1. Aleksandar Kuzmanovic & Edward W. Knightly A Performance vs. Trust Perspective in the Design of End-Point Congestion Control Protocols

2. Motivation l Sender-based TCP –Control functions given to the sender

3. Receiver-Based TCP l Receiver decides how much data can be sent, and which data should be sent by the sender l DATA – ACK communication becomes REQ - DATA l Example protocols –TFRC [RFC3448], WebTP, and RCP

4. Why Receiver-Based TCP? l Example: Busy web server –Receiver-based TCP distributes the state management across a large number of clients l Generally –Whenever a feedback is needed from the receiver, receiver-based TCP has advantage over sender-based schemes due to the locality of information l Benefits [RCP03] Performance Functionality - Loss recovery- Seamless handoffs - Congestion control- Server migration - Power management for - Bandwidth aggregation mobile devices - Web response times - Network-specific congestion control

5. Vulnerability l Receivers remotely control servers by deciding which packets and when to be sent l Receivers have both means and incentive to manipulate the congestion control algorithm –Means: open source OS –Incentive: faster web browsing & file download

6. An Example: Request-Flood Attack l Request flood attack –A misbehaving receiver floods the server with requests, which replies and congests the network l Resource stealing –A misbehaving receiver moderately re-tunes TCP parameters to gain performance, yet eludes detection

7. Remaining Outline l Modeling receiver misbehaviors l Evaluate network-based solutions l Present an end-point solution l Conclusion

8. Algorithmic Misbehavior Why parameter-based misbehaviors? –Easy to implement –Tells how much you can misbehave while eluding detection l Goal –Compute TCP throughput for arbitrary (misbehaving) parameters

9. Bandwidth Stealing

10. Network-Based Solutions l RED-PD [MFW01] designed to detect non- responsive flows –Monitors only a subset of flows at the router and compares their rates to the targeted bandwidth (TB)  TB is computed as a TCP-fair throughput for »Observed Ploss & RTT=40ms  If Ti > TB => flow i malicious l Pushback [RFC3168] –Once a misbehavior is detected, network nodes coordinate efforts to thwart a malicious (flooding) node

11. RED-PD l Fact –Network-based schemes lack the exact knowledge of end-point parameters l Example –RED-PD doesn’t know about RTT: TB=f(Ploss, RTT=40ms) l Implication –Clients with RTT > 40 ms can exploit this vulnerability l Algorithmic misbehavior –Our algorithm tells how to re-tune AIMD parameters to steal bandwidth, yet elude detection

12. Pushback l The request-flood attack and Pushback l But in the request flooding scenario, the flooding machine is not malicious –moreover, it is a victim…

13. An End-Point Solution l Sender-side verification: –Ping Agent:  Measures RTT by pinging the receiver –TFRC Agent:  Computes “TCP- fair” rate –Control Agent:  Enforces the sending rate

14. A Server-Side Only Solution l Secure RTT measurement –What if the receiver simulates a shorter RTT?  Use nonce [ESWSA01]  Randomize the time between pings l Secure Ploss measurement –What if the receiver floods the sender with requests?  Use nonce [ESWSA01]  The sender purposely drops a packet; if the receiver never re- request the packet – it is cheating! The solution is completely independent of a potentially misbehaving receiver

15. Evaluation l Scenarios: –with behaving receiver (to study false positives) –with misbehaving receivers (to study detection) End-point scheme is able to detect even very moderate misbehaviors Slight inaccuracy for higher packet loss ratios (due to TFRC conservatism)

16. Challenges l “Advanced” TCP stacks –From the sender’s perspective, advanced TCP stacks look like a receiver’s misbehavior l HTTP servers –A single malicious receiver can significantly degrade performance to others –Counter mechanisms discussed in the paper  Can protect against DoS, but at the same time can reduce the performance in absence of DoS attacks

17. Conclusions l Receiver-based TCP stacks are highly vulnerable to receiver misbehaviors –cannot be safely deployed in the Internet without some level of protection l Network-based schemes are fundamentally limited to thwart receiver misbehaviors l An end-point-based solution –accurate and independent of a potentially misbehaving receiver –system security and protocol performance  both cannot be maximized simultaneously