01/07/13

"One dramatic case involved a Canadian man named Walter Nowakowski, who was apparently the first person to be charged in Canada with theft of communications (Canadian Criminal Code Section S.342.1) for accessing the Internet through someone's unsecured Wi-Fi network. Thousands of Canadian “war drivers” do this every day, so why was he singled out? Because of ancillary actions and intent. He was allegedly caught driving the wrong way on a one-way street, naked from the waist down, with laptop in hand, while downloading child pornography through the aforementioned unsecured wireless access point. The police apparently considered his activity egregious enough that they brainstormed for relevant charges and tacked on theft of communications to the many child pornography-related charges.

Similarly, charges involving port scanning are usually reserved for the most egregious cases. Even when paranoid administrators notify the police that they have been scanned, prosecution (or any further action) is exceedingly rare. The fact that a 911 emergency service was involved is likely what motivated prosecutors in the Moulton case. Your author scanned millions of Internet hosts while writing this book and received fewer than ten complaints."

"Nmap Network Scanning" (Gordon “Fyodor” Lyon)

23/06/13

"A government could order a Certificate Authority to produce a malicious certificate for any domain. There is circumstantial evidence that this may happen. And because CAs are located in 52+ countries, there are lots of governments that can do this, including some deeply authoritarian ones. Also, governments could easily perform any of the above network attacks against CAs in other countries."

How secure is HTTPS today? How often is it attacked? (EFF)

04/06/13 - trac: disabling wiki and enabling timeline view as default

This will setup Timeline as default page (other options are: RoadmapModule, BrowserModule, QueryModule, ReportModule, TicketModule):

sed -i 's/WikiModule/TimelineModule/' main.py

And this will disable the wiki (trac.ini):

[components]
trac.wiki.* = disabled

23/05/13

Software isn't about methodologies, languages, or even operating systems. It is about working applications. At Adobe I would have learned the art of building massive applications that generate millions of dollars in revenue. Sure, PostScript wasn't the sexiest application, and it was written in old school C, but it performed a significant and useful task that thousands (if not millions) of people relied on to do their job. There could hardly be a better place to learn the skills of building commercial applications, no matter the tools that were employed at the time. I did learn an important lesson at ObjectSpace. A UML diagram can't push 500 pages per minute through a RIP.
There are two types of people in this industry. Talkers and Doers. ObjectSpace was a company of talkers. Adobe is a company of doers. Adobe took in $430 million in revenue last quarter. ObjectSpace is long bankrupt.
http://www.codinghorror.com/blog/2004/12/it-came-from-planet-architecture.html

21/05/13

14/05/13

05/05/13

 

The algorithms were implemented from scratch and trained on the Reuters articles. For the frequency-rank approach, we additionally used a readily trained implementation of the original algorithm, which we included in the evaluation process as LC4J3. We used each of the algorithms to detect the languages of the previously unused Reuters headlines and the words obtained from dictionaries.
Table 2 shows the accuracies for detecting the language of the Reuters headlines and the dictionary entries across all algorithms and all settings for n. But, the values of LC4J need to be treated carefully: in many cases the algorithm could not detect any language at all. This might be, because the language models provided with the implementation are too sparse for short texts. The values given here are solely based on those cases where language detection was successful. When taking into account the unclassified documents, the accuracy drops drastically to 39.24% for the headlines and to 30.33% for the dictionary words.

(A Comparison of Language Identification Approaches on Short, Query-Style Texts)