Many news outlets are often focused on reporting about the same subject at the same time.  At the moment swine flu has taken the spotlight.  The more time spent on one topic, the less time there is to devote to an examination of other subjects.  Though this convergence of focus may to some extent be the result of an efficient allocation of resources to topics the public finds interesting, there are likely other effects at work.  The relationship between news providers should be approached as a network, and the influence of these providers on each other should be considered.

In a March, 2009 New York Times article (http://www.nytimes.com/2009/04/01/business/media/01cable.html?partner=rss&emc=rss) the changing terrain of cable news is discussed.  According to the article, Fox News, a conservative-minded news network, maintains the highest prime time ratings for cable news.  Recently, left-leaning MSNBC has for the first time overtaken CNN for the second highest.  The rise of ratings-dependent politicized news may serve as one factor leading to the seemingly synchronized focus on news stories.

Consider a payoff matrix of the game played between MSNBC and Fox News in regards to a decision to cover a particular story.  If both networks cover a story, then they are able to do so from their political stance, and both receive a positive payoff in ratings from their like-minded viewers.  If neither network covers a story, then the payoff is zero.  However, if one network addresses a topic and the other fails to, then they are able to set the tone for coverage of the issue.  If the subject is important, then the network that covers it will receive a positive payoff while the one that doesn’t receives a negative payoff.  If the story is not important, each network will receive a payoff of zero.

In this situation, the strategy that makes the most sense is to cover the same stories as the other news channel.  As there is a limited amount of time for news, clearly not all topics can be addressed.  However, there is a greater risk from not covering a story that the other channel is than from both ignoring the same stories.

http://www.cs.ucsb.edu/~seclab/projects/torpig/index.html

Botnets - legions of computers controlled by malware and coordinated by a malicious botmaster - are used for many purposes, including spamming, launching distributed denial-of-service attacks, and stealing personal information, but until recently they had never been used for academic research. In early 2009, researchers at the University of California, Santa Barbara, used a vulnerability in the infamous Torpig bot to “hijack” the botnet for a period of ten days and analyze the data it harvested. The full paper offers an interesting look at the methods Torpig uses and how they can be subverted or guarded against and is recommended reading for anyone interested in botnets, but relevant to this course is the Torpig code which simultaneously makes the botnet more robust and offers an intelligent intruder the opportunity to hijack it.

All bots (malware controlling an infected computer) on a given botnet need to communicate with one or more “command and control” servers - to upload stolen credit card numbers, download today’s spam messages and recipient lists, or otherwise carry out the botnet’s purposes. The mechanics of this communication are of interest, since sticking the C&C server’s IP address in the bot’s configuration file is just begging some dark-suited men to show up at your door, and any proxies you route the communication through probably won’t be very happy about it. Most modern botnets register domains for their C&C servers, which are then stored by individual bots, but this still allows major points of vulnerabilities in the network - if law enforcement or abuse complaints get these domains pulled, the botnet will fall apart. A technique known as “domain flux,” used by Torpig and other sophisticated malware such as Conficker, makes the network much more robust by dynamically generating domain names to check for a valid C&C server, but also allows an attacker with knowledge of the domain-generation code to hijack the botnet by registering one such domain and setting up a valid C&C server of their own (a process known as “sinkholing”).

Torpig uses the following procedure to generate domains: first, it takes a short list of three-character strings, uses the year and week to select two, and concatenates them. It then sends requests to this string plus .com, .net, or .biz; the first DNS to identify itself as a valid C&C server terminates the search process, and all further communication is carried out with that server. If none is found, Torpig then generates a domain based on the day and repeats the process. If that fails, it moves on to hardcoded domains. Obviously, with even a small number of building blocks, there would be enough domains generated in this manner to allow the criminals behind the botnet to keep their C&C servers alive even if dozens or hundreds of specific domains were shut down; however, this flexibility is a double-edged sword, as if (for instance) all the domain names for a particular week remain unregistered while the criminals have only registered the daily domains, a clever attacker can hijack the botnet for that week if he knows the algorithm Torpig uses to generate domains and the communications which identify a server as a valid C&C by setting up such a server and registering one of the weekly domains. Torpig will look for the weekly domain first, find a valid server, and communicate with the hijacker rather than its original botmasters. In fact, this is exactly what the researchers did, accumulating over 70 gigabytes of stolen data from over 180,000 infected computers.

