Reports rightly focus on the attacks themselves and their effect on the Wikileaks site, rather than the BotNets behind many DDoS events or the other malicious ends to which they can be put.  However, it is interesting  that the technology being used to hinder the Wikileaks distribution is the same used by criminals to gather private information on a massive scale, for release to the highest bidder.

In early 2009  some researchers at the University of California, Santa Barbara managed to take over part of a BotNet being used to steal private information such as passwords and credit card numbers.  You can see Richard A. Kemmerer, a member of the research group, explaining the 10-day exploit in this Google talk.  As part of the experiment, the group analysed encrypted passwords stolen by the BotNet to see how easily each user’s data could be cracked.  They found that of 173,686 unique passwords discovered, just under 58% could be cracked within 24 hours (56k  -  about 32%  -  were able to be cracked within 65 minutes).  Further analysis also revealed that 28% of people reused the same password on multiple domains.  So, there are some relatively easy pickings for BotNet creators to harvest and on-sell.

The results aren’t particularly surprising; we are a pretty lazy bunch in general and there are so many points online and offline at which passwords are required to access content.  The effort required to generate different memorable, but secure, passwords is high.  Yet, the risks associated with not having strong passwords are rising as we move more of our digital lives to the cloud.  So, here are a couple of ideas I’ve gathered for generating memorable, strong passwords with minimal effort.

• Create an acronym from a phrase.  For instance, “Please Let Me In To Twitter So I Can See Some Tweets” would translate to “plmittsicsst”.  You can vary the phrase easily enough for different sites.  When combined with symbol or number replacement and a sprinkling of upper-case letters, this can generate strong passwords quickly.  So, our string above could become “Plm!tt%!c%%T” if we capitalise the first and last letters and replace i and s with the shift symbols for 1 and 5 (which look like i and s).
• Create a password base that you use everywhere, then mix in a site-specific password with that.  For example, you could take the first and last two characters of the street you grew up on along with the last two digits of your old student ID to get a base (e.g., “adde32″) then append the reverse of the consonants from the site name to this (e.g., “rttwt” for twitter).  Sprinkle with symbol replacement and you get “$dd#32rttwt”.  For good measure you can add a prefix and suffix symbol to add extra security “#$dd#32rttwt#”
• Use a password manager that generates random passwords :)

You can test out different approaches to get a feel for how secure the passwords you generate are at this site: http://howsecureismypassword.net/.  Obviously, you shouldn’t put any of your real passwords in, but you can use it to test out ideas using fake details or phrases.

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It is from the same article (Ehrenberg, Feb 1992, The Problem of Numeracy, AdMap), but this time relates to television programme viewership.  The first table presents detailed correlations for responses to the question ‘I really like to watch programme x‘ across a range of programmes and two channels (ITV and BBC).

Apart from an obvious diagonal line of 1.000 in the table (of course each programmes’ rating correlates perfectly with itself), there isn’t much else you can take out from it.  The next table renders the data a little more readable by introducing rounding to one decimal place, discarding the redundant leading zeros and disposing of the meaningless 1.000 diagonal.

And with a little more thought to row order, spacing and the key data for presentation (i.e., do we really need channel?), we get to the following:

Those familiar with television in the UK will now see that people who like to watch one sport programme also like to watch other sports programmes, particularly if they are ’round up’ type shows.  They don’t, however, like news or current events programmes so much.  A similar pattern occurs for current event watchers, but the programmes within that cluster have slightly lower correlations, meaning viewership is less likely to be homogeneous amongst that group.  If you are an advertiser or producer, this is useful stuff to know because it will give you an idea of the reach of, and competition around, a certain programme.  And you are more likely to understand this if the data is presented in a clear and concise way.

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This will have been partly due to my lack of familiarity with the dataset; the person responsible for sales for the organisation would have  brought a wealth of historic knowledge to the data that may have enabled them to quickly see discrepancies or commonalities in the charts.  However, there was also an element of ‘too much’ information.  There is only so much we humans can hold in our short term memory before we become overwhelmed and our ability to do mental calculations or comparisons is compromised.  This is why it is critical for anyone presenting data to consider not only the level of detail required, but also how the information should be delivered for quick and clear consumption.

Marketing scientist Andrew Ehrenberg spent a fair amount of time on these issues and was a strong advocate of data reduction (which relates to the idea that much success in research relies on the discovery of patterns in data, and that this process is aided by its presentation in simple tables).  In fact, Ehrenberg wrote a book on the subject that is freely downloadable from the EmpGens Journal.

Here is an example of Ehrenberg’s approach.  I’ve reproduced the tables from a four page article of his in Admap from 1992 titled ‘The Problem of Numeracy‘.  First up is a table not optimised for human consumption.  Try to pick out some noteworthy patterns.

Now try again, using a modified presentation of the same data:

The rounding, averages and different row ordering (population size, rather than alphabet) all make it easier to quickly understand the data.  We can now see, for instance, that most regions saw a dip in Q3, that Leeds and Edinburgh have seen strong growth in Q4, and that Leeds is consistently punching above its weight in per capita sales.  We can also easily answer comparative questions like ‘how much larger was Edinburgh than Swansea over the year‘ (about 2.5x), which were much harder to do from the first table.

