Duration 0.5 Days 3 CPD hours This course is intended for This course is designed for the non-technical end user of computers, mobile devices, networks, and the Internet, to enable you to use technology more securely to minimize digital risks. This course is also designed for you to prepare for the Certified CyberSAFE credential. You can obtain your Certified CyberSAFE certificate by completing the Certified CyberSAFE credential process on the CHOICE platform following the course presentation. Overview In this course, you will identify many of the common risks involved in using conventional end-user technology, as well as ways to use it safely, to protect yourself from those risks. You will: Identify the need for security Secure devices like desktops, laptops, smartphones, and more Use the Internet securely Regardless of your computer experience, this class will help you become more aware of technology ðrelated risks and what you can do to protect yourself and your organization from them. This course will help you to: ? Understand security compliance needs and requirements ? Recognize and avoid phishing and other social engineering ? Recognize and avoid viruses, ransomware, and other malware ? Help ensure data security on computers, mobile devices, networks, the Internet, and in the cloud. In this course, you will use discussions, case studies, and the experiences of your instructor and fellow students to explore the hazards and pitfalls of technology and learn how to use that technology safely and securely. Course includes access to the CyberSAFE assessment. Upon successful completion of the assessment, learners will receive the CyberSAFE credential and digital badge. Identifying the Need for Security Identify Security Compliance Requirements Recognize Social Engineering and Avoid Phishing and other Attacks Securing Devices Maintain Physical Security of Devices Use Passwords for Security Protect Your Data Identify and Mitigate Viruses, Ransomware, and other Malware Use Wireless Devices Securely Using the Internet Securely Browse the Web Safely Use Email Securely Use Social Networking Securely Use Cloud Services Securely Additional course details: Nexus Humans CertNexus CyberSAFE Extended Edition 2019 (CBS-310) training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the CertNexus CyberSAFE Extended Edition 2019 (CBS-310) course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.
Duration 5 Days 30 CPD hours This course is intended for This course is designed for business professionals who leverage data to address business issues. The typical student in this course will have several years of experience with computing technology, including some aptitude in computer programming. However, there is not necessarily a single organizational role that this course targets. A prospective student might be a programmer looking to expand their knowledge of how to guide business decisions by collecting, wrangling, analyzing, and manipulating data through code; or a data analyst with a background in applied math and statistics who wants to take their skills to the next level; or any number of other data-driven situations. Ultimately, the target student is someone who wants to learn how to more effectively extract insights from their work and leverage that insight in addressing business issues, thereby bringing greater value to the business. Overview In this course, you will learn to: Use data science principles to address business issues. Apply the extract, transform, and load (ETL) process to prepare datasets. Use multiple techniques to analyze data and extract valuable insights. Design a machine learning approach to address business issues. Train, tune, and evaluate classification models. Train, tune, and evaluate regression and forecasting models. Train, tune, and evaluate clustering models. Finalize a data science project by presenting models to an audience, putting models into production, and monitoring model performance. For a business to thrive in our data-driven world, it must treat data as one of its most important assets. Data is crucial for understanding where the business is and where it's headed. Not only can data reveal insights, it can also inform?by guiding decisions and influencing day-to-day operations. This calls for a robust workforce of professionals who can analyze, understand, manipulate, and present data within an effective and repeatable process framework. In other words, the business world needs data science practitioners. This course will enable you to bring value to the business by putting data science concepts into practice Addressing Business Issues with Data Science Topic A: Initiate a Data Science Project Topic B: Formulate a Data Science Problem