flash crowds and denial of service attacks:

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Flash Crowds And Denial of Service Attacks: Characterization and Implications for CDNs and Web Sites Aaron Beach Cs395 network security

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Flash Crowds And Denial of Service Attacks:. Characterization and Implications for CDNs and Web Sites Aaron Beach Cs395 network security. OVERVIEW. What is a “Flash Event?” (FE) What is a “Denial of Service Attack?” What is the difference? How can we distinguish between them? - PowerPoint PPT Presentation

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Page 1: Flash Crowds  And Denial of Service Attacks:

Flash Crowds And

Denial of Service Attacks:Characterization and Implications

for CDNs and Web Sites Aaron Beach

Cs395 network security

Page 2: Flash Crowds  And Denial of Service Attacks:

OVERVIEW• What is a “Flash Event?” (FE) • What is a “Denial of Service Attack?”• What is the difference?• How can we distinguish between them?• What is/are the solution(s)?

– Adaptive Content Distribution Networks?– Others?– Do you have any ideas??? Think about it

Page 3: Flash Crowds  And Denial of Service Attacks:

Flash Events• A flash event (FE) is a large surge in

traffic to a particular Web site causing a dramatic increase in server load and putting severe strain on the network links leading to the server, which results in considerable increase in packet loss and congestion

• “Flash crowds”

Page 4: Flash Crowds  And Denial of Service Attacks:

Denial of Service Attack (DoS)• An explicit attempt by attackers to prevent

legitimate users of a service from using that service

• Their definition: – any attempt to undermine a Web site

• What do you think?

Page 5: Flash Crowds  And Denial of Service Attacks:

The Major Differences• Flash Events represent legitimate

traffic to a website. This often means the website wants to service these requests as well as possible, while DoS attacks our unwanted and should not be serviced, but ignored or controlled.

Page 6: Flash Crowds  And Denial of Service Attacks:

Distinguishing Between Them

• 3 main characteristics– Traffic patterns– Client characteristics– File reference characteristics

Page 7: Flash Crowds  And Denial of Service Attacks:

Traffic Patterns• Overall traffic volume determines how

much a server should provision resources to keep the site operational

• Servers can shut down from over use• Studying these patterns allows us to

articulate the period when an unusually large number of clients can overwhelm a site

• We also can understand how and in what time pattern the server must defend against these rises in traffic

Page 8: Flash Crowds  And Denial of Service Attacks:

How substantial can an FE be?

88.2% of traffic in 11% of time71% of traffic in 7% of time

Page 9: Flash Crowds  And Denial of Service Attacks:

You can see the spikes in traffic

They look indistinguishable?

Page 10: Flash Crowds  And Denial of Service Attacks:

Now do they look the same?

Quite different… however

Page 11: Flash Crowds  And Denial of Service Attacks:

Behavior of traffic• First fifteen minutes• They both rise, one over a period of • One over 70 minutes• One over 40 seconds

Page 12: Flash Crowds  And Denial of Service Attacks:

Client Characteristics and clustering

• They use a network-aware clustering technique to determine the topological distribution of clients in FE and DoS.

• Client clustering allows one to aggregate individual clients into groups belonging to the same administrative domain.

• Clustering uses a large collection of unique network prefixes assembled from a wide set of BGP routing tables.

• The various client IP addresses are grouped into clusters based on longest prefix matching.

Page 13: Flash Crowds  And Denial of Service Attacks:

Clusters and Clients trends• Spikes in request volumes during an

FE correspond closely with the spikes in the number of clients accessing the site. Thus, the number of clients in a flash event follows the same increase patterns as the overall request rate.

Page 14: Flash Crowds  And Denial of Service Attacks:

No large change in averageper-client request rate

Page 15: Flash Crowds  And Denial of Service Attacks:

“Old” clusters during an FE• Clusters that have already visited the

site VS new clusters during an FE

• During the two FEs we are studying there was 42.7% in the Play-along trace and 82.9% in the Chile trace that were “old” clusters demonstrating that in these FEs a large percentage had made previous requests

Page 16: Flash Crowds  And Denial of Service Attacks:

File Reference Characteristics• Locality of reference enables a

reduction of server load through caching.

