Intelligence is Transforming the BFSI Sector 43 8. AI Now is a Race Among Startups and Tech Giants 9. AI in the top of priorities for CIOs and CTOs 10. AI in Sports 11. How a Country can be Transformed Using Artificial Intelligence 12. Don’t Underestimate the Power of an AI Chatbot 13. Industry Adoption of Cognitive and Artificial Intelligence 14. Artificial Intelligence – The Biggest Disruptor in the BFSI Industry 15. AI in Healthcare 16. AI in Cyber Security – Cognitive Cyber Defense 17. Be Aware of Cyber Threat 18. AI Revolution in India – National Strategy for AI 19. AI in Tour and Travels – Journey of a Digital Traveler 20. Top 100 Business Use Cases of Artificial Intelligence 21. T Impact of Modern Automation on Employment
Category: Computers

Reinforcement Learning For Cyber Physical Systems

Author : Chong Li
ISBN : 9781351006613
Genre : Computers
File Size : 83.5 MB
Format : PDF
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Reinforcement Learning for Cyber-Physical Systems: with Cybersecurity Case Studies was inspired by recent developments in the fields of reinforcement learning (RL) and cyber-physical systems (CPSs). Rooted in behavioral psychology, RL is one of the primary strands of machine learning. Different from other machine learning algorithms, such as supervised learning and unsupervised learning, the key feature of RL is its unique learning paradigm, i.e., trial-and-error. Combined with the deep neural networks, deep RL become so powerful that many complicated systems can be automatically managed by AI agents at a superhuman level. On the other hand, CPSs are envisioned to revolutionize our society in the near future. Such examples include the emerging smart buildings, intelligent transportation, and electric grids. However, the conventional hand-programming controller in CPSs could neither handle the increasing complexity of the system, nor automatically adapt itself to new situations that it has never encountered before. The problem of how to apply the existing deep RL algorithms, or develop new RL algorithms to enable the real-time adaptive CPSs, remains open. This book aims to establish a linkage between the two domains by systematically introducing RL foundations and algorithms, each supported by one or a few state-of-the-art CPS examples to help readers understand the intuition and usefulness of RL techniques. Features Introduces reinforcement learning, including advanced topics in RL Applies reinforcement learning to cyber-physical systems and cybersecurity Contains state-of-the-art examples and exercises in each chapter Provides two cybersecurity case studies Reinforcement Learning for Cyber-Physical Systems with Cybersecurity Case Studies is an ideal text for graduate students or junior/senior undergraduates in the fields of science, engineering, computer science, or applied mathematics. It would also prove useful to researchers and engineers interested in cybersecurity, RL, and CPS. The only background knowledge required to appreciate the book is a basic knowledge of calculus and probability theory.
Category: Computers

Machine Learning For Red Team Hackers

Author : Dr Emmanuel Tsukerman
ISBN : 9798675540396
Genre :
File Size : 74.25 MB
Format : PDF, Kindle
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Everyone knows that AI and machine learning are the future of penetration testing. Large cybersecurity enterprises talk about hackers automating and smartening their tools; The newspapers report on cybercriminals utilizing voice transfer technology to impersonate CEOs; The media warns us about the implications of DeepFakes in politics and beyond...This book finally teaches you how to use Machine Learning for Penetration Testing.This book will be teaching you, in a hands-on and practical manner, how to use the Machine Learning to perform penetration testing attacks, and how to perform penetration testing attacks ON Machine Learning systems. It will teach you techniques that few hackers or security experts know about.You will learn- how to supercharge your vulnerability fuzzing using Machine Learning.- how to evade Machine Learning malware classifiers.- how to perform adversarial attacks on commercially-available Machine Learning as a Service models.- how to bypass CAPTCHAs using Machine Learning.- how to create Deepfakes.- how to poison, backdoor and steal Machine Learning models.And you will solidify your slick new skills in fun hands-on assignments.
Category:

