AI-Enhanced Network & Packet Analysis

This course teaches students the fundamental concepts, methodologies, and tools necessary to analyze network traffic for the purposes of intrusion and threat detection, network defense, and low-profile incident investigation — now enhanced with AI-driven insights. While performing incident response or investigations, students will learn to determine where malicious activity is occurring and take their analytical skills to the next level.

The hands-on course begins with the role of network packet analysis in Computer Network Operations (CNO). Students learn core TCP/IP and Ethernet concepts and perform packet capture and analysis of self-generated network traffic, using tcpdump, tshark, and Wireshark, alongside emerging AI-assisted methods that accelerate anomaly detection, protocol identification, and data correlation. These include the use of large language models (LLMs) for summarization and triage, lightweight ML models for anomaly detection, and AI-assisted rule/signature generation to enhance detection engineering and streamline analysis workflows.

The course emphasizes both human expertise and AI augmentation, giving students practical experience in automated log analysis, packet classification models, and the integration of AI-based assistants into packet forensics operations. By combining foundational networking knowledge with AI-driven analytics, students develop the ability to interpret complex network behaviors with speed, accuracy, and critical reasoning.

Throughout the course, students will examine real packet captures illustrating exploits, reconnaissance techniques, and advanced network attacks. Students will practice traditional command-line filtering and GUI analysis, then apply AI tools to automatically extract indicators, summarize multi-session attacks, prioritize alerts, and assist in crafting BPF/Wireshark filters and IDS rules.

The course culminates in a capstone exercise in which students combine human analysis with AI-assisted workflows to detect, explain, and document complex network threats and breaches.

Duration

4-5 days

PREREQUISITES

• CompTIA Network+ certification or equivalent knowledge
• Working knowledge of TCP/IP fundamentals or equivalent experience (one year recommended)
• CCNA is recommended but not required
• Experience with basic Linux command line functions
• Working knowledge of information assurance and network security principles.

Upon completion of this course, the student will be able to:

• Analyze network traffic to understand application behavior and communication patterns.
• Identify protocol mechanics and anomalous protocol usage within packet captures.
• Use tcpdump, BPF, and tshark for deterministic captures and filtering.
• Operate Wireshark for deep packet inspection and protocol dissection.
• Use AI tools (LLMs and ML models) to accelerate triage: extract IOCs, summarize session activity, and prioritize suspicious flows.
• Develop and validate detection logic (BPF expressions, Suricata/Snort rules, Zeek scripts) assisted by AI drafts and refine them by testing against captures.
• Evaluate the reliability, bias, and limitations of AI outputs and perform human validation of AI-produced analysis.
• Produce professional incident writeups that combine human findings with verifiable AI assistance (including documenting prompts and model versions used).

Register 21 days before class start date and save 10%! Enter discount code EARLY10 during registration.

Register 21 days before class start date and save $250! Enter discount code EARLY250 during registration.

Is there a discount available for current students?

UMBC students and alumni, as well as students who have previously taken a public training course with UMBC Training Centers are eligible for a 10% discount, capped at $250. Please provide a copy of your UMBC student ID or an unofficial transcript or the name of the UMBC Training Centers course you have completed. Asynchronous courses are excluded from this offer.

What is the cancellation and refund policy?

Student will receive a refund of paid registration fees only if UMBC Training Centers receives a notice of cancellation at least 10 business days prior to the class start date for classes or the exam date for exams.