Internet of Things (IoT) Analysis and Security
This course is designed for Networking and Security personnel that need to develop a set of focused packet investigation techniques through study of the IoT networking Protocols using Wireshark and other Open-Source Analysis tools.
Key areas of study include: Specialized and advanced packet capture tips combined with specialized techniques including data traffic reconstruction and viewing. Operation, analysis and threat recognition for a many of the next generation Cloud and IoT technologies including Cloud Computing / Virtualization / IEEE 802.15 Bluetooth / IEEE 802.15.4 ZigBee / IEEE 802.16e WiMAX / Home RF / ZWave / RFID / Infrared / PBCC / 3G / 4G / 5G. Emphasis is placed on Real-World analysis techniques.
Successful completion of this course will provide these individuals with a path-way into the field of both Network and Forensics Analysis.
Recommended Course Prerequisites
For maximum effectiveness, attendees should have at least basic familiarity with TCP/IP networking and basic network infrastructure devices such as Switches, Routers, etc. Attendees will also be required to bring their own laptop.
The emerging technologies of Internet of Things enabled devices are among the recent advances in Networking. Effective analysis and troubleshooting such advanced technologies encompasses the skills of not only capturing data, but also the ability to discern unusual patterns hidden within seemingly normal network traffic. This course will provide the student with a set of investigate and analysis techniques focusing on the use of vendor-neutral, Open-Source Tools such as Wireshark to provide insight into the following areas:
- Specialized and advanced packet capture tips
- Recognition, analysis and threat recognition for a many of the next generation Cloud and IoT technologies including Cloud Computing / Virtualization / IEEE 802.15 Bluetooth / IEEE 802.15.4 ZigBee / IEEE 802.16e WiMAX / Home RF / ZWave / RFID / Infrared / PBCC / 3G / 4G / 5G
- Specialized Analysis techniques including data traffic reconstruction and viewing techniques.
5 days Classroom Instruction
Recommended Class Size