Lecture 4. Does the Internet have an Achilles' heel?

Transcription

1 Lecture 4 Does the Internet have an Achilles' heel?

2

3 Outline Definition Arguments for that the Internet have an Achilles' heel. Arguments against that the Internet have an Achilles' heel. Network throughput and robustness simulation to support arguments. Conclusion.

4 Does the Internet have an Achilles' heel?: Question specification: Are there high degree routers in the middle of the Internet that can be easily detected and attacked, so to fragment the Internet into many smaller pieces? Node degree = number of physical connections for a node Middle = many network router shortest forwarding paths pass through routers here Attack: - Denial of service: many clients overload one entity with requests. - Bombs...

5 Important problem to worry about, e.g., 2007 cyber attacks on Estonia Series of denial of service attacks that began 27 April, 2007 and swamped websites of Estonian organizations, including Estonian parliament, banks, ministries, newspapers and broadcasters.

6 Long-tail distribution of node degrees Long-tail distribution of node degrees => inhomogeneous network See whiteboard on long-tail distributions!

7 Nature cover, 2000, top ranked scientific journal It was measured that Internet has a long-tailed router degree distribution =>

8 What worried people in 2000 was that: the higher degree nodes in the long-tailed distribution are assumed to sit in the middle of the network.these can be attacked, and fragment the Internet.

9 Trench digging: Traffic aggregation Highly connected routers (high node degree) are at the edge of the network to divide little throughput among many users. Towards the core, traffic accumulates rapidly to avoid trench digging, so the core routers must have less connections. AT&T topology 2003: maximum degree of core router 68, maximum degree of edge router 313.

10 But the Internet could still have an Achilles' heel? Attack high troughput routers in the core!

11 Hardware: Total router throughput is limited Total throughput (Mbps) Total throughput = throughput per connection * number of connections => Whatever the number of connections, the total throughput is limited => No dominating routers in the middle of the network. [Alderson:2005] Understanding Internet topology: principles, models, and validation, Alderson, D., Lun L., Willinger, W., Doyle, J.C., IEEE/ACM Transactions on Networking, Volume: 13, Issue 6, 2005

12 But the Internet could still have an Achilles' heel? A scoundrel can spend a lot of time to detect a lot of important nodes, and attack all of these? Yes, but as we will see..., the Internet is good at reorganizing itself in case of router failure. - New key routers emerge during the attack, which are difficult to predict. Has to be motivated - Denial of service attack: The attacker must also have enough distributed fire power to maintain the blocking of the routers that were first attacked, while attacking the replacements.

13 Internet simulation Throughput and robustness (to base conclusions on in the end)

14 Throughput

15 Example 1 Degree distribution: G1 G2

16 Connectivity measure S(G) close to 1 <=> clusters of high-degree nodes in the network

17 Example 1 Degree distribution: G1 G2 Maximizes S(G)

18 Example 1: Connectivity measure

19 Example 1: Connectivity measure

20 Throughput optimization Gbps Routing matrix Network fixed, routing done, demand fix Demand for this connection

21 Throughput optimization Linear optimization problem: simplex algorithm and Newton's method!

22 Example 1: Throughput optimization for G1

23 Example 1: Throughput optimization for G1

24 Example 1: Throughput optimization for G1

25 Example 1: Throughput optimization for G1

26 Example 1 results Gbps

27 Example 1 results Better performance! Experimental observation: a small S(G) is better for performance

28 Example 2: Same optimization as in Ex. 1 [Alderson:2005] Random (preferential attachment) Optimized Distribution of node degrees same for all networks!

29 Example 2 (d) (e) (c) (b) (e) S(G)

30 (d) corresponds to Internet (d) High router degree on network edge, low router degree in the middle (traffic aggregation slide) (d) is optimized for performance while (b) is random. Internet is not constructed randomly, but by skilled engineers who optimize for performance. More discussion in [Alderson:2005] and in [Doyle:2005] The robust yet fragile nature of the Internet, J. C. Doyle, D. L. Alderson, L. Li, S. Low, M. Roughan, S. Shalunov, R. Tanaka, and W. Willinger, Proceedings of the National Academy of Sciences of the United States of America, vol. 102, no. 41, 2005

31 Robustness optimization

32 Example 2: Remove the router that decreases capacity most. Let the network rerun the routing algorithms [Doyle:2005]: Experiments: Network is not much fragmented (d) nominal 20% of routers deconnected (b) nominal (b) attacked (d) attacked (d) less fragile, yet fragile, cf., [Doyle 2005] title

33 Summary A long-tailed distribution of node degrees does not imply an Achilles' heel (graph optimization and routing should be taken into account). Before drawing conclusions, careful modeling of phenomena is important! The book does not show any robustness simulation at all (lecture's second last slide).