Academia.eduAcademia.edu

Figure 24 – uploaded by Riccardo Bettati

See full PDFdownloadDownload figure
Thus, we can use the lower bound of (4.38) as the estimation of detection rate by Theorem 4.3: Using sample variance as the classification feature gives rise to an

Figure 24 Thus, we can use the lower bound of (4.38) as the estimation of detection rate by Theorem 4.3: Using sample variance as the classification feature gives rise to an

Related Figures (39)

4. ACTIVE LINK-LOAD ANALYSIS ATTACKS AND COUNTERMEASURES ...61
4. ACTIVE LINK-LOAD ANALYSIS ATTACKS AND COUNTERMEASURES ...61
between the protected subnets A and B.
between the protected subnets A and B.
Figure 2. Flow Marking Attack Framework these below.
Figure 2. Flow Marking Attack Framework these below.
Figure 3. Bayes Decision Making for the Case of Two Payload Traffic Rates
Figure 3. Bayes Decision Making for the Case of Two Payload Traffic Rates
Figure 4. Experiment Setup in Laboratory for Passive Attacks
Figure 4. Experiment Setup in Laboratory for Passive Attacks
Figure 5. CIT Padding with Zero Cross Traffic
Figure 5. CIT Padding with Zero Cross Traffic
Figure 6. VIT Padding - Detection Rate vs. Sample Size
Figure 6. VIT Padding - Detection Rate vs. Sample Size
Figure 7. Empirical Detection Rate with Cross Traffic in Laboratory feature statistics. Thus, the bigger ner , the smaller the detection rate.
Figure 7. Empirical Detection Rate with Cross Traffic in Laboratory feature statistics. Thus, the bigger ner , the smaller the detection rate.
Differentiating the two sides of (3.50), we have the density function To get sample variance’s PDF at sample size n, we first compute its distribution function We denote Y;as the random variable of sample variance of padded traffic’s PIAT at the low rate payload traffic. Substituting (3.44) into (3.51), we then derive Y;’s density
Differentiating the two sides of (3.50), we have the density function To get sample variance’s PDF at sample size n, we first compute its distribution function We denote Y;as the random variable of sample variance of padded traffic’s PIAT at the low rate payload traffic. Substituting (3.44) into (3.51), we then derive Y;’s density
Thus, we use the lower bound of vy as the estimation of the detection rate. Since that vy must be greater than 50%, we can get (3.19). The theorem is proved. In the following, we prove that vy is an increasing function of r. That is, we need to prove that Cy in (3.20) is a decreasing function of r. For terms in (3.20), we have the
Thus, we use the lower bound of vy as the estimation of the detection rate. Since that vy must be greater than 50%, we can get (3.19). The theorem is proved. In the following, we prove that vy is an increasing function of r. That is, we need to prove that Cy in (3.20) is a decreasing function of r. For terms in (3.20), we have the
Using Taylor expansion over (3.86) and by appropriate approximation, we get mean of H to the cross point h, is denoted as D; Now we use Chebynov inequality for the error rate estimation. The distance from the
Using Taylor expansion over (3.86) and by appropriate approximation, we get mean of H to the cross point h, is denoted as D; Now we use Chebynov inequality for the error rate estimation. The distance from the
the ratio of D, to the standard deviation of h,, we have
the ratio of D, to the standard deviation of h,, we have
by sample entropy. Consider that detection rate must be greater than 50% and we can get In the following we prove that v. is an increasing function in terms of r. That is, we need to prove that C,, is a decreasing function of r. Denote
by sample entropy. Consider that detection rate must be greater than 50% and we can get In the following we prove that v. is an increasing function in terms of r. That is, we need to prove that C,, is a decreasing function of r. Denote
Figure 10. Experiment Setup in Laboratory for Active Attacks adversary pings the sender gateway behind the Marconi router.
Figure 10. Experiment Setup in Laboratory for Active Attacks adversary pings the sender gateway behind the Marconi router.
Figure 14. Detection Rate by RTT of Delayed Ping Packets with Zero Cross Traffic
Figure 14. Detection Rate by RTT of Delayed Ping Packets with Zero Cross Traffic
Differentiating the two sides of (4.47), we have the density function To get sample variance’s PDF at sample size n, we first compute its distribution function We denote Y;as the random variable of sample variance of padded traffic’s PIAT at the low rate payload traffic. Substituting (4.41) into (4.48), we then derive Y;’s density
Differentiating the two sides of (4.47), we have the density function To get sample variance’s PDF at sample size n, we first compute its distribution function We denote Y;as the random variable of sample variance of padded traffic’s PIAT at the low rate payload traffic. Substituting (4.41) into (4.48), we then derive Y;’s density
Thus, we use the lower bound of vy as the estimation of the detection rate. Since that vy must be greater than 50%, we can get (4.39). The theorem is proved. In the following, we prove that vy is an increasing function of r. That is, we need to prove that Cy in (4.63) is a decreasing function of r. For terms in (4.63), we have the
Thus, we use the lower bound of vy as the estimation of the detection rate. Since that vy must be greater than 50%, we can get (4.39). The theorem is proved. In the following, we prove that vy is an increasing function of r. That is, we need to prove that Cy in (4.63) is a decreasing function of r. For terms in (4.63), we have the
mean of H to the cross point h, is denoted as D; Now we use Chebynov inequality for the error rate estimation. The distance from the
mean of H to the cross point h, is denoted as D; Now we use Chebynov inequality for the error rate estimation. The distance from the
the ratio of D, to the standard deviation of h;, we have
the ratio of D, to the standard deviation of h;, we have
where by sample entropy. Consider that detection rate must be greater than 50% and we can get In the following we prove that v. is an increasing function in terms of r. That is, we need to prove that C,, is a decreasing function of r. Denote
where by sample entropy. Consider that detection rate must be greater than 50% and we can get In the following we prove that v. is an increasing function in terms of r. That is, we need to prove that C,, is a decreasing function of r. Denote
Figure 18. Flow Marking Attack Scenario
Figure 18. Flow Marking Attack Scenario
Figure 21. Power Spectrum of 802.11 DSSS Traffic for Stop-and-go Mix
Figure 21. Power Spectrum of 802.11 DSSS Traffic for Stop-and-go Mix
Figure 25. Detection Rate vs. Noise Traffic
Figure 25. Detection Rate vs. Noise Traffic
Related topics:
EngineeringComputer ScienceComputer SecurityTraffic analysis
580 California St., Suite 400
San Francisco, CA, 94104
© 2025 Academia. All rights reserved