Extracting, Transforming, and Loading Data Topic A: Extract Data Topic B: Transform Data Topic C: Load Data Analyzing Data Topic A: Examine Data Topic B: Explore the Underlying Distribution of Data Topic C: Use Visualizations to Analyze Data Topic D: Preprocess Data Designing a Machine Learning Approach Topic A: Identify Machine Learning Concepts Topic B: Test a Hypothesis Developing Classification Models Topic A: Train and Tune Classification Models Topic B: Evaluate Classification Models Developing Regression Models Topic A: Train and Tune Regression Models Topic B: Evaluate Regression Models Developing Clustering Models Topic A: Train and Tune Clustering Models Topic B: Evaluate Clustering Models Finalizing a Data Science Project Topic A: Communicate Results to Stakeholders Topic B: Demonstrate Models in a Web App Topic C: Implement and Test Production Pipelines
Duration 5 Days 30 CPD hours This course is intended for The skills covered in this course converge on four areas-software development, IT operations, applied math and statistics, and business analysis. Target students for this course should be looking to build upon their knowledge of the data science process so that they can apply AI systems, particularly machine learning models, to business problems. So, the target student is likely a data science practitioner, software developer, or business analyst looking to expand their knowledge of machine learning algorithms and how they can help create intelligent decisionmaking products that bring value to the business. A typical student in this course should have several years of experience with computing technology, including some aptitude in computer programming. This course is also designed to assist students in preparing for the CertNexus Certified Artificial Intelligence (AI) Practitioner (Exam AIP-210) certification Overview In this course, you will develop AI solutions for business problems. You will: Solve a given business problem using AI and ML. Prepare data for use in machine learning. Train, evaluate, and tune a machine learning model. Build linear regression models. Build forecasting models. Build classification models using logistic regression and k -nearest neighbor. Build clustering models. Build classification and regression models using decision trees and random forests. Build classification and regression models using support-vector machines (SVMs). Build artificial neural networks for deep learning. Put machine learning models into operation using automated processes. Maintain machine learning pipelines and models while they are in production Artificial intelligence (AI) and machine learning (ML) have become essential parts of the toolset for many organizations. When used effectively, these tools provide actionable insights that drive critical decisions and enable organizations to create exciting, new, and innovative products and services. This course shows you how to apply various approaches and algorithms to solve business problems through AI and ML, all while following a methodical workflow for developing data-driven solutions. Solving Business Problems Using AI and ML Topic A: Identify AI and ML Solutions for Business Problems Topic B: Formulate a Machine Learning Problem Topic C: Select Approaches to Machine Learning Preparing Data Topic A: Collect Data Topic B: Transform Data Topic C: Engineer Features Topic D: Work with Unstructured Data Training, Evaluating, and Tuning a Machine Learning Model Topic A: Train a Machine Learning Model Topic B: Evaluate and Tune a Machine Learning Model Building Linear Regression Models Topic A: Build Regression Models Using Linear Algebra Topic B: Build Regularized Linear Regression Models Topic C: Build Iterative Linear Regression Models Building Forecasting Models Topic A: Build Univariate Time Series Models Topic B: Build Multivariate Time Series Models Building Classification Models Using Logistic Regression and k-Nearest Neighbor Topic A: Train Binary Classification Models Using Logistic Regression Topic B: Train Binary Classification Models Using k-Nearest Neighbor Topic C: Train Multi-Class Classification Models Topic D: Evaluate Classification Models Topic E: Tune Classification Models Building Clustering Models Topic A: Build k-Means Clustering Models Topic B: Build Hierarchical Clustering Models Building Decision Trees and Random Forests Topic A: Build Decision Tree Models Topic B: Build Random Forest Models Building Support-Vector Machines Topic A: Build SVM Models for Classification Topic B: Build SVM Models for Regression Building Artificial Neural Networks Topic A: Build Multi-Layer Perceptrons (MLP) Topic B: Build Convolutional Neural Networks (CNN) Topic C: Build Recurrent Neural Networks (RNN) Operationalizing Machine Learning Models Topic A: Deploy Machine Learning Models Topic B: Automate the Machine Learning Process with MLOps Topic C: Integrate Models into Machine Learning Systems Maintaining Machine Learning Operations Topic A: Secure Machine Learning Pipelines Topic B: Maintain Models in Production