Though a simple blog post can’t do the paper justice (read it, it’s very interesting), the implications of this kind of hijacking for the study of networks are pretty clear.  Creating a system which can link to a vast number of potential “targets” - far too many for either you or your opponents to handle - can make a system incredibly robust while at the same time creating massive security holes (security sinkholes?).  The odds that Torpig - or Conficker, whose daily generation can produce 50,000 domains! - cannot contact any of its C&C servers for an extended period of time will be minimal if the criminals are smart about registering their domains, since only one connection needs to work, but at the same time, any attacker who knows the workings of this system can play the game just as well as the criminals who set up the system. Both will try to register the “domain of the week,” which the bots will communicate with in preference to the daily domains, and it’s entirely possible that this could create a botnet oscillating between various controllers, especially as authorities shut down such domains. In fact, depending on the bot itself and how much control the C&C’s have over it, such an attacker could permanently alter the botnet in a way that prevented the original owner from regaining control, such as changing the building blocks it uses to generate domains to something unknown to the original botmasters! This is exactly what the criminals behind Torpig did after ten days of researcher control; a new Torpig binary with a different DNS generation algorithm was distributed to infected computers, ending the hijacking. Presumably, if one were to figure out the new algorithm, the same sort of hijacking could be attempted again. This sort of botnet, then, requires information asymmetry between its botmasters and would-be attackers, since its very robustness also allows an intelligent attacker to subvert its control.

The practical applicability of solving the problem of finding the shortest path between two nodes in a network can be motivated by considering the problem of a transportation network. Consider a network in which each node represents an airport and each edge between nodes n₁ and n₂ is weighted proportionally to the cost of flying one airplane from n ₁ to n₂. Constructing the cost of the edges is a problem in itself, so this model will assume that each cost is well known.

For concreteness, consider the simple four node network in Figure 1. Suppose an airplane at airport D must get to airport B with the minimum cost, what path should that plane take. The answer, upon inspection, is clearly the path D-C-B. However, such inspection of a massive network of airports would be nearly impossible (in 1996 there were over 13,000 airports in the United States (http://www.bts.gov/publications/north_american_transportation_in_figures/html/table_11_2.html). So, an algorithm that, in general, can derive the shortest path between two nodes would be useful. Such an algorithm exists and is called Dijkstra’s algorithm developed by Edsger Dijkstra in 1959. In fact, Dijkstra’s algorithm finds the shortest path from a given source node to all the nodes in the graph.

Dijkstra’s algorithm works as follows. First, assign a cost value to every node in the network, initializing it to zero for the source node and infinity for all other nodes. Also, mark each node as unvisited, and set the source node as the current node. For the current node, consider each node that it links to, and calculate these adjacent nodes’ cost of traveling from the source node. If this calculated cost is less than the current cost for that node, overwrite the cost. When all nodes adjacent to the current node have been considered, mark the current node as visited. Then, find the node in the network with the smallest cost that has not been marked as visited as the current node and repeat the process. When all nodes have been marked as visited, the algorithm is done.

Considering the algorithm acting on Figure 1 can be instructional. Since our problem was to find the shortest path from D to B, make D the source node and the first current node. Set the cost of A to 3 and the cost of C to 5. Since all D’s adjacent nodes have been considered, mark it as visited. A is not the node with the smallest cost. It’s only unvisited neighbor is B, who’s cost is set to 10+3=13. A is marked as visited. The minimum cost is now node C. It’s only unvisited neighbor is B. Using this path, B’s cost is 7+5=12 < 13, so B’s cost is set to 12. The algorithm has show that the shortest path from D to B is through C.