Securing Your Ai And Machine Learning Systems

Author : Alexander Polyakov
ISBN : OCLC:1142100150
Genre :
File Size : 40.56 MB
Format : PDF, ePub, Mobi
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Design secure AI/ML solutions About This Video Gain practical experience with various open-source tools such as ART (Adversarial Robustness Toolkit) and DeepSec, developed to test machine learning algorithms for security Learn to design secure AI solutions depending on risks that are typical for your application with the help of a unique approach Understand the attacks and different approaches for securing various AI/ML systems In Detail Artificial Intelligence (AI) is literally eating software as more and more solutions become ML-based. Unfortunately, these systems also have vulnerabilities; but, compared to software security, few people are really knowledgeable about this area. If it's impossible to secure AI against cyberattacks, there will be no AI-based technologies, such as self-driving cars, and yet another "AI winter" will soon be on us. This course is almost certainly the first public, online, hands-on introduction to the future perspectives of cybersecurity and adopts a clear and easy-to-follow approach. In this course, you will learn about high-level risks targeting AI/ML systems. You will design specific security tests for image recognition systems and master techniques to test against attacks. You will then learn about various categories of adversarial attacks and how to choose the right defense strategy. By the end of this course, you will be acquainted with various attacks and, more importantly, with the steps that you can take to secure your AI and machine learning systems effectively. For this course, practical experience with Python, machine learning, and deep learning frameworks is assumed, along with some basic math skills.
Category:

The Ai Book

Author : Ivana Bartoletti
ISBN : 9781119551904
Genre : Business & Economics
File Size : 44.16 MB
Format : PDF, Kindle
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Written by prominent thought leaders in the global fintech space, The AI Book aggregates diverse expertise into a single, informative volume and explains what artifical intelligence really means and how it can be used across financial services today. Key industry developments are explained in detail, and critical insights from cutting-edge practitioners offer first-hand information and lessons learned. Coverage includes: · Understanding the AI Portfolio: from machine learning to chatbots, to natural language processing (NLP); a deep dive into the Machine Intelligence Landscape; essentials on core technologies, rethinking enterprise, rethinking industries, rethinking humans; quantum computing and next-generation AI · AI experimentation and embedded usage, and the change in business model, value proposition, organisation, customer and co-worker experiences in today’s Financial Services Industry · The future state of financial services and capital markets – what’s next for the real-world implementation of AITech? · The innovating customer – users are not waiting for the financial services industry to work out how AI can re-shape their sector, profitability and competitiveness · Boardroom issues created and magnified by AI trends, including conduct, regulation & oversight in an algo-driven world, cybersecurity, diversity & inclusion, data privacy, the ‘unbundled corporation’ & the future of work, social responsibility, sustainability, and the new leadership imperatives · Ethical considerations of deploying Al solutions and why explainable Al is so important
Category: Business & Economics

Network Anomaly Detection

Author : Dhruba Kumar Bhattacharyya
ISBN : 9781466582088
Genre : Computers
File Size : 48.14 MB
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With the rapid rise in the ubiquity and sophistication of Internet technology and the accompanying growth in the number of network attacks, network intrusion detection has become increasingly important. Anomaly-based network intrusion detection refers to finding exceptional or nonconforming patterns in network traffic data compared to normal behavior. Finding these anomalies has extensive applications in areas such as cyber security, credit card and insurance fraud detection, and military surveillance for enemy activities. Network Anomaly Detection: A Machine Learning Perspective presents machine learning techniques in depth to help you more effectively detect and counter network intrusion. In this book, you’ll learn about: Network anomalies and vulnerabilities at various layers The pros and cons of various machine learning techniques and algorithms A taxonomy of attacks based on their characteristics and behavior Feature selection algorithms How to assess the accuracy, performance, completeness, timeliness, stability, interoperability, reliability, and other dynamic aspects of a network anomaly detection system Practical tools for launching attacks, capturing packet or flow traffic, extracting features, detecting attacks, and evaluating detection performance Important unresolved issues and research challenges that need to be overcome to provide better protection for networks Examining numerous attacks in detail, the authors look at the tools that intruders use and show how to use this knowledge to protect networks. The book also provides material for hands-on development, so that you can code on a testbed to implement detection methods toward the development of your own intrusion detection system. It offers a thorough introduction to the state of the art in network anomaly detection using machine learning approaches and systems.
Category: Computers