Duration 0.5 Days 3 CPD hours This course is intended for This course is primarily designed for business leaders, consultants, product and project managers, and other decision-makers who are interested in growing the business by leveraging the power of AI. Other individuals who wish to explore basic AI concepts are also candidates for this course. This course is also designed to assist students in preparing for the CertNexus AIBIZ⢠(Exam AIZ-210) credential. Overview In this course, you will identify ways in which AI can bring significant value to the business. You will: Describe AI fundamentals. Identify the functions of AI in business. Implement business requirements for AI. Artificial intelligence (AI) is not just another technology or process for the business to consider?it is a truly disruptive force, one that delivers an entirely new level of results across business sectors. Even organizations that resist adopting AI will feel its impact. If the organization wants to thrive and survive in this transforming business landscape, it will need to harness the power of AI. This course is designed to help business professionals conquer and move beyond the basics of AI to apply AI concepts for the benefit of the business. It will give you the essential knowledge of AI you'll need to steer the business forward. Lesson 1: AI Fundamentals Topic A: A Brief History of AI Topic B: AI Concepts Lesson 2: Functions of AI in Business Topic A: Improve User Experiences Topic B: Segment Audiences Topic C: Secure Assets Topic D: Optimize Processes Lesson 3: Implementing Business Requirements for AI Topic A: Identify Design Requirements Topic B: Identify Data Requirements Topic C: Identify Risks in Implementing AI Topic D: Develop an AI Strategy
Duration 5 Days 30 CPD hours This course is intended for This course is targeted towards the information technology (IT) professional that has a minimum 1 year IT Security and Networking experience. This course would be ideal for Information System Owners, Security Officers, Ethical Hackers, Information Owners, Penetration Testers, System Owner and Managers as well as Cyber Security Engineers. Overview Upon completion, the Certified Professional Ethical Hacker candidate will be able to competently take the CPEH exam. The CPEH certification training enables students to understand the importance of vulnerability assessments and how to implement counter response along with preventative measures when it comes to a network hack. Security Fundamentals Overview The Growth of Environments and Security Our Motivation? The Goal: Protecting Information! CIA Triad in Detail Approach Security Holistically Security Definitions Definitions Relationships Method: Ping The TCP/IP Stack Which Services Use Which Ports? TCP 3-Way Handshake TCP Flags Malware Types of Malware Types of Malware Cont... Types of Viruses More Malware: Spyware Trojan Horses Back Doors DoS DDoS Packet Sniffers Passive Sniffing Active Sniffing Firewalls, IDS and IPS Firewall ? First Line of Defense IDS ? Second Line of Defense IPS ? Last Line of Defense? Firewalls Firewall Types: (1) Packet Filtering Firewall Types: (2) Proxy Firewalls Firewall Types ? Circuit-Level Proxy Firewall Type of Circuit- Level Proxy ? SOCKS Firewall Types ? Application-Layer Proxy Firewall Types: (3) Stateful Firewall Types: (4) Dynamic Packet-Filtering Firewall Types: (5) Kernel Proxies Firewall Placement Firewall Architecture Types ? Screened Host Multi- or Dual-Homed Screened Subnet Wi-Fi Network Types Wi-Fi Network Types Widely Deployed Standards Standards Comparison 802.11n - MIMO Overview of Database Server Review Access Controls Overview Role of Access Control Definitions More Definitions Categories of Access Controls Physical Controls Logical Controls ?Soft? Controls Security Roles Steps to Granting Access Access Criteria Physical Access Control Mechanisms Biometric System Types Synchronous Token Asynchronous Token Device Memory Cards Smart Card Cryptographic Keys Logical Access Controls OS Access Controls Linux Access Controls Accounts and Groups Password & Shadow File Formats Accounts and Groups Linux and UNIX Permissions Set UID Programs Trust Relationships Review Protocols Protocols Overview OSI ? Application Layer OSI ? Presentation Layer OSI ? Session Layer Transport Layer OSI ? Network Layer OSI ? Data Link OSI ? Physical Layer Protocols at Each OSI Model Layer TCP/IP Suite Port and Protocol Relationship