From this simple example, the utility of using computerized algorithms to calculate the shortest paths is seen, as well as a possible practical application of the Dijkstra method. (Numerische Mathematik, 1 (1959), S. 269–271. http://www-m3.ma.tum.de/twiki/pub/MN0506/WebHome/dijkstra.pdf )

http://www.chicagomaroon.com/2004/3/12/a-treatise-on-dating-the-prisoners-dilemma

The above article explains an interesting comparison between the prisoner’s dilemma which we discussed in class and dating using game theory. Like the prisoner’s dilemma game, this explanation shows why deception is a dominant strategy.

In class we learned about the prisoner’s dilemma which is a situation where two prisoners are caught by the police, put in separate rooms, and asked to confess to their crime. There is not enough evidence to convict them of the robbery they are suspected for, so the police need them to confess. It is a game theory situation because the best strategy for one prisoner depends on which strategy the other prisoner chooses. There are two options: either confess or don’t confess. If one prisoner confesses, but the other doesn’t confess, the one who confessed will get off and the one who didn’t will go to jail. If both prisoners confess, then they both go to jail. If neither confesses then they get a lesser charge of resisting arrest. The game can be viewed with the following payoff matrix:

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Based on this matrix, the most socially beneficial thing to do is for both prisoners not to confess. However, confessing actually turns out to be the dominant strategy. That is because no matter what the prisoner 2 does (confess or not confess) the best choice for prisoner 1 is to confess. So because confessing is a dominant strategy they both end up choosing that, turn each other in, and both end up going to jail (-4) when if they had just held out they would only get a small charge each (-1).

In the article this dilemma is compared to the interaction between guys and girls who are interested in each other. According to the author there is an “incentive for all individuals involved to show disinterest toward each other, regardless of the reality”. The reason for this is that each person, while they might be interested, also desires to increase their perception of “exclusivity” by rejecting others. In this game “exclusivity works as a reward system because girls brag to each other about how many guys hit on them, and guys brag about how many girls they turned down. Similarly, girls communicate when they fail in attracting a guy, and guys do the same. In each situation, the players use communication to establish exclusivity, thus increasing their own desirability or communicating failure.” So in a social situation where a guy and girl are interacting, assuming both are actually interested, if both express this interest both get a relative gain because they will both have been successful in attracting the other sex. If both show disinterest then no one gains or loses, because no one was successful and no one was rejected. But if one person gets rejected by the other then the one who got rejected experiences a loss, while the one who rejected them will experience a gain in exclusivity. So even if both are interested there are positives of deception (rejecting the other person even though you are interested). The game can be viewed in the following payoff matrix:

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Here it can be seen in the payoff matrix how no matter what choice the other person makes [lie (reject) or truth (don’t reject)] the dominant strategy for the other person is to lie and reject. That is because in this situation, like the prisoner’s dilemma you don’t know what the other person is going to do. It is socially optimal for both people to tell the truth, but because it is a dominant strategy to reject usually someone does. This is because “there are risks only when either player makes the decision to interact truthfully”. If a player chooses deception then there is no possible negative outcome, just a positive or a neutral.

So what is the author’s solution to this “dating dilemma”? He claims: “The answer is simple: do nothing! I call this tactic “pre-emptive protection of exclusivity.” Personally, I use my predictive abilities and realize that I’ll likely be shot down. And that she’ll probably brag to her friends about how “the columnist” tried to hit on her. So I do nothing. This is my way of really sticking it to girls whom I think aren’t interested in me.”

So there you have it, game theory explains why dating is so hard. When lying is a dominant strategy in male-female interactions it’s a surprise relationships ever work out.

