I recently took the SANS Security 487, Open-Source Intelligence (OSINT) Gathering and Analysis, course with Micah Hoffman. Now, I need to get started on the associated GIAC Open Source Intelligence (GOSI) exam prep.
When I put my training request in, my manager pointed out I could probably pass the exam without the course. Maybe my manager was right, but I like a good refresher course every once in a while.
I’ve mentioned Justin Seitz’s Automating OSINT before, talking about the Python course. I recently signed up for the Master Course. I only had the money for it due to work reimbursing for me for UMUC CSEC620, and I decided to use a little of that money for self study, not just the next CSEC course.
Work recently sent me to SANS Forensics 578, Cyber Threat Intelligence. This was my first SANS class ever, and it was pretty good. The instance of the class I was sent to was presented by Jake Williams and Rebekah Brown. I think having both of them teach the class was great, because it gave more from the trenches view than having just one of them as an instructor.
For those that don’t know, I’m working on my degree at the University of Maryland University College (UMUC). I just completed the second course in the Masters program I’m in. I just finished CSEC 620 “Human Aspects in Cybersecutiy: Ethics, Legal Issues, and Psychology”
A few months ago, a friend and co-worker asked if I had seen Automating OSINT. I hadn’t, so I went and checked it out and end up signed up for the free webinar. Turns out I had just missed the previous one by a few hours. And had some time to wait before the next one.
I’ve been wanting to expand beyond just bash scripting for most of my career. I tried learning Perl, and then I tried Python. The Google Python class, the MIT Python Class, Learn Python the Hardware, Think Python, Automate the Boring stuff with Python, and buying Python courses from Boing Boing. Problem is I never finished any of them. I think because I lose interest, and have other things to do.
Just so people have an idea of what the class is going to cover:
1. Basic theory of electromagnetic radiation known as radio waves
2. Install SDR# software and configure Dongle on Windows to monitor broadcasts (FM radio, Ham Radio, Other bands).
3. ADBS (Track airplanes, basically how FlightAware does it, with remote sensors people run)
4. Frequency counting (finding what Freqs are popular in an area to do more of item 2).
5. Radio Directional Finding, using RTL-SDR dongles on a Raspberry Pi with a touchscreen and gui software.
5a. (for licensed HAMS) how to turn the Raspberry Pi in to a broadcasting radio
Remember I said you only need 1 of these. These are how they came from Amazon (where I got them all), see last post for links.
RTL-SDR.com: Again I like this because it’s a metal case and came with 2 antenna.
The NooElec in the aluminum case. This is a bare USB stick put in to the block. The picture on Amazon is blue, but what I got was black with silver lettering (I like that look).
The Blue NooElec, like the one in the block case, it comes with a telescoping antenna.
Lastly the NooElec cheap option, with the stick antenna, that doesn’t collapse.
I’ll be teaching an Introductory class at Circle City Con this year, on Software Defined Radio.
Introduction to Software Defined Radio with the RTL-SDR on Windows and the Raspberry Pi 2
4-hour introduction to Software Defined Radio, using the RTL2832U chipset, covering both Microsoft Windows and the Raspberry Pi. We will be going over how to track airplanes, scan radio frequencies to find people talking, and covering a little radio theory. Covering RTL-SDR due to the cost of equipment. A list can be provided to students prior to the course.
Here is the part list you’ll need if you’re taking the class (Note the links got to RTL-SDR.com, Amazon, or Ada Fruit, and I am not associated with either of them). If you can get parts elsewhere that is fine :
All the RTL-SDR dong’es with antennas I’ve gotten so far have had magnetic mounts, and you need a ground plane for them to work right.
So after a class project, someone suggested I learn some R. After digging around a bit on the internet, I found the Coursera Data Science Specialization. It looked good.
The first class was The Data Scientists Toolbox class. It was good. The goal was to get students experience with hands on work in git and with Github. It also got the students ready on the software for R, by installing R and R-Studio.
I had to drop the second class, the R class, due to some issues that came up. I got bogged down during week 2 and wasn’t able to devote any time to the studies. I’ll take the class again when I can actually spend time focusing on it.
So I mentioned this previously as a teaser, but I had an article posted in the Linux Journal. It was based off my independent study at Eastern Michigan University.
It was in the December issue of the Linux Journal. Now it’s posted on their website.
This is related to the talk I am submitting for conferences this year. It has already be accepted to one conference. The talk has a little more information built in to it. For example the experience I had in an environment with heavy wifi coverage compared to home and Eastern Michigan University. A slight design modification. I don’t know yet if I’m going to rebuild using Raspberry Pi B+ or the new Raspberry Pi 2 model B.