Conceptual Use of Ports UDP versus TCP Protocols ? ARP Protocols ? ICMP Network Service ? DNS SSH Security Protocol SSH Protocols ? SNMP Protocols ? SMTP Packet Sniffers Example Packet Sniffers Review Cryptography Overview Introduction Encryption Cryptographic Definitions Encryption Algorithm Implementation Symmetric Encryption Symmetric Downfalls Symmetric Algorithms Crack Times Asymmetric Encryption Public Key Cryptography Advantages Asymmetric Algorithm Disadvantages Asymmetric Algorithm Examples Key Exchange Symmetric versus Asymmetric Using the Algorithm Types Together Instructor Demonstration Hashing Common Hash Algorithms Birthday Attack Example of a Birthday Attack Generic Hash Demo Instructor Demonstration Security Issues in Hashing Hash Collisions MD5 Collision Creates Rogue Certificate Authority Hybrid Encryption Digital Signatures SSL/TLS SSL Connection Setup SSL Hybrid Encryption SSH IPSec - Network Layer Protection IPSec IPSec Public Key Infrastructure Quantum Cryptography Attack Vectors Network Attacks More Attacks (Cryptanalysis) Review Why Vulnerability Assessments? Overview What is a Vulnerability Assessment? Vulnerability Assessment Benefits of a Vulnerability Assessment What are Vulnerabilities? Security Vulnerability Life Cycle Compliance and Project Scoping The Project Overview Statement Project Overview Statement Assessing Current Network Concerns Vulnerabilities in Networks More Concerns Network Vulnerability Assessment Methodology Network Vulnerability Assessment Methodology Phase I: Data Collection Phase II: Interviews, Information Reviews, and Hands-On Investigation Phase III: Analysis Analysis cont. Risk Management Why Is Risk Management Difficult? Risk Analysis Objectives Putting Together the Team and Components What Is the Value of an Asset? Examples of Some Vulnerabilities that Are Not Always Obvious Categorizing Risks Some Examples of Types of Losses Different Approaches to Analysis Who Uses What? Qualitative Analysis Steps Quantitative Analysis ALE Values Uses ALE Example ARO Values and Their Meaning ALE Calculation Can a Purely Quantitative Analysis Be Accomplished? Comparing Cost and Benefit Countermeasure Criteria Calculating Cost/Benefit Cost of a Countermeasure Can You Get Rid of All Risk? Management?s Response to Identified Risks Liability of Actions Policy Review (Top-Down) Methodology Definitions Policy Types Policies with Different Goals Industry Best Practice Standards Components that Support the Security Policy Policy Contents When Critiquing a Policy Technical (Bottom-Up) Methodology Review Vulnerability Tools of the Trade Vulnerability Scanners Nessus SAINT ? Sample Report Tool: Retina Qualys Guard http://www.qualys.com/products/overview/ Tool: LANguard Microsoft Baseline Analyzer MBSA Scan Report Dealing with Assessment Results Patch Management Options Review Output Analysis and Reports Overview Staying Abreast: Security Alerts Vulnerability Research Sites Nessus SAINT SAINT Reports GFI Languard GFI Reports MBSA MBSA Reports Review Reconnaissance, Enumeration & Scanning Reconnaissance Overview Step One in the Hacking ?Life-Cycle? What Information is Gathered by the Hacker? Passive vs. Active Reconnaissance Footprinting Defined Social Access Social Engineering Techniques Social Networking Sites People Search Engines Internet Archive: The WayBack Machine Footprinting Tools Overview Maltego GUI Johnny.Ihackstuff.com Google (cont.) Domain Name Registration WHOIS Output DNS Databases Using Nslookup Traceroute Operation Web Server Info Tool: Netcraft Introduction to Port Scanning Which Services use Which Ports? Port Scan Tips Port Scans Shou
Duration 2 Days 12 CPD hours This course is intended for Data Protection Officers Data Protection Managers Auditors Legal Compliance Officers Security Manager Information Managers Anyone involved with data protection processes and programs Overview It will show the world that students know privacy laws and regulations and how to apply them, and that students know how to secure your place in the information economy. When students earn a CIPP credential, it means they've gained a foundational understanding of broad global concepts of privacy and data protection law and practice, including: jurisdictional laws, regulations and enforcement models; essential privacy concepts and principals; legal requirements for handling and transferring data and more. The Certified Information Privacy Professional/United States (CIPP/US) program, developed by the International Association of Privacy Professionals (IAPP) - the world?s largest comprehensive global information privacy community and resource, was the first professional certification ever to be offered in information privacy. The CIPP/US credential demonstrates