People don’t often think of treating tables like other design elements in a user interface.  Yet as the example shows, they can fairly easily be tweaked to great effect.  And, when presented clearly, a table can convey more information in a short space of time than a series of charts.

The service needs to overcome the chicken-and-egg problem of not having the large user-base required for the service to be of most benefit.  It will also be competing with other nascent options like Facebook credits, which I imagine will soon expand beyond the confines of the Facebook platform, and Amazon’s Flexible Payments Service.

However, if they manage to get beyond beta I’d love to see what the usage stats turn out like.

• How many times would people give to the same content creators within a given period?
• Would sites with high user repeat visit rates do better than those with low repeat rates but high traffic?
• What phrases and presentations of the flattr button would generate the most gifts?

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I spotted some Wellington City Council contractors erecting a solution the other day:

I guess putting up a barrier is much cheaper than paving the goat-track!  The day after I took this there was someone churning up the ground with a rotary hoe, so it’ll be back to a grassed area in no time.

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Were we to buy some nice glasses, I suspect we’d draw upon a number of excuses to rationalise our decision, the key two being:

1. They look and feel really nice, and
2. Experts say the right glasses enhance the flavour of the wine.

I have no problem at all with the first excuse.  It’s the second one that sets off my bullshit meter, because ‘experts’ are often wrong and I’ve not actually seen any evidence that the assertion is true.

To test whether wine glasses enhance the taste of a wine, you’d have to do some blind testing.  That is, the wine tasters would have to be blind to which glass they were quaffing or sniffing from when they gave their judgements.  Pretty much all of the tests I managed to find in my trawl of the web were unblinded (see here for a recent NZHerald ‘test’), so the participants may have been influenced by the look of the glass itself rather than any true structural effects of the vessel.

I did manage to find one reference to research using blind tests, in a section of Wine Science from 2005 by Dr Ron Jackson:

…shape does affect the intensity of the wine’s fragrance – those possessing a wide base and narrow neck enhance the perception of the wine’s aroma.  However, the differences detected from a variation of shapes on the wide–narrow theme were marginal.  Published evidence does not support the view that particular shapes uniquely enhance the character of specific wines.

That particular shapes are not uniquely suited for tasting particular wines does not mean that they do not affect perception or, indeed, aesthetic pleasure.  Science has amply confirmed that visual and psychological influences often have a greater effect on what we perceive than the more subtle sensory data provided by taste and smell.

I doubt the goat track is much shorter than the paved alternative, yet there must be some perceived directness about it for a good number of people.  Perhaps it was first formed by those running to catch a green pedestrian light, like the guys in the first shot.  Whatever the case the path now seems to have a life of its own.  Enough pedestrians have taken the dirt route just to get to the waiting point that the entire area next to it has been completely stripped of grass.

Indeed, I must admit I found the dirt path choice quite compelling even though I wasn’t in a rush and could see the other pedestrian light was already orange.  It was probably the social proof of the well-worn track (“others seem to think it would be quicker, so it probably is”) along with the direct line-of-site to the other crossing that provided the appeal. And the fact that the path was already bare meant there would be no guilt in walking on the grass.

What’s bizzare is that we’ll choose that route even though it doesn’t really save us any material time.  In fact, even if it did save time, in most cases it would mean we just get to a waiting point quicker!

This ‘gravitational pull’ of shortcuts is frequently exploited.  Just look at the ads for 30-day weight-loss programs and get-rich quick schemes.  Even when there is little for us to gain we’ll take the short route so as to not miss out on just the potential for a mental, physical, or financial bargain.  It is unfortunate that the designers of this particular pedestrian crossing didn’t take it into account.  It might have made for a little less mud in winter.

Still, it gave me something to write about!

Here’s the area in Google Street View if you want to talk a stroll around it yourself…

View Larger Map

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Although many of his examples are interesting in themselves, it is worth noting that a number draw upon core psychological principles first put together 25 years ago by Robert Cialdini in a book titled Influence.  Cialdini studied how social norms and ingrained behaviours have a massive influence on our responses to the various stimuli we are presented with on a daily basis.  He grouped them into six general categories:

You can read a little more about each of these here, but it really is worth taking the time to read the book (most libraries will have it).  It presents both the underlying motivators along with specific examples of their expression in practice, so it is more useful than hearing only the examples themselves, which don’t necessarily lend themselves to application in a range of different domains.

Cialdini also recently co-authored a book titled Yes!, which presents summaries for over 50 scientific studies relating more-or-less to the six categories above.  It is a fascinating read.  Here are a couple of the findings:

• Tips increase by up to 23% when waiters give mints to their customers directly, rather than letting them pick the mints up from a bowl at the counter.  [an example of reciprocity]
• A hotel increased guest towel reuse rates (an environmentally friendly action) by 33% simply by changing the wording of the call-to-action message on a sign in the bathroom.  The most successful message suggested that others who had stayed in the same room recently had reused their towels. [an example of social proof, and also liking - we are influenced more by those who share attributes with us]
• Asking people to predict whether or not they will go out and vote actually increases the chance they will go out and vote (by about 25% points in the study cited).  [an example of social desirability bias combined with commitment and consistency]

There are many other examples in Yes! that translate the six general principles into practice, so you are bound to find some inspiration for mixing it up and applying the principles yourself.

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