Packet classification categorizes incoming packets into multiple forwarding classes based on pre-defined filters. This categorization makes information accessible for quality of service or security handling in the network. In this paper, we propose a scheme which combines the Aggregate Bit Vector algorithm and the Pruned Tuple Space Search algorithm to improve the performance of packet classification in terms of speed and storage. We also present the procedures of incremental update. Our scheme is evaluated with filter databases of varying sizes and characteristics. The experimental results demonstrate that our scheme is feasible and scalable.

This letter proposes a new hybrid EM wave absorber with the crossed-wedge shape, which can be applied to 3 m semi anechoic chambers. In this study, we designed a new hybrid EM wave absorber with the crossed-wedge shape, which consisted of the inorganic and organic thin corrugated dielectric lossy sheet containing organic conductive fibers. Then the 3 m semi anechoic chamber is constructed in the size of 9.0 m6.0 m5.7 m (LWH) using these absorbers, and also the normalized site attenuation (NSA) is measured according to ANSI C63.4 in the frequency range of 30 MHz to 1 GHz. As a result, the measured NSA is obtained within 3 dB of the theoretical one.

The single input rule modules connected fuzzy inference method (SIRMs method) by Yubazaki et al. can decrease the number of fuzzy rules drastically in comparison with the conventional fuzzy inference methods. Moreover, Seki et al. have proposed a functional-type SIRMs method which generalizes the consequent part of the SIRMs method to function. However, these SIRMs methods can not be applied to XOR (Exclusive OR). In this paper, we propose a "kernel-type SIRMs method" which uses the kernel trick to the SIRMs method, and show that this method can treat XOR. Further, a learning algorithm of the proposed SIRMs method is derived by using the steepest descent method, and compared with the one of conventional SIRMs method and kernel perceptron by applying to identification of nonlinear functions, medical diagnostic system and discriminant analysis of Iris data.

This letter proposes a new retransmission persistence management scheme for selective repeat automatic repeat request (SR-ARQ). By considering the overall traffic load that has to be managed by SR-ARQ, the proposed scheme arbitrates the retransmission persistence to prevent an abrupt delay increment due to excessive link-level local retransmissions. OPNET simulations show that SR-ARQ performs better with the proposed scheme than with a fixed value of retransmission persistence in terms of the throughput of transmission control protocol (TCP).

In this paper, first the temperature distribution of the pyramidal EM-wave absorber is calculated in the coupled method. Next, the injected power to the EM-wave absorber is changed to estimate the maximum power density that the EM-wave absorber can resist. As a result, the limitation of the injecting power density to a pyramidal EM-wave absorber is achievable.

In deep submicron designs, predicting gate delays with interconnect load is a noteworthy work for Static Timing Analysis (STA). The effective capacitance Ceff concept and the Thevenin model that replaces the gate with a linear resistor and a voltage source are usually used to calculate the delay of gate with interconnect load. In conventional methods, it is not considered that the charges transferred into interconnect load and Ceff in the Thevenin model are not equal. The charge difference between interconnect load and Ceff has the large influence to the accuracy of computing Ceff. In this paper, an advanced effective capacitance model is proposed to consider the above problem in the Thevenin model, where the influence of the charge difference is modeled as one part of the effective capacitance to compute the gate delay. Experimental results show a significant improvement in accuracy when the charge difference between interconnect load and Ceff is considered.

This paper presents a novel approach for robust impulsive synchronization of uncertain complex dynamical networks, each node of which possesses chaotic dynamics with different parameters perturbation and external disturbances as well as unknown but bounded network coupling effects. A new sufficient condition is proposed that guarantees the global robust synchronizing of such a network. Finally, the effectiveness of the proposed approach is evaluated by performing simulations on two illustrative examples.

Let us introduce n ( ≥ 2) mappings fi (i=1,,n ≡ 0) defined on reflexive real Banach spaces Xi-1 and let fi:Xi-1 → Yi be completely continuous on bounded convex closed subsets Xi-1(0) ⊂ Xi-1. Moreover, let us introduce n set-valued mappings Fi : Xi-1 Yi → Fc(Xi) (the family of all non-empty compact subsets of Xi), (i=1,,n ≡ 0). Here, we have a fixed point theorem in weak topology on the successively recurrent system of set-valued mapping equations:xi ∈ Fi(xi-1, fi(xi-1)), (i=1,,n ≡ 0). This theorem can be applied immediately to analysis of the availability of system of circular networks of channels undergone by uncertain fluctuations and to evaluation of the tolerability of behaviors of those systems.