a strong foundation in U.S. privacy laws and regulations and understanding of the legal requirements for the responsible transfer of sensitive personal data to/from the U.S., the EU and other jurisdictions.This course will provide you with a foundational understanding of broad global concepts of privacy and data protection law and practice, including: jurisdictional laws, regulations and enforcement models; essential privacy concepts and principals; legal requirements for handling and transferring data and more. Introduction to privacy Modern history of privacy Introduction to personal information Overview of data protection roles Summary of modern privacy frameworks Structure of U.S. law Structure and sources of U.S. law and relevant terms Governmental bodies having privacy and information security authority General Data Protection Regulation overview (GDPR) High-level overview of the GDPR Significance of the GDPR to U.S. organizations Roles and responsibilities outlined in the law California Consumer Privacy Act of 2018 (CCPA) High-level overview of the newly passed California Consumer Privacy Act of 2018 Scope Consumer rights Business obligations Enforcement Enforcement of U.S. privacy and security laws Distinguishing between criminal and civil liability Comparing federal and state authority Theories of legal liability Enforcement powers and responsibilities of government bodies, such as the FTC and state attorneys general Information management from a U.S. perspective Developing a privacy program Role of privacy professionals and accountability Employee training User preferences Managing vendors Data classification Federal versus state authority Differences between federal and state authority Preemption Healthcare Privacy laws in healthcare Major components of HIPAA Development of HITECH Privacy protections mandated by other significant healthcare laws Financial privacy Goals of financial privacy laws Key concepts of FCRA, FACTA and GLBA Red Flags Rule, Dodd-Frank and consumer protection laws Education Privacy rights and protections under FERPA Recent amendments provided by PPRA and NCLBA Telecommunications and marketing Rules and regulations of telecommunications entities Laws that govern marketing Addressing privacy in the digital advertising Law enforcement and privacy Privacy laws on intercepting communication Telecommunications industry and law enforcement Laws ensuring rights to financial privacy National security and privacy Rules and regulations on intercepting communication Evolution of the law Collaboration of government agencies and private companies to improve cybersecurity Civil litigation and privacy Privacy issues related to litigation Electronic discovery, redaction and protective orders U.S. discovery rules versus foreign laws Legal overview of workplace privacy Federal and state laws regulating and protecting employee privacy Federal laws prohibiting discrimination Privacy before, during and after employment Lifecycle of employee privacy Background screening Employee monitoring Investigating misconduct and termination Antidiscrimination laws ?Bring your own device? policies State data security laws State laws impacting data security Social Security number use regulation Laws governing data destruction Data breach notification laws Scope of state data breach notification law Nine elements of state data breach notification laws Major differences in state laws
Duration 5 Days 30 CPD hours This course is intended for Anyone whose position requires CCSP certificationIndividuals whose responsibilities involve procuring, securing, and managing cloud environments or purchased cloud services Overview In-depth coverage of the six domains required to pass the CCSP exam:Architectural concepts and design requirementsCloud data securityCloud platform and infrastructure securityCloud application securityOperationsLegal and compliance This course is the most comprehensive review of cloud security concepts and industry best practices covering the six domains of the CCSP Common Body of Knowledge (CBK). You will gain knowledge in identifying the types of controls necessary to administer various levels of confidentiality, integrity, and availability, with regard to securing data in the cloud. You will identify the virtual and physical components of the cloud infrastructure with regard to risk management analysis, including tools and techniques necessary for maintaining a secure cloud infrastructure. You will gain an understanding in cloud software assurance and validation, utilizing secure software, and the controls necessary for developing secure cloud environments. You will identify privacy issues and audit processes utilized within a cloud environment, including auditing controls, assurance issues, and the specific reporting attributes. Architectural Concepts and Design Requirements Cloud Data SecurityCloud Platform and Infrastucture Security Cloud Application SecurityOperations Legal and compliance
