Can Long Term Predictive Model be Used to Prevent Crime?

“Prison data, court files show link between school truancy and crime” 

 Chicago Tribune News Feb 19, 2013

http://articles.chicagotribune.com/2013-02-19/news/ct-met-prison-truancy-20130219_1_prison-data-dropouts-school

The forming of a criminal

1 Recruitment of members

2 Intimidating to retain new members

3 Initiation of the gang member

4 Progressively more aggressive crimes

5 Homicide to protect or gain territories

Are Homicide committed primarily by gang members and by mentally disturbed? For a better discussion, let’s focus on the gang factor here.

Usually gang members are recruited at a young age, entrenched via initiation phases. The activities that harden them starts from petty crime such as auto theft, graduating to sexual assault, and to the ultimate power play - homicide. So,

-        Can we look at which crimes are happening today to predict which will occur 6 months or 6 years from now?

-           Can we intervene when these indicators are starting to show?

-           Can we provide a concrete set of data to guide action plans for schools and civic organizations?

 Can Long Term Prediction help prevent homicides?

Just like the production of a computing program, it is far less expensive to fix a bug in the software while coding than to fix this bug after production. The cost of criminal rehabilitation is much higher than that necessary to ensure a child gets the proper guidance to steer away from a life of crime.

Long term prediction can be more effective by providing guidance through less expensive interventions. 

Evidence of Result from Long Term Prediction in other industries

Let’s look at the power utility industries in their forecasting methods. They are doing a great job in supplying power and I believe from their results, there are lessons we can learn from their success.  

Utility forecasting falls into 2 categories – short term forecasting and long term forecasting.

Short Term Forecasting uses historical data correlation based on day of week, time of day, temperature and other factor to predict usage on an hourly, monthly basis.

Long Term Forecasting uses community development plans, road construction plan and city zoning data to predict capital expansion projects such as where to place power plants and distribution lines.

We can also identify Long Term Forecasting Predictors in crime based on factors available from various open government data sources. 

Interested? Please contact me.

Bernie  

What they know about you

What do they know about you - a lot.

It is difficult to understand how much digital signatures you leave on your computer even though you turn off cookies. I found this sction in Wall Street Journal that is dedicated to many ways that you can be tracked in cyberspace. http://online.wsj.com/public/page/what-they-know-digital-privacy.html

The section on digital fingerprinting is http://online.wsj.com/video/what-they-know-your-digital-fingerprint/49B4A220-88A5-4F53-BA89-20BBB0A83CB2.html  

Should we be worried? Just like in the real (non cyber) world, one has to be careful.

• You don't visit irreputable stores online or in real life.
• You don't talk to strangers online or in real life, unless they are introduced by a friend that you know. 
• You check out the person or the company before you interact with the person or company. There are many ways you can find out.

We are in the cyber world. There is no turning back. We just have to learn to live in it safely.

Are there other best pratices you can share?

Bike Theft - there is always a lesson that can be learned

Cable lock that's been cut.

Bike Theft - living in a city with the reputation of being bike friendly, it should be of no surprise that bike thieves love the city as well.

So what does a bike theft got to do with cyber security? Bear with me, and I hope to draw some parallels.

Yes, couple of years ago, I had my new bike stolen, on a Saturday afternoon, from a busy street that I thought no thief will be brave enough to take. I just thought I was unlucky. Not until a couple of weeks ago after I actually witnessed a bike theft first hand that I realized that it was my stupidity instead.

Then, yesterday, I was in some email exchanges that discussed whether an End of Life security device has any value. It dawn on me that bike theft and security theft have analogies.

Let me first relay to you my first hand experience of the bike theft. It was also on a Saturday afternoon but only 2 weeks ago, in front of a theatre, with packed crowd on the sidewalk. This guy walked up to the line of locked bikes. Most of the bikes used the U type lock but one used the cable lock. The thief took out the bolt cutter from his draw string backpack, clip the cable lock - all within half second and not more than 5 feet from me. I yield at him, challenging him. He replied with some stupid answer, got on the bike and took off.  This all happened within 5 seconds. I dialed 911 and reported it . The reporting took me 5 minutes.

These incidences taught me a few lessons.

1) Bike thieves have lots of practice. They think like thieves, not like good guys. Stealing a bike in a busy street is no worse than in a quiet street.

Analogy - Cyber thieves are the same. They think like bad people. They don't care if you use the internet a lot or just occasionally, you are the same victim.

2) After my personal bike was stolen, I've learned that cable locks are useless. This is a widely known fact and well published. So, why are bikers still using cable locks? The bike thief took the easiest prey.

Analogy - an End of Life security appliance means no more support, patches. This also is a widely known fact and well published. Bad guys know it too. So why are we using outdated security appliances? The bike thief can identify a security device and take his easiest prey.

3) Even though I reported the bike theft, do you think the thief will ever be caught? Even if caught, do you think he will go to court? Highly doubt it.

Analogy - cyber thieves stealing a couple of thousands dollars from our bank or credit card. You reported it, do you think he will be caught? Stealing smaller amounts from lots of people is much less noticeable than stealing a large amount from a big company.

The bike thief was clean cut and looked just like any other tourist. Lessons learned, you don't know what a bad guy looks like.

Any other lessons learned? Please share with me.
 

The lazy days of Summer

Summer are lazy days. Kids are on break. Families are thinking about vacation. Office is quiet and spam traffic is down. So life is good!

I only wish hackers look at summer the same way we do. Seeing the activities behind the scene, hackers are not taking a break. CRN released this report .

Just because you don't see it, doesn't mean it went away. The hidden ones are worse than the ones you know.

So make sure you delegate the vigilance of data security to someone before you take off on your vacation.