2012年3月26日 星期一

Online Social Network Security


When it comes to security about computers and Internet, we often worried about the hackers stealing information and take advantages of the bugs and careless of people. But it is really different between this two points. 


I  read the information that from the website that professor recommended  and found that the  conventional security objectives is the service combined of different characteristics of Authentication ,Access control ,Data confidentiality, Data integrity,Non-repudiation .


What are the social network security objectives? This is quite a different view about the security and  we should view that from different points. As mentioned in the lecture, we can see that privacy,integrity and availability are very important for social network security.

By comparing two different security service we find data integrity or integrity is the only wanted in both services and other are not very match to each other. Why would security service have such a difference in the two area? We first have more detail of them.

We now to see the 5 aspects of the conventioanl security. The first is authentication, we have two small parts about that peer entity and data original authentication. Which means that we should know the peer and data are both correct. The second is accsee control, which means that not all the people are allowed to access the souce. The third one is data confidentiality, which is used to describe protection of data from unauthorized disclosure. The forth one is data integrity, as see in the face, we should not allow others to change the data under any circumstances. The last one is non-repudiation, that says we cannot deny what we do in the past.

Then we moved to the social network security, we first see the privacy, this point is needed because in the social network, we have information in the network and do not want any one can see that, I think this point is similar to the point access control but not the same for accsee control is more concerned for damage from the outside. The second is integrity which also mentiond in the conventional security objective, this can also refer to that we should keep our data as a whole and not be changed by others. The last is availability, that is important for we should allow others to see what we want to show, if we cannot guarantee this one, the social network is meaningless. And for other characteres not mentioned, I think due to social network, they are not need for the not-repudiation is useless in the environment of social network security.

Here to give the case about the difference of why there is no authentication in social network security. I think we have the following reasones. Just first imaging a case: we want to accsee others blog and need a password! Does that a useful way? Absolute not, we should allow anyone can  access our blog at any time.
So, we should not need the authentication in social network security. 

2012年3月13日 星期二

A brief introduction about SNA

     In my viewpoint, what called social network analysis can have two ways to describe: one of them is relationships and flows between different entities such as people, groups, organizations, computers, URLs.
     Another refers to methods used to analyze social networks, social structures made up of individuals , which are connected by one or more specific types.
     Social network analysis views social relationships in terms of network theory consisting of nodes and ties . Nodes are the individual actors within the networks, and ties are the relationships between the actors. In its simplest form, a social network is a map of specified ties, such as friendship, between the nodes being studied. The nodes to which an individual is thus connected are the social contacts of that individual.

     Social network analysis provides both a visual and a mathematical analysis of human relationships.In the example, we have the following picture:

     So, when it comes to the question in the example, we first briefly describe the simple social network in the following chart:



Alice
Bob
Carol
David
Eva
Alice
-
1
1
1
0
Bob
1
-
0
1
0
Carol
1
0
-
1
0
David
1
1
1
-
1
Eva
0
0
0
1
-

    In the above charts, we have following assumptions:the links between two people means that they knew each other and they cannot knew the other guys if there is no direct link between two. In the chats that 1 means link and 0 is no link which means they do not know each other.
    Within the question about who is the most influential point, we can easily see that from the picture and chart that David is, but what is the standard to do the determine?
    We have several methods to measure a social network, different methods give us different point of view about that special social network. We learned from the lecture that we have degree, density, geodesic distance and centrality to measure the social network.
     According to my opinion, to measure the most influential, the notion of influence range first comes to my mind, to find out whether it is suitable for the question, we have the following about the notion:
     Define influence range of ni as the set of actors who are reachable from ni
     Define Ji as the number of actors in the influence range of actor i (excluding i itself)
     An “improved” actor-level centrality closeness index considers how proximate ni is to the actors in its influence range
     A refined closeness centrality (for both directional and nondirectional) is
     This index is a ratio of the fraction of the actors in the group who are reachable, to the average distance that these actors are from the actor ni
So, we can easily computing the results in the following chart:
Alice
0.75
Bob
0.5
Carol
0.5
David
1
Eva
0.25
     
    From the result, we take David as the most influence node in this social network.
    But we should also keep in mind is that: is it a good way to measure this example in that way? The answer is no!
    we have one reason that in this example, we have no distance meaning, so the computing result may have not show the result correctly.
    So we turn to other ways to do the research:  centrality.
    We have three centralities: Degree, Betweenness,Closeness. To define which to use, we first see the differences between them:
    Degree Centrality:It signifies activity or popularity
    Betweenness Centrality: It is a measure of the potential for control as an actor who is high in “betweenness” is able to act as a gatekeeper controlling the flow of resources (information, money, power, e.g.) between the alters that he or she connects.
    Closeness Centrality: Can be understood as how long does it take for a message to spread inside the network from a particular node
    Backing to our question, we found that the degree centrality is the best to fit the question, so using this to compute, we have the following results:
Alice
3
Bob
2
Carol
2
David
4
Eva
1
    What we get the answer is the same form the above but I think this is more reliable than the first one, and we can also use other methods to do the same question, due to the limited time, I think if you are interested, you can do it !
    According to the above resulted are obtained, I found the following findings:
    1. Different social networks may have different characteristics, if we want to know furture about it, the metheds we use to do the research should follow the special characteristics, though sometimes the results maybe the same.
    2.One same social network, using different methods may lead to different results, this is quiet normal.
    3.Due to the limition of one social network, some notion of the methods may have no meaning, such as the distance in the example.
    4. We can do one research in the social netork by using different assumptions, may have differnet results, this is the same as view one thing in differnet views.
    5. As we can easily see that the cutpoint is David and the bridge is the tie between David and Eva, so we can draw a conclusion: the most influence point maybe or near the cutpoint or the bridge.


Reference:
 http://www.orgnet.com/sna.html
 http://en.wikipedia.org/wiki/Social_network_analysis