Duration 3 Days 18 CPD hours This course is intended for Information System Owners Analysts Ethical Hackers ISSOs Cyber Security Managers IT Engineers Overview Upon completion, the Certified Vulnerability Assessor candidate will be able to competently take the exam. This course provides a solid understanding of the tools an IT engineer needs to review an Information System. In this course, you will learn the importance of vulnerability assessments and how they are used to prevent serious cyber break-ins. Lessons include understanding malware and viruses and how they can infiltrate an organization?s network. After you take this course, you will be able to assess a company?s security posture and perform a basic vulnerability test.ÿPlus, you will be able to generate reports to guide new security implementation. Course Outline Why Vulnerability Assessment Vulnerability Types Assessing the Network Assessing Web Servers and Applications Assessing Remote and VPN Services Vulnerability Assessments & Tools of the Trade Output Analysis
Duration 3 Days 18 CPD hours This course is intended for The primary audience for this course are System Administrators and System Architects. Overview Explain the architecture in SAP BusinessObjects Business Intelligence platformConfigure SAP BusinessObjects Business Intelligence platformPerform common server management and administrative tasks in SAP BusinessObjects Business Intelligence platform In this course, students learn how to explain the architecture in the SAP BusinessObjects Business Intelligence platform and perform common server management and administrative tasks in the SAP BusinessObjects Business Intelligence platform. SAP BusinessObjects Business Intelligence Platform Describing the SAP BusinessObjects Business Intelligence Platform Describing the SAP BusinessObjects Business Intelligence Platform Architecture Installation of SAP BusinessObjects Business Intelligence Platform Installing SAP BusinessObjects Business Intelligence Platform: Server-Side Installation Installing SAP BusinessObjects Business Intelligence Platform: Client-Side Installation Server Administration and Management Using the Central Management Console (CMC) Using the Central Configuration Manager (CCM) Web Application Servers Management Configuring Web Application Servers Central Management Server (CMS) Database Managing the Central Management Server (CMS) and System Database Configuring Auditing File Repository Server Management Managing the File Repository Server Using the Repository Diagnostic Tool Adaptive Servers Managing the Adaptive Job Server Managing the Adaptive Processing Server Crystal Reports Servers Demonstrating Information Flows in Crystal Reports Configuring Crystal Reports Managing Crystal Reports Servers Web Intelligence Server Managing Web Intelligence Document Schedules Viewing Web Intelligence Documents Configuring a Web Intelligence Processing Server Configuring a Connection Server Dashboard Servers Configuring Dashboard Servers Managing Dashboard Design Servers Explorer Servers Configuring Explorer Servers Managing Information Spaces Event Servers Configuring Event Servers Managing Event Servers SAP BusinessObjects Business Intelligence Platform 4.1 Monitoring Monitoring the SAP BusinessObjects Business Intelligence Platform 4.1 Using the SAP BusinessObjects Business Intelligence Platform 4.1 Monitoring Dashboard Additional course details: Nexus Humans BOE320 SAP BI Platform - Admin Servers (Win) training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the BOE320 SAP BI Platform - Admin Servers (Win) course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.
Duration 3 Days 18 CPD hours This course is intended for Blockchain Architects Blockchain DevelopersApplication Developers Blockchain System AdministratorsNetwork Security Architects Cyber Security ExpertsIT Professionals w/cyber security experience Overview Those who attend the Security for Blockchain Professionals course and pass the exam certification will have a demonstrated knowledge of:Identifying and differentiating between security threats and attacks on a Blockchain network.Blockchain security methods, best practices, risk mitigation, and more.All known (to date) cyber-attack vectors on the Blockchain.Performing Blockchain network security risk analysis.A complete understanding of Blockchain?s inherent security features and risks.An excellent knowledge of best security practices for Blockchain System/Network Administrators.Demonstrating appropriate