Blockchain Cybersecurity Trust And Privacy

Author : Kim-Kwang Raymond Choo
ISBN : 9783030381813
Genre : Computers
File Size : 29.16 MB
Format : PDF, Kindle
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​This book provides the reader with the most up-to-date knowledge of blockchain in mainstream areas of security, trust, and privacy in the decentralized domain, which is timely and essential (this is due to the fact that the distributed and P2P applications is increasing day-by-day, and the attackers adopt new mechanisms to threaten the security and privacy of the users in those environments). This book also provides the technical information regarding blockchain-oriented software, applications, and tools required for the researcher and developer experts in both computing and software engineering to provide solutions and automated systems against current security, trust and privacy issues in the cyberspace. Cybersecurity, trust and privacy (CTP) are pressing needs for governments, businesses, and individuals, receiving the utmost priority for enforcement and improvement in almost any societies around the globe. Rapid advances, on the other hand, are being made in emerging blockchain technology with broadly diverse applications that promise to better meet business and individual needs. Blockchain as a promising infrastructural technology seems to have the potential to be leveraged in different aspects of cybersecurity promoting decentralized cyberinfrastructure. Blockchain characteristics such as decentralization, verifiability and immutability may revolve current cybersecurity mechanisms for ensuring the authenticity, reliability, and integrity of data. Almost any article on the blockchain points out that the cybersecurity (and its derivatives) could be revitalized if it is supported by blockchain technology. Yet, little is known about factors related to decisions to adopt this technology, and how it can systemically be put into use to remedy current CTP’s issues in the digital world. Topics of interest for this book include but not limited to: Blockchain-based authentication, authorization and accounting mechanisms Applications of blockchain technologies in digital forensic and threat hunting Blockchain-based threat intelligence and threat analytics techniques Formal specification of smart contracts Automated tools for outsmarting smart contracts Security and privacy aspects of blockchain technologies Vulnerabilities of smart contracts Blockchain for securing cyber infrastructure and internet of things networks Blockchain-based cybersecurity education systems This book provides information for security and privacy experts in all the areas of blockchain, cryptocurrency, cybersecurity, forensics, smart contracts, computer systems, computer networks, software engineering, applied artificial intelligence for computer security experts, big data analysts, and decentralized systems. Researchers, scientists and advanced level students working in computer systems, computer networks, artificial intelligence, big data will find this book useful as well.
Category: Computers

Deep Learning For Nlp And Speech Recognition

Author : Uday Kamath
ISBN : 9783030145965
Genre : Computers
File Size : 55.11 MB
Format : PDF, ePub, Docs
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This textbook explains Deep Learning Architecture, with applications to various NLP Tasks, including Document Classification, Machine Translation, Language Modeling, and Speech Recognition. With the widespread adoption of deep learning, natural language processing (NLP),and speech applications in many areas (including Finance, Healthcare, and Government) there is a growing need for one comprehensive resource that maps deep learning techniques to NLP and speech and provides insights into using the tools and libraries for real-world applications. Deep Learning for NLP and Speech Recognition explains recent deep learning methods applicable to NLP and speech, provides state-of-the-art approaches, and offers real-world case studies with code to provide hands-on experience. Many books focus on deep learning theory or deep learning for NLP-specific tasks while others are cookbooks for tools and libraries, but the constant flux of new algorithms, tools, frameworks, and libraries in a rapidly evolving landscape means that there are few available texts that offer the material in this book. The book is organized into three parts, aligning to different groups of readers and their expertise. The three parts are: Machine Learning, NLP, and Speech Introduction The first part has three chapters that introduce readers to the fields of NLP, speech recognition, deep learning and machine learning with basic theory and hands-on case studies using Python-based tools and libraries. Deep Learning Basics The five chapters in the second part introduce deep learning and various topics that are crucial for speech and text processing, including word embeddings, convolutional neural networks, recurrent neural networks and speech recognition basics. Theory, practical tips, state-of-the-art methods, experimentations and analysis in using the methods discussed in theory on real-world tasks. Advanced Deep Learning Techniques for Text and Speech The third part has five chapters that discuss the latest and cutting-edge research in the areas of deep learning that intersect with NLP and speech. Topics including attention mechanisms, memory augmented networks, transfer learning, multi-task learning, domain adaptation, reinforcement learning, and end-to-end deep learning for speech recognition are covered using case studies.
Category: Computers

