TY - GEN
T1 - Designing router scheduling policies
T2 - 17th ACM Conference on Computer and Communications Security, CCS'10
AU - Kadloor, Sachin
AU - Gong, Xun
AU - Kiyavash, Negar
AU - Venkitasubramaniam, Parv
PY - 2010
Y1 - 2010
N2 - We examine a queuing side channel which results from a shared resource between two users in the context of packet networks. We consider the scenario where one of them is a legitimate user and the other is an attacker who is trying to learn about the former's activities. We show that the waiting time of an adversary sending a small but frequent probe stream to the shared resource (e.g., a router) is highly correlated with traffic pattern of the user. Through precise modeling of the constituent flows and the scheduling policy of the shared resource, we describe a dynamic program to compute the optimal privacy preserving policy that minimizes the correlation between user's traffic and attacker's waiting times. While the explosion of state-space for the problem prohibits us from characterizing the optimal policy, we derive a sub-optimal policy using a myopic approximation to the problem. Through simulation results, we show that indeed the sub-optimal policy does very well in high traffic regime. Furthermore, we compare the privacy/delay trade-offs among various scheduling policies, some already widely deployed in scheduling and others suggested by us based on the intuition from the myopic approximation.
AB - We examine a queuing side channel which results from a shared resource between two users in the context of packet networks. We consider the scenario where one of them is a legitimate user and the other is an attacker who is trying to learn about the former's activities. We show that the waiting time of an adversary sending a small but frequent probe stream to the shared resource (e.g., a router) is highly correlated with traffic pattern of the user. Through precise modeling of the constituent flows and the scheduling policy of the shared resource, we describe a dynamic program to compute the optimal privacy preserving policy that minimizes the correlation between user's traffic and attacker's waiting times. While the explosion of state-space for the problem prohibits us from characterizing the optimal policy, we derive a sub-optimal policy using a myopic approximation to the problem. Through simulation results, we show that indeed the sub-optimal policy does very well in high traffic regime. Furthermore, we compare the privacy/delay trade-offs among various scheduling policies, some already widely deployed in scheduling and others suggested by us based on the intuition from the myopic approximation.
KW - Algorithms
KW - Security
KW - Theory
UR - http://www.scopus.com/inward/record.url?scp=78649984658&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=78649984658&partnerID=8YFLogxK
U2 - 10.1145/1866307.1866403
DO - 10.1145/1866307.1866403
M3 - Conference contribution
AN - SCOPUS:78649984658
SN - 9781450302449
T3 - Proceedings of the ACM Conference on Computer and Communications Security
SP - 702
EP - 704
BT - CCS'10 - Proceedings of the 17th ACM Conference on Computer and Communications Security
Y2 - 4 October 2010 through 8 October 2010
ER -