• They use these characteristics in designing an “adaptive CDN.”

• We consider:– aggregate file references – reference patterns of individual clients– reference patterns of client clusters.

Page 17: Flash Crowds  And Denial of Service Attacks:

What files are accessed in FE• 60% (61% and 82% for Play-along and

Chile, respectively) of documents are accessed only during flash events.

• So, CDN’s will not cache and not be prepared for the FE

• Indeed, most CDN caches will not have these documents at the beginning of the FE

• So there will be many misses at the beginning of an FE

Page 18: Flash Crowds  And Denial of Service Attacks:

Popularity of files

Page 19: Flash Crowds  And Denial of Service Attacks:

Also about clusters and file popularity

• Requests for documents come from many different Clusters…

• This means that current CDNs will result in many different serves getting requests for the same file… resulting in more misses for the files popular only during FEs

Page 20: Flash Crowds  And Denial of Service Attacks:

Password cracking• Much like DoS attacks• We must detect early and stop them

• Detect “401 unauthorized” messages

Page 21: Flash Crowds  And Denial of Service Attacks:

Trends during attacks• During attacks most clients making

requests were new… never had made requests before

• Only 0.6% of the clusters seen at one site during the attack had been seen before, and the percentage of these clusters drops to 0.1% for another site.

Page 22: Flash Crowds  And Denial of Service Attacks:

Trends in DoS requests (Code Red)

Page 23: Flash Crowds  And Denial of Service Attacks:

Rise in Clusters vs Clients

FE

DoS

Page 24: Flash Crowds  And Denial of Service Attacks:

Overlap of clusters during DoS• Calculated overlap for DoS was:• 0.6% in the creighton site• 0% in the fullnote site• 1.8% in the spccctxus site • 14.3% rellim site. • Compare this to:• 42.7% and 82.9% in the FEs studied

Page 25: Flash Crowds  And Denial of Service Attacks:

Comparing the two: DoS vs FE

Page 26: Flash Crowds  And Denial of Service Attacks:

SOLUTION TIME!!!• What should the server do when it is being

overwhelmed??– Discard “more malicious” requests

• How?– Monitor users and average request rate– Periodically “cluster” addresses– When overwhelmed… drop malicious

addresses (must belong to old clusters and continue “normal” request rates

- Solution not too taxing on processes and you can implement it in an filtering accept() function

Page 27: Flash Crowds  And Denial of Service Attacks:

Will this always work??• Sometimes DoS attacks are able to

flood links… and the server can do nothing…

• Since attacker does not know who is using site they cannot know which clusters to send with (the author thinks this is a way to avoid letting this information prepare attackers… what do you think??

Page 28: Flash Crowds  And Denial of Service Attacks:

What about FEs?• If we know how to deal with DoS

attacks… we still have the problem of what to do when flash events happen

• Solution : Adaptive CDN

Page 29: Flash Crowds  And Denial of Service Attacks:

Adaptive CDN• “Dynamic Delegation”• The more caches the more requests,

so make less caches with more space• Have primaries and delegates… • When a FE is detected the DNS

servers sends requests to delegates first and they go to primaries…

• Only primaries can make requests to origin server, clustering caches

Page 30: Flash Crowds  And Denial of Service Attacks:

Algorithm for Dynamic Delegation• When a node “P” is overloaded it

redirects packets to another node that has a low load, using it as a “delegate”

• When a node goes low it stops using delegates

• Tests show this lowered load on origin server by: a factor of 50 in one test and 30 in the other… without too high load distribution in the caches.

Page 31: Flash Crowds  And Denial of Service Attacks:

Review• Flash Event (Flash Crowd)• FE vs DoS• Difference and Detection• Detecting and stopping• Dealing with FE using adaptive CDN