The book showcases how advanced cybersecurity and forensic techniques can be applied to various computational issues. It further covers the advanced exploitation tools that are used in the domain of ethical hacking and penetration testing. • Focuses on tools used in performing mobile and SIM forensics, static and dynamic memory analysis, and deep web forensics • Covers advanced tools in the domain of data hiding and steganalysis • Discusses the role and application of artificial intelligence and big data in cybersecurity • Elaborates on the use of advanced cybersecurity and forensics techniques in computational issues • Includes numerous open-source tools such as NMAP, Autopsy, and Wireshark used in the domain of digital forensics The text is primarily written for senior undergraduates, graduate students, and academic researchers, in the fields of computer science, electrical engineering, cybersecurity, and forensics.

This book addresses the topics related to artificial intelligence, the Internet of Things, blockchain technology, and machine learning. It brings together researchers, developers, practitioners, and users interested in cybersecurity and forensics. The first objective is to learn and understand the need for and impact of advanced cybersecurity and forensics and its implementation with multiple smart computational technologies. This objective answers why and how cybersecurity and forensics have evolved as one of the most promising and widely-accepted technologies globally and has widely-accepted applications. The second objective is to learn how to use advanced cybersecurity and forensics practices to answer computational problems where confidentiality, integrity, and availability are essential aspects to handle and answer. This book is structured in such a way so that the field of study is relevant to each reader’s major or interests. It aims to help each reader see the relevance of cybersecurity and forensics to their career or interests. This book intends to encourage researchers to develop novel theories to enrich their scholarly knowledge to achieve sustainable development and foster sustainability. Readers will gain valuable knowledge and insights about smart computing technologies using this exciting book. This book: • Includes detailed applications of cybersecurity and forensics for real-life problems • Addresses the challenges and solutions related to implementing cybersecurity in multiple domains of smart computational technologies • Includes the latest trends and areas of research in cybersecurity and forensics • Offers both quantitative and qualitative assessments of the topics Includes case studies that will be helpful for the researchers Prof. Keshav Kaushik is Assistant Professor in the Department of Systemics, School of Computer Science at the University of Petroleum and Energy Studies, Dehradun, India. Dr. Shubham Tayal is Assistant Professor at SR University, Warangal, India. Dr. Akashdeep Bhardwaj is Professor (Cyber Security & Digital Forensics) at the University of Petroleum & Energy Studies (UPES), Dehradun, India. Dr. Manoj Kumar is Assistant Professor (SG) (SoCS) at the University of Petroleum and Energy Studies, Dehradun, India.

Learn how to use Python for vulnerability scanning, malware analysis, penetration testing, and more KEY FEATURES ● Get familiar with the different aspects of cybersecurity, such as network security, malware analysis, and penetration testing. ● Implement defensive strategies to protect systems, networks, and data from cyber threats. ● Discover advanced offensive techniques for penetration testing, exploiting vulnerabilities, and assessing overall security posture. DESCRIPTION Python is a powerful and versatile programming language that can be used for a wide variety of tasks, including general-purpose applications and specific use cases in cybersecurity. This book is a comprehensive guide to solving simple to moderate complexity problems in cybersecurity using Python. It starts with fundamental issues in reconnaissance and then moves on to the depths of the topics such as forensic analysis, malware and phishing analysis, and working with wireless devices. Furthermore, it also covers defensive and offensive security topics, such as system hardening, discovery and implementation, defensive security techniques, offensive security techniques, and penetration testing. By the end of this book, you will have a strong understanding of how to use Python for cybersecurity and be able to solve problems and create solutions independently. WHAT YOU WILL LEARN ● Learn how to use Python for cyber forensic analysis. ● Explore ways to analyze malware and phishing-based compromises. ● Use network utilities to gather information, monitor network activity, and troubleshoot issues. ● Learn how to extract and analyze hidden information in digital files. ● Examine source code for vulnerabilities and reverse engineering to understand software behavior. WHO THIS BOOK IS FOR The book is for a wide range of people interested in cybersecurity, including professionals, researchers, educators, students, and those considering a career in the field. TABLE OF CONTENTS 1. Getting Started 2. Passive Reconnaissance 3. Active Reconnaissance 4. Development Environment for Advanced Techniques 5. Forensic Analysis 6. Metadata Extraction and Parsing 7. Malware and Phishing Analysis 8. Working with Wireless Devices 9. Working with Network Utilities 10. Source Code Review and Reverse Engineering 11. System Hardening, Discovery, and Implementation 12. Defensive Security Techniques 13. Offensive Security Techniques and Pen Testing