Hands On System Programming With C

Author : Dr. Rian Quinn
ISBN : 9781789131772
Genre : Computers
File Size : 24.27 MB
Format : PDF, Docs
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A hands-on guide to making system programming with C++ easy Key Features Write system-level code leveraging C++17 Learn the internals of the Linux Application Binary Interface (ABI) and apply it to system programming Explore C++ concurrency to take advantage of server-level constructs Book Description C++ is a general-purpose programming language with a bias toward system programming as it provides ready access to hardware-level resources, efficient compilation, and a versatile approach to higher-level abstractions. This book will help you understand the benefits of system programming with C++17. You will gain a firm understanding of various C, C++, and POSIX standards, as well as their respective system types for both C++ and POSIX. After a brief refresher on C++, Resource Acquisition Is Initialization (RAII), and the new C++ Guideline Support Library (GSL), you will learn to program Linux and Unix systems along with process management. As you progress through the chapters, you will become acquainted with C++'s support for IO. You will then study various memory management methods, including a chapter on allocators and how they benefit system programming. You will also explore how to program file input and output and learn about POSIX sockets. This book will help you get to grips with safely setting up a UDP and TCP server/client. Finally, you will be guided through Unix time interfaces, multithreading, and error handling with C++ exceptions. By the end of this book, you will be comfortable with using C++ to program high-quality systems. What you will learn Understand the benefits of using C++ for system programming Program Linux/Unix systems using C++ Discover the advantages of Resource Acquisition Is Initialization (RAII) Program both console and file input and output Uncover the POSIX socket APIs and understand how to program them Explore advanced system programming topics, such as C++ allocators Use POSIX and C++ threads to program concurrent systems Grasp how C++ can be used to create performant system applications Who this book is for If you are a fresh developer with intermediate knowledge of C++ but little or no knowledge of Unix and Linux system programming, this book will help you learn system programming with C++ in a practical way.
Category: Computers

Hands On Deep Learning For Iot

Author : Mohammad Abdur Razzaque PhD
ISBN : 9781789616064
Genre : Computers
File Size : 39.74 MB
Format : PDF, Docs
Download : 290
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Implement popular deep learning techniques to make your IoT applications smarter Key Features Understand how deep learning facilitates fast and accurate analytics in IoT Build intelligent voice and speech recognition apps in TensorFlow and Chainer Analyze IoT data for making automated decisions and efficient predictions Book Description Artificial Intelligence is growing quickly, which is driven by advancements in neural networks(NN) and deep learning (DL). With an increase in investments in smart cities, smart healthcare, and industrial Internet of Things (IoT), commercialization of IoT will soon be at peak in which massive amounts of data generated by IoT devices need to be processed at scale. Hands-On Deep Learning for IoT will provide deeper insights into IoT data, which will start by introducing how DL fits into the context of making IoT applications smarter. It then covers how to build deep architectures using TensorFlow, Keras, and Chainer for IoT. You’ll learn how to train convolutional neural networks(CNN) to develop applications for image-based road faults detection and smart garbage separation, followed by implementing voice-initiated smart light control and home access mechanisms powered by recurrent neural networks(RNN). You’ll master IoT applications for indoor localization, predictive maintenance, and locating equipment in a large hospital using autoencoders, DeepFi, and LSTM networks. Furthermore, you’ll learn IoT application development for healthcare with IoT security enhanced. By the end of this book, you will have sufficient knowledge need to use deep learning efficiently to power your IoT-based applications for smarter decision making. What you will learn Get acquainted with different neural network architectures and their suitability in IoT Understand how deep learning can improve the predictive power in your IoT solutions Capture and process streaming data for predictive maintenance Select optimal frameworks for image recognition and indoor localization Analyze voice data for speech recognition in IoT applications Develop deep learning-based IoT solutions for healthcare Enhance security in your IoT solutions Visualize analyzed data to uncover insights and perform accurate predictions Who this book is for If you’re an IoT developer, data scientist, or deep learning enthusiast who wants to apply deep learning techniques to build smart IoT applications, this book is for you. Familiarity with machine learning, a basic understanding of the IoT concepts, and some experience in Python programming will help you get the most out of this book.
Category: Computers

Cybersecurity Data Science Projects For Students

Author : Dr Emmanuel Tsukerman
ISBN : 9798675962525
Genre :
File Size : 73.83 MB
Format : PDF, ePub, Docs
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Looking to enter the profession but don't know where to start? Projects for Students will help you on the path to ultimately becoming a badass hacker and security expert who knows how to use machine learning to break and secure systems. In this one-of-its-kind workbook, you will be guided on interesting and fun projects that will allow you to display your skills and growing knowledge. The projects are purposefully designed to be at the perfect balance of challenge (i.e., a beginner can complete them with a bit of patience) and interest so that solving them is sure to impress hiring managers, employers and co-workers. The course uses python and tensorflow for deep learning. It is hands on and each project is immersive several-week experience. Students expected to get their hands dirty with malware, neural networks and DeepFakes!✔ Classify and Detect Malware.✔ Catch Network Intruders.✔ Detect Insider Threats.✔ Break CAPTCHAs.✔ Construct an Evolutionary Fuzzer.✔ Construct Adversarial Attacks on Deep Neural Networks.✔ Impersonate Voice.✔ Create DeepFakes.✔ Generate Fake Reviews.
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