Blockchain data safeguarding techniques. This course covers all known aspects of Blockchain security that exist in the Blockchain environment today and provides a detailed overview of all Blockchain security issues, including threats, risk mitigation, node security integrity, confidentiality, best security practices, advanced Blockchain security and more. Fundamental Blockchain Security Cryptography for the Blockchain Hash Functions Public Key Cryptography Elliptic Curve Cryptography A Brief Introduction to Blockchain The Blocks The Chains The Network Promises of the Blockchain Blockchain Security Assumptions Digital Signature Security Hash Function Security Limitations of Basic Blockchain Security Public Key Cryptography Review Real-Life Public Key Protection Cryptography and Quantum Computers Lab 1 (Tentative) Finding Hash Function Collisions Reversible hash function Hash function with poor non-locality Hash function with small search space Breaking Public Key Cryptography Brute Forcing a Short Private Key Brute Forcing a Poorly-Chosen Private Key Consensus in the Blockchain Blockchain Consensus and Byzantine Generals Blockchain Networking Review Byzantine Generals Problem Relation to Blockchain Byzantine Fault Tolerance Introduction to Blockchain Consensus Security Blockchain Consensus Breakthrough Proof of Work What is Proof of Work? How does Proof of Work Solve BGP? Proof of Work Security Assumptions Attacking Proof of Work Proof of Stake What is Proof of Stake? How does Proof of Stake Solve BGP? Proof of Stake Security Assumptions Attacking Proof of Stake General Attacks on Blockchain Consensus Other Blockchain Consensus Algorithms Lab 2 (Tentative) Attacking Proof of Work Performing a 51% Attack Performing a Selfish Mining Attack Attacking Proof of Stake Performing a XX% Attack Performing a Long-Range Attack Malleable Transaction Attacks Advanced Blockchain Security Mechanisms Architectural Security Measures Permissioned Blockchains Checkpointing Advanced Cryptographic Solutions Multiparty Signatures Zero-Knowledge Proofs Stealth Addresses Ring Signatures Confidential Transactions Lab 3 (Tentative) Permissioned Blockchains 51% on a Checkpointed Blockchain Data mining on a blockchain with/without stealth addresses Zero-Knowledge Proof Simulation Trying to fake knowledge of a ZKP Module 4: Blockchain for Business Introduction to Ethereum Security What is Ethereum Consensus in Ethereum Smart Contracts in Ethereum Ethereum Security Pros and Cons of Ethereum Blockchains Introduction to Hyperledger Security What is Hyperledger Consensus in Hyperledger Smart Contracts in Hyperledger Hyperledger Security Pros and Cons of Hyperledger Blockchains Introduction to Corda Security What is Corda Consensus in Corda Smart Contracts in Corda Corda Security Pros and Cons of Corda Blockchains Lab 4 Blockchain Risk Assessment What are the Risks of the Blockchain? Information Security Information Sensitivity Data being placed on blockchain Risks of disclosure Regulatory Requirements Data encryption Data control PII protection Blockchain Architectural Design Public and Private Blockchains Open and Permissioned Blockchains Choosing a Blockchain Architecture Lab 5 Exploring public/private open/permissioned blockchains? Basic Blockchain Security Blockchain Architecture User Security Protecting Private Keys Malware Update Node Security Configuring MSPs Network Security Lab 6 (TBD) Smart Contract Security Introduction to Smart Contracts Smart Contract Security Considerations Turing-Complete Lifetime External Software Smart Contract Code Auditing Difficulties Techniques Tools Lab 7 (Tentative) Try a couple of smart contract code auditing tool against different contracts with built-in vulnerabilities Module 8: Security Implementing Business Blockchains Ethereum Best Practices Hyperledger Best Practices Corda Best Practices Lab 8 Network-Level Vulnerabilities and Attacks Introduction to Blockchain Network Attacks 51% Attacks Denial of Service Attacks Eclipse Attacks Routing Attacks Sybil Attacks Lab 9 Perform different network-level attacks System-Level Vulnerabilities and Attacks Introduction to Blockchain System Vulnerabilities The Bitcoin Hack The Verge Hack The EOS Vulnerability Lab 10 Smart Contract Vulnerabilities and Attacks Introduction to Common Smart Contract Vulnerabilities Reentrancy Access Control Arithmetic Unchecked Return Values Denial of Service Bad Randomness Race Conditions Timestamp Dependence Short Addresses Lab 11 Exploiting vulnerable smart contracts Security of Alternative DLT Architectures What Are Alternative DLT Architectures? Introduction to Directed Acyclic Graphs (DAGs) DAGs vs. Blockchains Advantages of DAGs DAG Vulnerabilities and Security Lab 12 Exploring a DAG network