This book explores machine learning (ML) defenses against the many cyberattacks that make our workplaces, schools, private residences, and critical infrastructures vulnerable as a consequence of the dramatic increase in botnets, data ransom, system and network denials of service, sabotage, and data theft attacks. The use of ML techniques for security tasks has been steadily increasing in research and also in practice over the last 10 years. Covering efforts to devise more effective defenses, the book explores security solutions that leverage machine learning (ML) techniques that have recently grown in feasibility thanks to significant advances in ML combined with big data collection and analysis capabilities. Since the use of ML entails understanding which techniques can be best used for specific tasks to ensure comprehensive security, the book provides an overview of the current state of the art of ML techniques for security and a detailed taxonomy of security tasks and corresponding ML techniques that can be used for each task. It also covers challenges for the use of ML for security tasks and outlines research directions. While many recent papers have proposed approaches for specific tasks, such as software security analysis and anomaly detection, these approaches differ in many aspects, such as with respect to the types of features in the model and the dataset used for training the models. In a way that no other available work does, this book provides readers with a comprehensive view of the complex area of ML for security, explains its challenges, and highlights areas for future research. This book is relevant to graduate students in computer science and engineering as well as information systems studies, and will also be useful to researchers and practitioners who work in the area of ML techniques for security tasks.

Dr.S. SanthoshKumar, Assistant Professor, Department of Computer Science, Alagappa University, Karaikudi, Sivaganga, Tamil Nadu, India. Dr.A.Thasil Mohamed, Application Architect, Compunnel, Inc NJ, USA.

Today, the relentless depletion of natural resources has reached a critical juncture, demanding innovative solutions. Advanced Geospatial Practices in Natural Environment Resource Management dives into the intricate tapestry of issues jeopardizing ecosystems. This book systematically dissects the fundamental drivers, traces the historical evolution, and elucidates the underlying causes that have led to this precarious point. From deforestation to pollution, from climate change to habitat destruction, these challenges are multifaceted. By harnessing the power of data-driven decision-making and predictive modeling, this book advocates for a profound shift in the approach to environmental issues. This book also explores the complexities of water, soil, and air-related challenges, offering technically sound solutions that strike a balance between legislative, economic, social, and political considerations. The holistic approach championed in these pages holds the potential to benefit governments, businesses, and communities alike. This book is ideal for a diverse audience, including students, scholars, and researchers, as well as environmental science enthusiasts, geospatial technology professionals, and AI/ML practitioners. Policymakers, environmental engineers, and professionals engaged in governmental and corporate sustainability initiatives will also discover practical solutions to address the pressing challenges.

The main goal of the book is to explore the idea behind data modeling in smart agriculture using information and communication technologies and tools to make agricultural practices more functional, fruitful and profitable. The research in the book looks at the likelihood and level of use of implemented technological components with regard to the adoption of different precision agricultural technologies. To identify the variables affecting farmers’ choices to embrace more precise technology, zero-inflated Poisson and negative binomial count data regression models were utilized. Outcomes from the count data analysis of a random sample of various farm operators show that various aspects, including farm dimension, farmer demographics, soil texture, urban impacts, farmer position of liabilities, and position of the farm in a state, were significantly associated with the approval severity and likelihood of precision farming technologies. Farm management information systems (FMIS) have constantly advanced in complexity as they have incorporated new technology, the most recent of which is the internet. However, few FMIS have fully tapped into the internet’s possibilities, and the newly developing idea of precision agriculture receives little or no support in the FMIS that are now being sold. FMIS for precision agriculture must meet a few more criteria beyond those of regular FMIS, which increases the technological complexity of these systems’ deployment in a number of ways. In order to construct an FMIS that meet these extra needs, the authors here evaluated various cutting-edge web-based methods. The goal was to determine the requirements that precision agriculture placed on FMIS.

