Measuring the efficiency of SDN mitigations against cyber attacks
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1 Measuring the efficiency of SDN mitigations against cyber attacks Ralph Koning Ben de Graaff, Robert Meijer, Cees de Laat, Paola Grosso System and Network Engineering research group Universiteit van Amsterdam
2 Context
3 SARNET Control loop Detection phase: Detect, Classify, Analyze Decision phase: Risk, Decide Response phase: Respond, Adjust, Measure Learn phase: Learn (with input from other phases)
4 Problem statement Detect Decide Respond There are multiple ways of responding to a single attack. To select the right countermeasure the response phase executes: Risk analysis (we will omit this since we cannot quantify risk) Response selection How does one pick the most effective countermeasure to defend against an attack?
5 Response selection We can rank responses based on past behaviour. Therefore, we need a measure of the effect of the response. Success rate; did we recover? Response time; how fast did we recover? Impact; How much was lost?
6 Detection points and thresholds Transactions Threshold Amount Time
7 Impact Transactions Threshold Amount Time
8 Efficiency Impact Timeout Threshold (Baseline) Importance Not recovered boundary Cost integral Cost under normal circumstances Because we have no cost measurements we will ignore cost for now. = 0, = 1 We are only interested in the Recovered situation
9 Efficiency Impact Timeout Threshold (baseline) Success rate Weight (Importance of metric) Efficiency single metric: Efficiency defence: Efficiency countermeasure:
10 Environment
11 Scenario Screenshot here
12 Scenario Screenshot here
13 Scenario Screenshot here
14 Scenario Screenshot here
15 Observables Metrics Sales: the combined amount of transactions to web services CPU: combined CPU load on the web services logfail: The amount of failed logins Attack classifications DDoS_Attack pwd_bf_attack CPU_Attack UDP based DDoS attack causes link congestion Password brute force attack causes abnormal login failures DoS attack focused on consuming CPU resources. if not Sales > 210 if not logfail< 20 if not CPU < 85 and not Sales < 210
16 Experiments Each measurement is repeated 50 times. We vary the following parameters: Response timeout: s Attack size: Light, Medium, Heavy The recorded values are averaged over a moving window of 10 samples. For impact we use a ceiling of 2 * threshold to prevent the impact of unbounded metrics from growing out of scale towards infinity.
17 Example: DDos attack Threshold
18 Example: DDos attack Attack start Threshold
19 Example: DDos attack Detect + Implement Recover Threshold
20 Example: DDos attack Detect Recover Threshold Impact
21 Example: DDos attack (Bonus) CPU drops too
22 Success rate Defence success rate in % (50 attempts) Attack Defence Size Light Medium Heavy CPU_attack captcha honeypot udp-filter udp-rateup pwd_bf_attack captcha honeypot udp-filter udp-rateup DDoS_attack captcha honeypot udp-filter udp-rateup
23 Success rate Defence success rate in % (50 attempts) Attack Defence Size Light Medium Heavy CPU_attack captcha honeypot udp-filter udp-rateup pwd_bf_attack captcha honeypot udp-filter udp-rateup DDoS_attack captcha honeypot udp-filter udp-rateup
24 Success rate Defence success rate in % (50 attempts) Attack Defence Size Light Medium Heavy CPU_attack captcha honeypot udp-filter udp-rateup pwd_bf_attack captcha honeypot udp-filter udp-rateup DDoS_attack captcha honeypot udp-filter udp-rateup
25 Success rate Defence success rate in % (50 attempts) Attack Defence Size Light Medium Heavy CPU_attack captcha honeypot udp-filter udp-rateup pwd_bf_attack captcha honeypot udp-filter udp-rateup DDoS_attack captcha honeypot udp-filter udp-rateup
26 Efficiency Efficiency of countermeasures (50 attempts) Attack Defence Size Light Medium Heavy CPU_attack captcha honeypot pwd_bf_attack captcha honeypot DDoS_attack udp-filter udp-rateup
27 Ranking defences Based on the defence efficiency a SARNET will make the following choices First choice Second choice CPU_attack captcha honeypot pwd_bf_attack honeypot/captcha - DDoS_attack udp-filter - DDoS_attack (light) udp-filter udp-rateup
28 Conclusions Determining efficiency is a first step towards ranking countermeasures and self learning. Efficiency is universal enough to apply and compare on new countermeasures.
29 Multi-Domain Demo at booth #1281 (Ciena)
30 Contact: Ralph Koning r.koning _at_ uva.nl booth booth # Research made possible by:
31 Effectiveness and Impact (2) Transactions Threshold
32 CPU attack recovery time
33 DDOS recovery time
34 Weights The values we use for in the efficiency calculation. Classification Sales Logfail CPU CPU_attack DDoS_attack pwd_bf_attack 0 0 1
Measuring the Efficiency of SDN Mitigations Against Cyber Attacks
Measuring the Efficiency of SDN Mitigations Against Cyber Attacks Ralph Koning a,, Ben de Graaff a, Robert Meijer a, Cees de Laat a, Paola Grosso a a System and Network Engineering Group (SNE), Universiteit
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