Blog

Last week we have discussed some of the emerging methods of communication on the early Internet. We covered the means of communication where the primary target was conveying information to single or multiple recipients and where - at least theoretically - the primary communication intent was work- or research-related. Today we see quite the opposite trend where the communication platforms are originally envisioned for free time communication and only later on the companies try to leverage them for some possible profit. If we look at the dawn of time, we can see that this is nothing new.

It has been a busy year here at Trustica and while typically people use the occasion of the beginning of a new year to reflect on what has happened in the last one, I would like to look further back in time and write about some highlights in the history of Internet messaging. It turns out, the history of communication over interconnected data networks has a lot to do with what we have been up to for almost a year now and we have learned a lot and I think some parts are really worth sharing.

I was really keen to attend one of the (ISC)2 SecureEvents: The SecureCEE Conference 2016 in Prague. Read on if you are interested in current security trends!

As our latest project has progressed we encountered a strange obstacle: there is no portable way to determine file inode number in Racket. That would not be much of a problem, but as we tried to dynamically link stat-like functions from libc using ffi, we found that each platform and glibc version has different ABI - including the sizes of various stat structure fields. So we dived into writing extensions in the C programming language.

In one of our recent projects we are working hard to be able to detect filesystem changes that may indicate substantiate increase in the number of encrypted files. There may be several hints that given file contains encrypted data and one of the most prominent properties of such file is its high entropy. But how to measure it? And how to measure it effectively? In this post we will look into a relatively simple statistical analysis of file data that can shed light on its entropy. The only problem here is there are no readily available software solutions to do this.