This book introduces big data analytics and corresponding applications in smart grids. The characterizations of big data, smart grids as well as a huge amount of data collection are first discussed as a prelude to illustrating the motivation and potential advantages of implementing advanced data analytics in smart grids. Basic concepts and the procedures of typical data analytics for general problems are also discussed. The advanced applications of different data analytics in smart grids are addressed as the main part of this book. By dealing with a huge amount of data from electricity networks, meteorological information system, geographical information system, etc., many benefits can be brought to the existing power system and improve customer service as well as social welfare in the era of big data. However, to advance the applications of big data analytics in real smart grids, many issues such as techniques, awareness, and synergies have to be overcome. This book provides deployment of semantic technologies in data analysis along with the latest applications across the field such as smart grids.

" ADVANCED DIGITAL FORENSICS: Techniques and Technologies for 2024" is the definitive guide for professionals and students who want to delve deeper into digital forensic analysis. This book offers a comprehensive and practical approach, covering everything from fundamentals to the most advanced techniques, with a focus on emerging technologies and threats in 2024. Written by Diego Rodrigues, a renowned consultant and author with extensive experience in market intelligence, technology, and innovation, this book stands out for its updated and practical approach. With 42 international certifications from institutions such as IBM, Google, Microsoft, AWS, Cisco, Boston University, EC-Council, Palo Alto, and META, Rodrigues brings a wealth of knowledge and insights to readers. About the Book: - Solid Fundamentals: Begin with the basic principles of digital forensics, establishing a robust foundation for advancing into more complex topics. - Modern Tools and Techniques: Learn to use the latest and most effective tools, such as Wireshark, Splunk, Cellebrite, and Magnet AXIOM, to capture and analyze critical data. - Forensics in Complex Environments: Explore the challenges and solutions for forensic analysis in modern networks, IoT devices, and cloud environments. - Advanced Threat Analysis: Understand how to investigate sophisticated attacks, including APTs and ransomware, using artificial intelligence and machine learning. - Practical Cases and Real Applications: Apply the knowledge gained in detailed case studies that reflect real-world scenarios and challenges faced by security professionals. - Recommended Practices: Follow best practices to ensure the integrity of evidence, legal compliance, and effectiveness in investigations. "Advanced Digital Forensics: Techniques and Technologies for 2024" is an indispensable resource for anyone looking to excel in the field of cybersecurity and digital forensics. Equipped with updated knowledge and recommended practices, you will be prepared to face the complex challenges of the modern digital world. Get your copy today and elevate your forensic skills to the next level! TAGS Digital Forensics Blockchain Cryptocurrencies Ransomware APTs Machine Learning Artificial Intelligence SIEM EDR Splunk Wireshark Cellebrite Magnet AXIOM Cloud Forensics AWS Azure Google Cloud Mobile Device Forensics IoT Cybersecurity Digital Investigation Network Forensic Analysis Tools Techniques Python Automation Tools SOAR Darktrace Critical Infrastructure Security Malware Analysis Blockchain Explorer Chainalysis Elliptic Audit Logs Data Recovery Techniques Reverse Engineering Cyber Threat Intelligence Tech Writing Storytelling Tech Book 2024 Python Java Linux Kali Linux HTML ASP.NET Ada Assembly Language BASIC Borland Delphi C C# C++ CSS Cobol Compilers DHTML Fortran General HTML Java JavaScript LISP PHP Pascal Perl Prolog RPG Ruby SQL Swift UML Elixir Haskell VBScript Visual Basic XHTML XML XSL Django Flask Ruby on Rails Angular React Vue.js Node.js Laravel Spring Hibernate .NET Core Express.js TensorFlow PyTorch Jupyter Notebook Keras Bootstrap Foundation jQuery SASS LESS Scala Groovy MATLAB R Objective-C Rust Go Kotlin TypeScript Elixir Dart SwiftUI Xamarin React Native NumPy Pandas SciPy Matplotlib Seaborn D3.js OpenCV NLTK PySpark BeautifulSoup Scikit-learn XGBoost CatBoost LightGBM FastAPI Celery Tornado Redis RabbitMQ Kubernetes Docker Jenkins Terraform Ansible Vagrant GitHub GitLab CircleCI Travis CI Linear Regression Logistic Regression Decision Trees Random Forests FastAPI AI ML K-Means Clustering Support Vector Tornado Machines Gradient Boosting Neural Networks LSTMs CNNs GANs ANDROID IOS MACOS WINDOWS Nmap Metasploit Framework Wireshark Aircrack-ng John the Ripper Burp Suite SQLmap Maltego Autopsy Volatility IDA Pro OllyDbg YARA Snort ClamAV iOS Netcat Tcpdump Foremost Cuckoo Sandbox Fierce HTTrack Kismet Hydra Nikto OpenVAS Nessus ZAP Radare2 Binwalk GDB OWASP Amass Dnsenum Dirbuster Wpscan Responder Setoolkit Searchsploit Recon-ng BeEF aws google cloud ibm azure databricks nvidia meta x Power BI IoT CI/CD Hadoop Spark Pandas NumPy Dask SQLAlchemy web scraping mysql big data science openai chatgpt Handler RunOnUiThread()Qiskit Q# Cassandra Bigtable VIRUS MALWARE docker kubernetes Kali Linux Nmap Metasploit Wireshark information security pen test cybersecurity Linux distributions ethical hacking vulnerability analysis system exploration wireless attacks web application security malware analysis social engineering Android iOS Social Engineering Toolkit SET computer science IT professionals cybersecurity careers cybersecurity expertise cybersecurity library cybersecurity training Linux operating systems cybersecurity tools ethical hacking tools security testing penetration test cycle security concepts mobile security cybersecurity fundamentals cybersecurity techniques cybersecurity skills cybersecurity industry global cybersecurity trends Kali Linux tools cybersecurity education cybersecurity innovation penetration test tools cybersecurity best practices global cybersecurity companies cybersecurity solutions IBM Google Microsoft AWS Cisco Oracle cybersecurity consulting cybersecurity framework network security cybersecurity courses cybersecurity tutorials Linux security cybersecurity challenges cybersecurity landscape cloud security cybersecurity threats cybersecurity compliance cybersecurity research cybersecurity technology

