Optimization of packet filter with maintenance of rule dependencies

Tanaka, Ken; Mikawa, Kenji; Takeyama, Kouhei

doi:10.1587/comex.2.80

Cited by 7 publications

(6 citation statements)

References 3 publications

(3 reference statements)

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“…As shown in Fig. 7, the proposed method decreases the latency by about 11% compared to Tanaka et al [13], SGM [10], and Hikage et al [12]. This 11% reduction of classification latency is large improvement.…”

Section: Methodsmentioning

confidence: 73%

“…We used the CUDD ZDD package [20]. For the comparison, we implemented a simple rule sorting algorithm (SR) [7], the method by Tanaka et al [13], sub-graph merging (SGM) [10], and the method by Hikage et al [11] in Java. We generated rules and headers with the standard packet benchmark tool for packet classification algorithms, namely, ClassBench [21].…”

Section: Methodsmentioning

confidence: 99%

“…Although an ordering violates the overlap relation, it can satisfy the classification policy if it satisfies the dependency relation. Therefore, Tanaka et al defined the constraint of ORO such that an ordering must satisfy the dependency relation [13], [14]. For example, although rules r P 2 and r P 3 in Table 1 Existing heuristics for ORO based on the overlap or dependency relations [2], [7]- [14] do not interchange dependent rules r i and r j .…”

Section: Definition 3: (Roro)mentioning

confidence: 99%

“…Thus, if we generate an initial solution at random, we cannot obtain a good solution. Therefore, our method uses the solution obtained by applying the reordering method of Tanaka et al [13] as the initial solution on line 1.…”

Section: Simulated Annealing By Exchanging Dependent Rules Without Anmentioning

confidence: 99%

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Simulated Annealing Method for Relaxed Optimal Rule Ordering

Harada

Tanaka

Mikawa

2020

IEICE Trans. Inf. & Syst.

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Recent years have witnessed a rapid increase in cyberattacks through unauthorized accesses and DDoS attacks. Since packet classification is a fundamental technique to prevent such illegal communications, it has gained considerable attention. Packet classification is achieved with a linear search on a classification rule list that represents the packet classification policy. As such, a large number of rules can result in serious communication latency. To decrease this latency, the problem is formalized as optimal rule ordering (ORO). In most cases, this problem aims to find the order of rules that minimizes latency while satisfying the dependency relation of the rules, where rules r i and r j are dependent if there is a packet that matches both r i and r j and their actions applied to packets are different. However, there is a case in which although the ordering violates the dependency relation, the ordering satisfies the packet classification policy. Since such an ordering can decrease the latency compared to an ordering under the constraint of the dependency relation, we have introduced a new model, called relaxed optimal rule ordering (RORO). In general, it is difficult to determine whether an ordering satisfies the classification policy, even when it violates the dependency relation, because this problem contains unsatisfiability. However, using a zero-suppressed binary decision diagram (ZDD), we can determine it in a reasonable amount of time. In this paper, we present a simulated annealing method for RORO which interchanges rules by determining whether rules r i and r j can be interchanged in terms of policy violation using the ZDD. The experimental results show that our method decreases latency more than other heuristics.

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Section: Methodsmentioning

confidence: 73%

Section: Methodsmentioning

confidence: 99%

Section: Definition 3: (Roro)mentioning

confidence: 99%

Section: Simulated Annealing By Exchanging Dependent Rules Without Anmentioning

confidence: 99%

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Simulated Annealing Method for Relaxed Optimal Rule Ordering

Harada

Tanaka

Mikawa

2020

IEICE Trans. Inf. & Syst.

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show abstract

“…They achieved better optimal rule order than (Hamed and Al-shear, 2006), but the algorithm took O(n3) time complexity in the worst case. Also, policy violation might occur (Tanaka et al, 2013).…”

Section: Related Workmentioning

confidence: 99%