radius

Progress has slowed a bit on the fraud management system… other priorities have come up over the last month or so but here’s a new walk though.  The backend hasn’t changed much.  What has changed is the hardware requirements.  When I started this project I had no idea how much processing power or space or IO was going to be required so I built the system in such a way that it could be easily scaled at several points.  As it turns out.. for this size of a network (about 250k customers) that was unnecessary.

It’s been about a month since I posted the initial overview and I thought it would be good to post an update of the progress. While I’ve not been able to devote 100% to this project over the last month there have been some significant improvements.  The most visible ones are to the web interface.  I’ve added a very flexible application level authorization system.  I’ve also added an interface for managing one of the key inputs to the system with a protective 2 level approval process. I’ve also been tweaking the scoring system to better handle corner cases as I’ve seen them. Still plenty of work to be done but it’s starting to take shape.   For the overview of this system check out my first post about it.  Screen shots after the break.

I’ve been working on a big new project since just before the new year and it’s starting to take shape and generate useful results.   I can’t give away too many details on how exactly it works but I wanted to share this with some of you who are also working in telecom.  I was asked to develop a real-time system to identify toll fraud that would work for our entire voip carrier network that currently originates calls from 19 different countries for both residential, SMB, and wireless.  For those who don’t know.. I spent a year working for another telecom software company helping to run and debug a call mediation and rating platform for a tier2 carrier.  This experience was useful in that I was able to quickly develop a scalable, distributed processing framework while avoiding the cumbersome overhead I’ve observed in other systems.  Continue after the jump for more details…

As part of a larger project I needed to generate real time radius records from the CDR accounting files of several cluster pairs of Broadsoft application servers. So I wrote a perl script to do just that. It maps the CDR fields to radius attribs and encodes the accounting packet using the Net::Radius::Packet CPAN module. In my case I’m using the Radiator radius server from OSC Software on the other end with lots of custom ‘hook code’ to clean up and store the call data coming off our network into a Postgresql database.