Paper

The paper can be downloaded here and the slides can be downloaded here. It’s also available at the ACM Digital Library.

Bibtex Entry

@inproceedings{kak-soups09,
	Title = {Balancing Usability and Security in a Video CAPTCHA},
	Author = {Kurt Alfred Kluever and Richard Zanibbi},
	Booktitle = {Proceedings of the 5th Symposium On Usable Privacy and Security 2009},
	Address = {Mountain View, CA, USA},
	Month = {July},
	Year = {2009}
}

Here’s some quick info about SOUPS:

The fifth Symposium on Usable Privacy and Security (SOUPS) will be held July 15-17, 2009 at Google in Mountain View, CA. This symposium will bring together an interdisciplinary group of researchers and practitioners in human computer interaction, security, and privacy. The program features technical papers, workshops and tutorials, a poster session, panels and invited talks, and discussion sessions. SOUPS 2009 will be held in cooperation with ACM SIGCHI.

1. Paul Erdős and Paul C. Kainen
2. Paul C. Kainen and Vladik Ya. Kreinovich
3. Vladik Ya. Kreinovich and Hung Trung Nguyen
4. Hung Trung Nguyen and Leonid K. Reznik
5. Leonid K. Reznik and Kurt Alfred Kluever (via IEEE Sensors 2007)
   

I also found a couple of length 6 paths with interesting researchers (bolded below) in them:

1. Paul Erdős and Dieter Kratsch
2. Dieter Kratsch and Jitender S. Deogun
3. Jitender S. Deogun and Shashank K. Mehta
4. Shashank K. Mehta and George Nagy
5. George Nagy and Richard Zanibbi
6. Richard Zanibbi and Kurt Alfred Kluever (via IEEE WNYIP 2008)
   

1. Paul Erdős and Andrew M. Odlyzko
2. Andrew M. Odlyzko and Colin L. Mallows
3. Colin L. Mallows and Henry S. Baird
4. Henry S. Baird and Dorothea Blostein
5. Dorothea Blostein and Richard Zanibbi
6. Richard Zanibbi and Kurt Alfred Kluever (via IEEE WNYIP 2008)

An interesting article here states that “the median Erdős number is 5; the mean is 4.65, and the standard deviation is 1.21.”

Here are some great links for more reading about this topic:

• http://web.aanet.com.au/image/erdos/
• http://www.oakland.edu/enp/index.html
• http://www.oakland.edu/enp/trivia.html
• http://en.wikipedia.org/wiki/Erd%C5%91s_number

• insert(element, weight)
• sample()

When you insert an element into the data structure, you specify a weight. This weight divided by the total of the other weights in the data structure, is the probability that the item is returned when sample() is invoked. You should design your data structure with both speed and space in mind.

Here is a good solution. The insert() operation requires O(1) constant amortized time and the sample() operation requires O(lg n) time due to binary search. The space requirements is O(n) as well.

public final class BinarySearchWeightedSampler<E> {
  private List<E> elements = new ArrayList<E>();
  private List<Double> weights = new ArrayList<Double>();

  public void insert(E element, double weight) {
      elements.add(element);
      if (weights.isEmpty()) weights.add(weight);
      else weights.add(weight + weights.get(weights.size() - 1));
  }

  public E sample() {
    return elements.get(
        binarySearch(weights, Math.random(), 0, weights.size() - 1,
                     weights.get(weights.size() - 1)));
  }

  public int binarySearch(List<Double> array, double val,
      int low, int high, double totalWeight) {
    if (high < low) return low;
    int mid = low + ((high - low) / 2);
    int midValue = array.get(mid) / totalWeight;
    if (midValue > val)
      return binarySearch(array, val, low, mid - 1, totalWeight);
    else if (midValue < val)
      return binarySearch(array, val, mid + 1, high, totalWeight);
    else
      return mid;
  }
}

If we ignore the space requirements and assume the weights have finite precision (I chose integers for clarity, but any finite precision number can be made to work), we can sample in O(1) constant time:

public final class DiscreteWeightedSampler<E> {
  private List<E> elements = new ArrayList<E>();

  public void insert(E element, int weight) {
    for (int i = 0; i < weight; ++i) {
      elements.add(element);
    }
  }

  public E sample() {
    return elements.get((int) (Math.random() * elements.size()));
  }
}

What is your favorite class and why?
Theory of Computer Algorithms. This course is the first formal, in-depth course on algorithms, complexity, and data structures. These three components are the foundations of Computer Science and I highly recommend that everyone take this course (although it is a very difficult course).

One piece of advice I have for 1^st year students is…
Establish a relationship with your professors by asking questions in class and utilizing office hours when you are confused.

