The packet classification problem to determine the behavior of incoming packets at the network devices. The processing latency of packet classification by linear search is proportional to the number of classification rules. To limit the latency caused by classification to a certain level, we should develop a classification algorithm that classifies packets in a time independent of the number of classification rules. Arbitrary (including noncontiguous) bitmask rules are efficiently expressive for controlling higher layer communication, achiving access control lists, Quality of Service and so on. In this paper, we propose a classification algorithm based on run-based trie [1] according to arbitrary bitmask rules. The space complexity of proposed algorithm is in linear in the size of a rule list. The time complexity except for construction of that can be regarded as constant which is independent the number of rules. Experimental results using a packet classification algorithm benchmark [2] show that our method classifies packets in constant time independent of the number of rules.

Network devices, such as routers or L3 switches, have a feature called packet-filtering for network security. They determine whether or not to pass arriving packets by applying filtering rules to them. If the number of comparisons of packets with rules increases, the time required for a determination will increase, which will result in greater communication delay. Various algorithms for optimizing filtering tables to minimize the load of packet filtering, which directly impacts the communication delay, have been proposed. In this paper, first we introduce an adaptive packet filter based on an algorithm that reconstructs the filtering table according to the frequency distribution of arrival packets. Next, we propose a new reconstruction algorithm based on grouping of dependent rules. Grouping dependent rules makes it possible to sort the rules in the table by the frequency of matching. Finally, we show the effectiveness of our algorithm by comparing it against previously reported algorithms.

Recent years have witnessed a rapid increase in cyber-attacks 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 ri and rj are dependent if there is a packet that matches both ri and rj 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 ri and rj can be interchanged in terms of policy violation using the ZDD. The experimental results show that our method decreases latency more than other heuristics.

Packet classification is a fundamental task in the control of network traffic, protection from cyber threats. Most layer 3 and higher network devices have a packet classification capability that determines whether to permit or discard incoming packets by comparing their headers with a set of rules. Although linear search is an intuitive implementation of packet classification, it is very inefficient. Srinivasan et al. proposed a novel lookup scheme using a hierarchical trie instead of linear search, which realizes faster packet classification with time complexity proportional to rule length rather than the number of rules. However, the hierarchical trie and its various improved algorithms allow only single prefix rules to be processed. Since it is necessary for layer 4 and higher packet classifications to deal with arbitrary bitmask rules in the hierarchical trie, we propose a run-based trie based on the hierarchical trie, but extended to deal with arbitrary bitmask rules. Our proposed algorithm achieves O((dW)2) query time and O(NdW) space complexity with N rules of length dW. The query time of our novel alrorithm doesn't depend on the number of rules. It solves the latency problem caused by increase of the rules in firewalls.

Orthogonal multi-carrier direct sequence code division multiple access (orthogonal MC DS-CDMA) is a combination of orthogonal frequency division multiplexing (OFDM) and time-domain spreading, while multi-carrier code division multiple access (MC-CDMA) is a combination of OFDM and frequency-domain spreading. In MC-CDMA, a good bit error rate (BER) performance can be achieved by using frequency-domain equalization (FDE), since the frequency diversity gain is obtained. On the other hand, the conventional orthogonal MC DS-CDMA fails to achieve any frequency diversity gain. In this paper, we propose a new orthogonal MC DS-CDMA that can obtain the frequency diversity gain by applying FDE. The conditional BER analysis is presented. The theoretical average BER performance in a frequency-selective Rayleigh fading channel is evaluated by the Monte-Carlo numerical computation method using the derived conditional BER and is confirmed by computer simulation of the orthogonal MC DS-CDMA signal transmission.

Packet classification is used to determine the behavior of incoming packets in network devices according to defined rules. As it is achieved using a linear search on a classification rule list, a large number of rules will lead to longer communication latency. To solve this, the problem of finding the order of rules minimizing the latency has been studied. Misherghi et al. and Harada et al. have proposed a problem that relaxes to policy-based constraints. In this paper, we show that the Relaxed Optimal Rule Ordering (RORO) for the allowlist is NP-hard, and by reducing from this we show that RORO for the general rule list is NP-hard. We also propose a heuristic algorithm based on the greedy method for an allowlist. Furthermore, we demonstrate the effectiveness of our method using ClassBench, which is a benchmark for packet classification algorithms.