Michael Walfish, Mythili Vutukuru, Hari Balakrishanan, David Karger, Scott Shankar DDos Defense by Offense.

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Presentation transcript:

Michael Walfish, Mythili Vutukuru, Hari Balakrishanan, David Karger, Scott Shankar DDos Defense by Offense

Introduction A distributed denial-of-service (DDoS) attack is one in which a multitude of compromised systems attack a single target, thereby causing denial of service for users of the targeted system. Goal is to defend servers against application level DDos, a noxious attack in which criminals mimic legitimate client behavior by sending proper looking requests via compromised and commandeered hosts. The attacker forces to spend much of its resources on spurious requests. Examples of such attacks include using bots to attack website by : requesting large files,making queries of search engines and issuing computationally expensive requests.

Taxonomy of defenses Over-provision massively Detect and block Charge all clients in currency Speak up is a currency approach with bandwidth as the currency

Applicability of speak up How much aggregate bandwidth does the legitimate clientele need for speak up to be effective? How much aggregate bandwidth does the legitimate clientele need for speak up to leave them unharmed by an attack? Small websites, if defended by speak up, still be harmed? Because bandwidth is in part a communal resource,doesn’t the encouragement to send more traffic damage the network?

Applicability of speak up For the speak up to defend against the threat model, the following two conditions must hold: Adequate link bandwidth Adequate client bandwidth

Design of speak up Motivated by simple observation about bad clients : they send requests to victimized servers at much higher rates than legitimate clients do.

Illustration Imagine a request response server,where each request is cheap for clients to issue, is expensive to serve, and consumes same quantity of server resources. Suppose that every server has the capacity to handle c requests per second and that the aggregate demand from good clients is g requests per second, g<c If the attackers consume all of their aggregate upload band width B and if B + g > c, then the good clients will receive only a fraction g/( g + B) of the server’s resources. Assuming B>>g,the bulk of the server goes to attacking clients.

Illustration

Design goal and required mechanism Design goal : with our view of bandwidth as currency, our principle goal is to allocate resources to competing clients in proportion to their bandwidths. If the good clients make g requests per second in aggregate and have an aggregate band width of G requests per second to the server, and if the bad clients have a bandwidth of B requests per second, then the server should process good requests at a rate of min(g,G/(G+B)c)

Required mechanisms Practical realization of speak up needs three mechanisms. 1. Limit requests to the server c per second. 2. Speak up must perform encouragement. 3. Given the incoming bandwidths, speak up needs a proportional allocation mechanism to admit clients at rates proportional to their delivered band width

Required Mechanisms Encouragement can take several forms 1) Random drops and Aggressive retries 2) Explicit payment channel

Robustness to cheating Theorem : In a system with regular service intervals, any client that continuously transmits an ε fraction of the average band width received by the thinner gets at least an ε /2 fraction of the service,regard less of how the bad clients time or divide up their band width. This claim remains true regard less of the service rate c, which need not be known to carry out the auction.

Revisiting assumptions Speak up’s effect on network : Speak up would not much increase total traffic. 1) Inflating upload traffic to the level of download traffic would cause an inflation factor of at most two. 2) Only a small fraction of Internet servers is attacked at any one time.

Revisiting assumptions Shared links Provisioning the thinner Attacker’s constraint

Heterogeneous requests Generalize the design to handle the more realistic case when requests are unequal. If a client’s request is made of x chunks, the client must win x auctions for its request to be fully served.

Experimental Evaluation Validating the thinner’s allocation:

Experimental Evaluation

Latency and Byte cost

Experimental Evaluation

Heterogeneous network conditions

Experimental Evaluation

Good and bad clients sharing a bottleneck

Impact of speak up on other traffic

Conclusion This study has sought an answer to two high level questions : 1. Which conditions call for speak up’s peculiar brand of protection ? 2. Does speak up admit a practical design ?

Questions