An ICI (Inter-Cell Interference) mitigation algorithm for exploiting macroscopic diversity for an up-link OFDMA (Orthogonal Frequency Division Multiple Access) system is proposed. To reduce the influence of carrier collision, the order of resource allocation is coordinated based on the location of each MS (Mobile Station) and the associated carrier group. This consideration significantly reduces ICI and enhances throughput at the boundary region.

We propose a complexity-reducing algorithm for serial scheduled min-sum decoding that reduces the number of check nodes to process during an iteration. The check nodes to skip are chosen based on the reliability, a syndrome and a log-likelihood-ratio (LLR) value, of the incoming messages. The proposed algorithm is evaluated by computer simulations and shown to reduce the decoding complexity about 20% compared with a conventional serial scheduled min-sum decoding with small fractional decibel degradation in error correction performance.

An approach to image thresholding based on the plausibility of object and background regions by adopting a co-occurrence matrix and category utility is presented. The effectiveness of the proposed method is shown through the experimental results tested on several images and compared with conventional methods.

Network intrusion detection systems rely on a signature-based detection engine. When under attack or during heavy traffic, the detection engines need to make a fast decision whether a packet or a sequence of packets is normal or malicious. However, if packets have a heavy payload or the system has a great deal of attack patterns, the high cost of payload inspection severely diminishes detection performance. Therefore, it would be better to avoid unnecessary payload scans by checking the protocol fields in the packet header, before executing their heavy operations of payload inspection. When payload inspection is necessary, it is better to compare a minimum number of attack patterns. In this paper, we propose new methods to classify attack signatures and make pre-computed multi-pattern groups. Based on IDS rule analysis, we grouped the signatures of attack rules by a multi-dimensional classification method adapted to a simplified address flow. The proposed methods reduce unnecessary payload scans and make light pattern groups to be checked. While performance improvements are dependent on a given networking environment, the experimental results with the DARPA data set and university traffic show that the proposed methods outperform the most recent Snort by up to 33%.

In 1999, Gennaro, Halevi and Rabin proposed a signature which achieves provable security without assuming the random oracles, and it is the first RSA-type signature whose security is proved in the standard model. Since that time, several signatures have been proposed to achieve better efficiency or useful property along with the provable security in the standard model. In this paper, we construct a trapdoor hash function, and design an efficient online/offline signature by using the trapdoor hash function. Our signature scheme requires only one non-modular multiplication of two small integers for online signing, and it provides the fastest online signing among all online/offline signatures that achieve provable security in the standard model.

In the near future, wireless local area networks (WLANs) will overlap to provide continuous coverage over a wide area. In such ubiquitous WLANs, a mobile node (MN) moving freely between multiple access points (APs) requires not only permanent access to the Internet but also continuous communication quality during handover. In order to satisfy these requirements, an MN needs to (1) select an AP with better performance and (2) execute a handover seamlessly. To satisfy requirement (2), we proposed a seamless handover method in a previous study. Moreover, in order to achieve (1), the Received Signal Strength Indicator (RSSI) is usually employed to measure wireless link quality in a WLAN system. However, in a real environment, especially if APs are densely situated, it is difficult to always select an AP with better performance based on only the RSSI. This is because the RSSI alone cannot detect the degradation of communication quality due to radio interference. Moreover, it is important that AP selection is completed only on an MN, because we can assume that, in ubiquitous WLANs, various organizations or operators will manage APs. Hence, we cannot modify the APs for AP selection. To overcome these difficulties, in the present paper, we propose and implement a proactive AP selection method considering wireless link condition based on the number of frame retransmissions in addition to the RSSI. In the evaluation, we show that the proposed AP selection method can appropriately select an AP with good wireless link quality, i.e., high RSSI and low radio interference.