Understand the nitty-gritty of Cybersecurity with ease Key FeaturesAlign your security knowledge with industry leading concepts and toolsAcquire required skills and certifications to survive the ever changing market needsLearn from industry experts to analyse, implement, and maintain a robust environmentBook Description It's not a secret that there is a huge talent gap in the cybersecurity industry. Everyone is talking about it including the prestigious Forbes Magazine, Tech Republic, CSO Online, DarkReading, and SC Magazine, among many others. Additionally, Fortune CEO's like Satya Nadella, McAfee's CEO Chris Young, Cisco's CIO Colin Seward along with organizations like ISSA, research firms like Gartner too shine light on it from time to time. This book put together all the possible information with regards to cybersecurity, why you should choose it, the need for cyber security and how can you be part of it and fill the cybersecurity talent gap bit by bit. Starting with the essential understanding of security and its needs, we will move to security domain changes and how artificial intelligence and machine learning are helping to secure systems. Later, this book will walk you through all the skills and tools that everyone who wants to work as security personal need to be aware of. Then, this book will teach readers how to think like an attacker and explore some advanced security methodologies. Lastly, this book will deep dive into how to build practice labs, explore real-world use cases and get acquainted with various cybersecurity certifications. By the end of this book, readers will be well-versed with the security domain and will be capable of making the right choices in the cybersecurity field. What you will learnGet an overview of what cybersecurity is and learn about the various faces of cybersecurity as well as identify domain that suits you bestPlan your transition into cybersecurity in an efficient and effective wayLearn how to build upon your existing skills and experience in order to prepare for your career in cybersecurityWho this book is for This book is targeted to any IT professional who is looking to venture in to the world cyber attacks and threats. Anyone with some understanding or IT infrastructure workflow will benefit from this book. Cybersecurity experts interested in enhancing their skill set will also find this book useful.