In the current day and age, networking, both in the social and business atmosphere has become extremely important. Networking websites like Facebook and LinkedIn rank supreme, and the continued advancement of technology drives people to “stay connected.” It is a reasonably well known fact that any sort of “connections” when searching for jobs, can prove to be invaluable. Furthermore, as one of the cornerstones of social network theory, Mark Granovetter, proved, just because a tie is “weak” does not make it any less important or influential than a “strong” tie; in fact, many times weak ties prove to be much more valuable than strong ties. Especially in the current job-market climate, it has never been more important to have “connections,” regardless if these ties are weak or strong. While the job-seekers focus on building and using their business contacts for jobs, the managers in charge of building strong organizations in companies have some important decisions to make with regards to the amount and strength of ties in their organizations. If these managers have the opportunity to build the “perfect” organization from scratch, do they build an organization of strongly connected, qualified individuals, who have all successfully worked with each other before and have similar experiences, or do they choose qualified individuals who have no ties, or at the most, weak ties with each other, and are relatively new in working with each other, or some combination of the two. Obviously this decision should be based on the very specific needs of the organization; nevertheless, this situation brings up interesting questions that are important for any organization to consider. On the one hand, the close-knit group should need less time to adjust to each other and work as a team, but because they have such close ties to each other, their minds and opinions might be made up already. On the other hand, by bringing together a group of qualified, but less connected individuals, the time to bond as a team will take longer, but the potential for new ideas might be greater.

Over the past couple of years, one major problem in corporations has been executive greed and corruption, specifically with regards to the hiring of friends over other qualified business professionals. These are “strong” ties, but are they good for business? Perhaps, but most likely not. Therefore, it seems once again, even though counter-intuitive, weak ties may actually be stronger than strong ties. While Granovetter is the father of the theory of the strength of weak ties, many other individuals have come up with examples that further validate and prove Granvonetter’s theory. For example, in The Strength of Weak Ties: The Influence of Horizontal Research Ties on National Environmental Policies, Elizabeth Malone and Sylvia Edgerton, provide the belief that “if we want to address questions about how information and innovation spread, we must include—even focus on—weak ties, because information spreads poorly via paths that consist only of strong ties” (Malone 3). They even go on further to say that “if everyone who passed on a message did so only to close friends, transmission of the message would be slow at best and, very possibly, short-lived” (Malone 3). Therefore, as Malone and Edgerton conclude, weak ties are the starting point for innovation and influence because of their ability to access large portions of the population, with less barriers than with strong ties. As can be seen, if the main goal for a new organization is innovation, a collection of individuals with weak ties is not a bad organizational model.

http://www.globalchange.umd.edu/data/publications/1_
The_Strength_of_Weak_Ties.revised.pdf

http://www.wilsonweb.com/wmt5/viral-principles.htm

             The internet has changed the method in which businesses can connect with people and distribute their message.  For example, in the modern electronic age, the spending on internet advertising has exploded as companies take advantage of the cheapness and efficient nature of online advertisements that target users more precisely.   As a result, the rate of spread of information has  increased exponentially.  As companies adapt new strategies to connect with people online, the phenomenon known as viral marketing has proven to be an effective method of reaching large numbers of individuals and quickly creating a customer base.   The goal of a viral marketer is to create buzz or a popularity wave about a product or idea, so that the idea spreads widely.Viral marketing is an strategy in which companies create an type of ad or media that connects with views and by its unique nature encourages viewers to spread it to their acquaintances.  This tactic relies on exploiting the digital version of the old-fashioned word of mouth phenomenon and can result in the marketer’s ad being rapidly spread throughout a network, like a virus, at little to no cost to the business.  Although it is cheap, one of the drawbacks is that the company does not have direct control of the message as it is being passed along, so it is possible for it to be

        Initially, viral marketing was grounded in chain emails that promised the receiver some sort of compensation such as free services, gifts, or promotions.  A famous example of this is Hotmail’s huge growth of 12 million users using chain emails by encouraging people to forward the email to their friends with the promise of free and fast email account.  With the introduction of YouTube and Facebook, viral marketing moved into videos and applications.  It is interesting to note that the success of a viral campaign is dependent on how well it is able to reach the viewers on a personal level.  If more people are able to identify with the campaign culturally, morally, or ideologically, the rate of spread increases.  It is also interesting to observe the evolution of viral marketing in correlation with the technology available.  As technology increases, the viral campaign available to the viewer is able to reach them on a more individual level. 