Orthogonal frequency division multiplexing (OFDM) is a critical technology in 3G evolution systems, which can effectively avoid intra-cell interference, but may bring with serious inter-cell interference. Inter-cell interference cancellation is one of effective schemes taken in mitigating inter-cell interference, but for many existing schemes in inter-cell interference cancellation, various generalized spatial diversities are taken, which always bring with extra interference and blind spots, or even need to acquire extra information on source and channel. In this paper, a novel inter-cell interference mitigation method is proposed for 3G evolution systems. This method is based on independent component analysis in blind source separation, and the input signal to interference plus noise ratio (SINR) is set as objective function. By generalized eigenvalue decomposition and algorithm iterations, maximum signal noise ratio (SNR) can be obtained in output. On the other hand, this method can be worked with no precise knowledge of source signal and channel information. Performance evaluation shows that such method can mitigate inter-cell interference in a semi-blind state, and effectively improve output SNR with the condition that lower input SINR, higher input SNR and longer lengths of the processing frame.

This paper describes the application techniques of the latency insertion method (LIM) to CMOS circuit simulations. Though the existing LIM algorithm to CMOS circuit performs fast transient analysis, CMOS circuits are not modeled accurately. As a result, they do not provide accurate simulations. We propose a more accurate LIM scheme for the CMOS inverter circuit by adopting a more accurate model of the CMOS inverter characteristics. Moreover, we present the way to expand the LIM algorithm to general CMOS circuit simulations. In order to apply LIM to the general CMOS circuits which consist of CMOS NAND and NOR, we derive the updating formulas of the explicit form of the LIM algorithm. By using the explicit form of the LIM scheme, it becomes easy to take in the characteristics of CMOS NAND and NOR into the LIM simulations. As a result, it is confirmed that our techniques are useful and efficient for the simulations of CMOS circuits.

The notion of anonymous signatures has recently been formalized by [18], which captures an interesting property that a digital signature can sometimes hide the identity of the signer, if the message is hidden from the verifier. However, in many practical applications, e.g., an anonymous paper review system mentioned in [18], the message for anonymous authentication is actually known to the verifier. This implies that the effectiveness of previous anonymous signatures may be unjustified in these applications. In this paper, we extend the previous models, and develop a related primitive called strong anonymous signatures. For strong anonymous signatures, the identity of the signer remains secret even if the challenge message is chosen by an adversary. We then demonstrate some efficient constructions and prove their security in our model.

In this paper, an image restoration method using the Wiener filter is proposed. In order to bring the theory of the Wiener filter consistent with images that have spatially varying statistics, the proposed method adopts the locally adaptive Wiener filter (AWF) based on the universal Gaussian mixture distribution model (UNI-GMM) previously proposed for denoising. Applying the UNI-GMM-AWF for deconvolution problem, the proposed method employs the stationary Wiener filter (SWF) as a pre-filter. The SWF in the discrete cosine transform domain shrinks the blur point spread function and facilitates the modeling and filtering at the proceeding AWF. The SWF and UNI-GMM are learned using a generic training image set and the proposed method is tuned toward the image set. Simulation results are presented to demonstrate the effectiveness of the proposed method.

The RFID tag system has received attention as an identification source. Each RFID tag is attached to some object. With the unique ID of the RFID tag, a user identifies the object provided with the RFID tag, and derives appropriate information about the object. One of important applications of the RFID technology is the position estimation of RFID tags. It can be very useful to acquire the location information concerning the RFID tags. It can be applied to navigation systems and positional detection systems for robots etc. In this paper, we propose a new position estimation method of RFID tags by using a probabilistic approach. In this method, mobile objects (person and robot, etc.) with RFID readers estimate the positions of RFID tags with multiple communication ranges. We show the effectiveness of the proposed method by computer simulations.

In PKC 2004, Choi et al. proposed an ID-based authenticated group key agreement (AGKA) protocol using bilinear pairings. Unfortunately, their protocol suffered from an impersonation attack and an insider colluding attack. In 2008, Choi et al. presented an improvement to resist insider attacks. In their modified protocol, they used an ID-based signature scheme on transcripts for binding them in a session to prevent replay of transcripts. In particular, they smartly used the batch verification technique to reduce the computational cost. In this paper, we first show that Choi et al.'s modified AGKA protocol still suffers from an insider colluding attack. Then, we prove that the batch verification of the adopted ID-based signature scheme in their modified protocol suffers from a forgery attack.