Johns Hopkins University
Intrusion Detection Specialization
Johns Hopkins University

Intrusion Detection Specialization

Master Intrusion Detection for Cybersecurity . Gain expertise in intrusion detection systems and advanced network analysis to effectively respond to cybersecurity threats.

Jason Crossland

Instructor: Jason Crossland

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Get in-depth knowledge of a subject
Intermediate level

Recommended experience

4 months
at 13 hours a week
Flexible schedule
Learn at your own pace
Get in-depth knowledge of a subject
Intermediate level

Recommended experience

4 months
at 13 hours a week
Flexible schedule
Learn at your own pace

What you'll learn

  • Explore the principles of intrusion detection systems and their role in enhancing cybersecurity defenses across various environments.

  • Gain hands-on experience with machine learning techniques to improve threat detection and incident response strategies in networks.

  • Develop a comprehensive understanding of Tor networking and its implications for privacy, security, and intrusion detection.

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Taught in English
Recently updated!

November 2024

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Specialization - 3 course series

What you'll learn

  • Understand the roles of HIDS and NIDS, their key components, and applications across cybersecurity contexts.

  • Install and configure IDS solutions on VMs to detect real-time threats in host and network environments.

  • Compare signature-based and anomaly-based detection methods and configure IDS rules accordingly.

  • Use quantitative techniques to assess IDS effectiveness, analyzing data to select optimal solutions for security needs.

Skills you'll gain

Category: Intrusion Detection Fundamentals
Category: Threat Detection Techniques
Category: Quantitative IDS Evaluation
Category: IDS Configuration and Operation
Category: Attack Classification and Analysis

What you'll learn

  • Understand the differences between network situational awareness and traditional NIDS for effective incident detection.

  • Gain proficiency in using GOTS and COTS tools for network packet analysis and troubleshooting networking challenges.

  • Learn to conduct ROC analysis on IDS data and interpret event graphs and precision-recall metrics for better decision-making.

  • Explore the NIST Cybersecurity Framework and SANS Incident Response Cycle to effectively manage and respond to cyber incidents.

Skills you'll gain

Category: Cyber Incident Management
Category: Incident Response Planning
Category: ROC Analysis Interpretation
Category: Practical Firewall Configuration
Category: Network Traffic Analysis

What you'll learn

  • Explore advanced machine learning techniques, including neural networks and clustering, for improved threat detection in cybersecurity.

  • Understand the integration of machine learning algorithms into Intrusion Detection Systems (IDS) for enhanced security measures.

  • Gain knowledge of The Onion Router (ToR) architecture and its applications, focusing on privacy and anonymous communication.

  • Learn to utilize Security Onion tools for effective incident response within high-volume enterprise environments, enhancing cybersecurity strategy.

Skills you'll gain

Category: Integration of ML in IDS
Category: Advanced Machine Learning Techniques
Category: Incident Response with IDS Tools
Category: Data Anonymization and Security
Category: ToR Networking Proficiency

Instructor

Jason Crossland
Johns Hopkins University
6 Courses362 learners

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