If you could have dinner with a famous computer scientist, living or dead, who would you choose?
Luis von Ahn. His work on CAPTCHAs and human computation has inspired me to pursue it as my thesis topic.

What is the most interesting project you have worked on, either in a course or on the job?
The most interesting project I’ve worked on has been my thesis. Reading all of the existing research has helped me develop a brand new idea that nobody else in the world has worked on.

Where do you see yourself in ten years?
Hopefully back in school earning my PhD in Computer Science.

Original post: http://www.cs.rit.edu/about/profiles/Kurt_Kluever
PDF version: http://www.cs.rit.edu/five_minutes/pdf/Kurt_Kluever.pdf

Also check out 5 Minutes with Richard Zanibbi (my thesis advisor) and 5 Minutes with Brian Renzenbrink (a good friend).

On January 28th, 2009, my thesis advisor (Richard Zanibbi) presented a talk on Video CAPTCHAs at the RIT Center for Imaging Science. An abstract of the talk can be download here. A video of his talk (with slides) can be watched here using Adobe Acrobat Connect.

My Job (Google)

My job is going great. I really love the work environment and people at Google. Everyone is willing to take time out of their day to help you with whatever you need…which is good because the project I’m working on has a very high learning curve. It uses a ton of Google-centric infastructure pieces that all work together in a very specific way. Since I’ve had no exposure to these technologies before, work has been going a little slow (lots of reading of other’s code and documentation, not a lot of coding). It’s a bit frustrating because it’s hard to measure productivity when most of your time is spent inputting knowledge (into your own brain), not outputting knowledge (to others). However, this means I’m learning something new every day (which is exciting). I’ll also excited to report that I’ll be continuing my work on Video CAPTCHAs at Google :)

My City (Hoboken)

There are tons and tons of young professionals everywhere. According to Wikipedia, the median age here is only 30 (as a comparison, the median age in the US is 35.3). While that doesn’t seem like a big difference, you’ll quickly notice it walking around the streets. The city of Hoboken itself is actually a lot of fun. Since the young population drives the local businesses, there are tons of bars, restaurants, and coffee shops in downtown Hoboken. In fact, no matter what day it is, the streets and bars are always full of people.

My Commute (Walk, PATH Train, Walk)

Nearly everyone here takes the PATH train into NYC for work. The PATH train is a bargain: for $1.30 (if you buy in bulk), you can get to midtown Manhattan in under 15 minutes. My train (from Hoboken to 14th Street) makes 2 stops along the way (at Christopher St and 9th St) and still only takes 11 minutes. That’s a faster commute than it would be even if I lived in most places in Manhattan. The only bad part of my commute is getting to the PATH station in Hoboken. It’s a mile walk from my apartment which isn’t bad now, but once the bad weather hits it’s going to be brutal. I’m going to try to get my bike down here to speed up the commute though. Once I get to 14th St, I have another half a mile or so walk to Google. Others have recommended that I take the L subway, but I’d rather save the $2 each way and walk the two blocks. Overall, my commute into the city costs me $1.30, a few hundred calories, and about 40 minutes of my time.

My Car (A Sad S4)

One of the main reasons that I decided on the apartment that I’m in is that it came with a free garaged parking spot my for S4. However, I’ve quickly realized that having a car down here is rather pointless. I’ve only used it two times since moving down here: 1) buying furniture on move in day 2) returning an air mattress to BJs. Other than that, it sits in the garage and looks at me in anger: it wants to be driven. Next weekend I’ll be driving up to Rochester to present at the IEEE WNYIP 2008 workshop…that’ll cheer my car up :) Also, gas is really cheap (comparatively) down here: $3.30/gallon for regular.

My Eating (An Empty Fridge)

I do all my weekday eating at Google: breakfast (sometimes), lunch (always), and dinner (except on Fridays). Because of this, I have very little (read: no) food in my fridge. In fact, all I have at my apartment is 3 mini-bags of popcorn and some soda. On the weekends, I go out to eat. There’s no sense in going grocery shopping for the weekend only. I’m sure at some point I’ll stock my cabinets with non-perishables like soup, etc. Also I should note that I may end up dying of mercury poisoning due to the amount of fish I’m eating at Google every day.

Paper

The paper can be downloaded here or from the RIT Digital Media Library.

Bibtex Entry

@inproceedings{videoCAPTCHAsUsabilityVsSecurity,
	Title = {Video CAPTCHAs: Usability vs. Security},
	Author = {Kurt Alfred Kluever and Richard Zanibbi},
	Booktitle = {Proceedings of the IEEE Western New York Image Processing Workshop 2008},
	Address = {Rochester, NY, USA},
	Month = {September},
	Year = {2008}
}