http://vids.myspace.com/index.cfm?fuseaction=vids.individual&videoid=8133592#

In this scene from The Princess Bride, my favorite movie ever,Westley(The Dread Pirate Roberts) challenges Vizzini to a duel of wits.  In this duel Westley will poison one of without Vizzini knowing which of the cups is poisoned. Vizzini will then choose which cup each of them will drink.  As we see Vizzini spouts many arguments as to why Westley would or would not choose to poison one cup or the other. Finally, he believes he knows which cup is safe and drinks from it. Westley drinks form the other. Just as Vizzini is laughing and advising Westley to “never go against a Sicilian when death is on the line,” Vizzini drops dead. We can see though that each of Vizzini’s arguements are self-contradictatory as if Westley comes to the same conclusion, he would instead put the poison in the other cup. Systematic Actions can be thought through and defeated by the other player, therefore one must be unsystematic or random in order to win.

However the game being played is one of asymmetric information. Princess Buttercup was surprised to  find that Westley had put the poison in the cup he placed closer to himself. He replys with a tidbit of information that Vizzini would surely have liked to know, “They were both poisoned, I have been building up immunity to Iocaine for years.”  Vizzini didnot know that Westley’s payoffs differed from his and thus was not able to see him poisoning both cups.

In the world of digital music, movies, and books, the intellectual property rights of these formats have started to be questioned by many individuals. In a generation of Bit Torrents and Peer-to-Peer file sharing, the many people of the world disregard these rights in order to illegally copy formats of music, movies, and books in order to share them a dollar or two. But who owns the rights to these formats? This question of intellectual property rights is a great question that has found parents of high school age student paying thousands of dollars to record companies for the illegal downloading of music.

In this article, the question of intellectual property rights is brought up and defined. Since the social optimum scenario for the marketing of these digital formats is to charge nothing for them. Giving them away to the public is socially optimum, but charging from them decreases the amount of people using the format and decreases the social outcome of all users. In this article, the question of property rights is defined by an individual that plays a large role in the copyright movement, Mark Helprin. Mark Helprin sees that intellectual property is no different from “brick and mortar property” in which the individuals that created the media can pass it down through the generations. Even though the question of intellectual property rights is brought up, the answer to this question will eventually be answered when the generation of pirates learns to pay for the goods they use.

http://washingtontimes.com/news/2009/may/01/protecting-intellectual-property-digital-age/

When it comes to professional relationships, more information is going to be transmitted generally speaking to people with more edges that branch out into the network.The more edges a person has linking them to other people, the smaller the average length of pathways between them and any other random person in the group. Information travels not only between nodes that know each other, but also down paths between nodes that don’t know each other directly. An example of this in a work setting would be if one person asks another person to consult their resources in order to recommend a particular type of vendor. This is an example of information traveling down a path that is longer than one edge.

Part of the value of people using personal connections for referrals is that to help identify “known quantities” so to speak. People are hesitant to recommend someone they feel will reflect poorly on them.  The YouTube video “Professional Networking with LinkedIn” (http://www.youtube.com/watch?v=S_Hmgo90Bzg) describes a method and purpose for using online professional networking site LinkedIn to find job opportunities.

The idea of Six Degrees of Separation, published originally by Stanley Milgram, has recently received some support from a study conducted by Microsoft. Using data from their MSN Messenger, Microsoft determined the average distance between any two people to be about 6.6 degrees. In their study, they determined acquaintances as people who had sent at least one text message to each other. According to the study, about 78% of people were within 7 steps of one another, but the largest distances between people went up to 29 steps. Microsoft’s study is important because it fills in many of the gaps in Milgram’s original experiment. Milgram only conducted the study within the United States, and used a method of tracking that had a very low success rate. The Microsoft study, however, covered 180 million people and 30 billion messages. The study was far more comprehensive due to the fact that it covered people from around the world, and not just in one country. Also, with the data it was very easy to establish links between people. Finally, the fact that MSN messenger is responsible for roughly half the world’s instant-messaging traffic gives the study a much broader base of information, and makes its result far more credible than the original. The only disparity is that the Microsoft researchers found closer to 7 degrees of separation rather than 6.

http://www.washingtonpost.com/wp-dyn/content/article/2008/08/01/AR2008080103718.html