Book Online Tickets for Cyber Security, Mumbai. Introduction
 

In today’s Internet-dependent business environment, organizations must link their systems across enterprise-wide and virtual private networks as well as connect mobile users.
 
In this course, you learn how to analyze

Cyber Security

 

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About The Event

Introduction

 

In today’s Internet-dependent business environment, organizations must link their systems across enterprise-wide and virtual private networks as well as connect mobile users.
 
In this course, you learn how to analyze risks to your networks and the steps needed to select and deploy the appropriate countermeasures to reduce your exposure to network threats.
 
“Cyber awareness has become the need of the hour.”
 
 Learning Objective:
  •  Analyze your exposure to security threats and protect your organization’s systems and data
  • Deploy firewalls and data encryption to minimize threats
  • Manage risks emanating from inside the organization and from the Internet
  • Preventing unwanted network access with a personal firewall.
Course Outline
 
Part I – Cyber Crime, Frauds and Risks
 
1. Security goals
  •  Confidentiality
  • Integrity
  • Authentication
  • Authorization
  • Accountability
  • Non repudiation
  • Availability
2. Security Mechanisms
  •  Cryptography
  • Message Authentication Codes and Cryptographic Hash Functions
  • Passwords, Biometrics and Authentication Protocols
  •  Access control (MAC, DAC, RBAC, ABAC)
  • Captchas and resource control
  • Auditing/logging
  • Non-repudiation protocols
3. Attacks (Buffer Overflow, SQL and Command Injection, DNS cache poisoning, X
SS, XSRF, DoS/DDoS, Malware, etc.) and Threat Modeling
 
4. Laws of Security
 
5. Secure coding principles
 
6. Cyber-crime, cyber bullying and cyber terrorism
 
7. Internet Safety and data security
 
Part II. Computer Security from the Data Science Perspective
  1. Unique Challenges of security domain
  2. Data Mining techniques (association rule mining, clustering, anomaly detection) with applications to malware detection
  3. Machine Learning techniques (Decision Trees, Support Vector Machines, Neural Networks, one class learning, semi-supervised learning) with applications to intrusion detection and malware detection.
Part III. Email Masquerade and Social Engineering Attacks
  1.  Fake emails, phishing and spear-phishing – fundamental characteristics
  2. Natural language processing/Natural language generation
  3. Comprehensive detection methods for social engineering attacks
  4. Education and training regimes

Target Audience

Any person with basic knowledge on computer and interest towards Information Security / Cyber Security Domain can attend this workshop.

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