Glomacs Institute

Learning Objectives

• What is Cyber Security and what are the objectives?
• Understand the concept of Confidentiality, Integrity, Availability and Cyber Security Risk Management
• Careers in Cyber Security
• Skills needed to succeed in Cyber Security

Learning Objectives

• • Understand Virtualization Technologies
  • Client-Side/Desktop Virtualization Technologies: Oracle VirtualBox (Free), VMWare Fusion (Paid), Windows 10 Hyper-V (Comes with Windows)
  • Building Virtual Machines with VirtualBox
  • Virtualization Disk Formats: OVF – Open Virtualization Format , OVA – Open Virtualization Archive/Appliance
  • Installing Kali Linux, Ubuntu Linux and Windows and networking the VMs

Learning Objectives

• • Understand Cryptography and its use in Security as well as attacks on Cryptosystems
    • Symmetric/Asymmetric Encryption
    • Hash Functions, Digital Signatures, Hashing and Salting,
    • Public Key Infrastructures, Digital Certificates and Security
    • Steganography
    • Attacks on Cryptosystems
    • Generating and Verifying hashes
    • Signing a file with digital signatures
      • GPG, HMAC, SHA sum etc

Learning Objectives

• • Understand Computer Network Architecture and Security Analyses
    • Introduction to Computer Networks
      • Open Systems Interconnect (OSI) layered model
      • TCP/IP Networking
      • Domain Name System
      • Transport Layer Security (TLS)
    • Common Network Threats and Attacks
      • ARP Poisoning, WEP Attacks, DoS and DDoS, Man-in-the-Middle attacks etc.
    • Network Security Tools and Usage
      • Nmap, dig, TLS Audit, Wireshark, Suricata/Snort
    • Network Reconnaissance
      • Network Service Discovery
      • Banner Grabbing
      • Identify the Network Routes in the System
    • DNS lookup and reverse lookup
    • Network Path tracing
    • Network Sniffing Analysis
    • Network scanning
    • Enumeration

• Learning Objectives

  • • Understand Application Security Issues
      • Understanding OWASP Top 10 with specific focus on
        • Cross-Site Scripting (XSS)
        • SQL Injection (SQLi)
        • Cross-Site Request Forgery CSRF
      • Penetration Testing Web Applications with OWASP ZAP and Burp Suite
      • Finding Secrets in Source Code with CheckMate
      • Application Fuzzing
      • Debugging and Reverse Engineering to find security flaws
      • Static Source Code Security Analyses

Learning Objectives

• Understand the roles and responsibility and value of Threat Intelligence to Security
  • Open-Source Intelligence (OSINT) and use of recon-ng
  • Google Hacking
  • Anonymity-Preserving Research with The Onion Routing (Tor) protocol
  • Dark Web Research
  • MITRE ATT&CK Framework
  • Reconnaissance
  • Insider Threats

Learning Objectives

• • Security Monitoring and Threat Hunting
    • Threat Hunting and Indicators of Compromise (IoCs)
    • YARA rules, tools and techniques
    • Use of Wazuh, ELK, OSquery, OSSEC, GRR Rapid Response and other tools
  • Conducting Incident Response
    • GRR Rapid Response
    • Malware Forensics
    • Leading Incident Response efforts

Learning Objectives

• • Understand Vulnerability Scanning and Management as a core Security function
    • Vulnerability Scanning with Nessus and OpenVas
    • Vulnerability Scoring with CVSS
    • Security Patching and Patch Management
    • Systems Security Hardening
      • SCAP and CIS Benchmarks
      • User OpenScap and CIS-CAT Lite to verify compliance of servers to security hardening standards
      • Policy Tailoring files

Learning Objectives

• • Moving into a Cyber Security Career
    • Soft skills
    • Training, Conferences and Certifications
    • Publishing your results and engaging the community to develop a portfolio and gain visibility and recognition
    • Interview Techniques
  • Advancing in Cyber Security
    • Growing into other areas of Cyber Security
    • Gaining leadership skills and qualities
    • Adding value to the business
    • Speaking to the executives and the board

• Learning Objectives
• What is Deep Learning
• The Neuron
• The Activation Function
• A Simple Perceptron
• How does Neural Network Work?
• How does Neural Network Learn?
• Feed-Forward Neural Network
• Gradient Descent and Stochastic Gradient Descent
• Backpropagation
• Step-by-Step how to build an Artificial Neural Network
• Convolution Neural Network (CNN)
• Recurrent Neural Network (RNN) and Long Short Term Memory (LSTM)
• Hands-on Deep Learning Projects
• Key Takeaways
•