Facial skin detection is an important step in facial surgical planning like as many other applications. There are many problems in facial skin detection. One of them is that the image features can be severely corrupted due to illumination, noise, and occlusion, where, shadows can cause numerous strong edges. Hence, in this paper, we present an automatic Expectation-Maximization (EM) algorithm for facial skin color segmentation that uses knowledge of chromatic space and varying illumination conditions to correct and segment frontal and lateral facial color images, simultaneously. The proposed EM algorithm leads to a method that allows for more robust and accurate segmentation of facial images. The initialization of the model parameters is very important in convergence of algorithm. For this purpose, we use a method for robust parameter estimation of Gaussian mixture components. Also, we use an additional class, which includes all pixels not modeled explicitly by Gaussian with small variance, by a uniform probability density, and amending the EM algorithm appropriately, in order to obtain significantly better results. Experimental results on facial color images show that accurate estimates of the Gaussian mixture parameters are computed. Also, other results on images presenting a wide range of variations in lighting conditions, demonstrate the efficiency of the proposed color skin segmentation algorithm compared to conventional EM algorithm.

The management of subscriptions and events is an important task in the content-based publish/subscribe system. A good management mechanism can not only produce lower matching costs to speed up the delivery of matched events to the interested subscribers but can also induce good load balancing for subscription storage. In this paper, we consider the construction of this kind of system over a peer-to-peer overlay network and propose two message-to-node mapping schemes for system management. We both analyze and simulate the performance of the proposed schemes. The simulation results show the superiority of our schemes over existing ones.

We developed a content delivery system using a partially reconfigurable FPGA to securely distribute digital content on the Internet. With partial reconfigurability of a Xilinx Virtex-II Pro FPGA, the system provides an innovative single-chip solution for protecting digital content. In the system, a partial circuit must be downloaded from a server to the client terminal to play content. Content will be played only when the downloaded circuit is correctly combined (=interlocked) with the circuit built in the terminal. Since each circuit has a unique I/O configuration, the downloaded circuit interlocks with the corresponding built-in circuit designed for a particular terminal. Thus, the interface of the circuit itself provides a novel authentication mechanism. This paper describes the detailed architecture of the system and clarify the feasibility and effectiveness of the system. In addition, we discuss a fail-safe mechanism and future work necessary for the practical application of the system.

This paper will propose a wolf attack probability (WAP) as a new measure for evaluating security of biometric authentication systems. The wolf attack is an attempt to impersonate a victim by feeding "wolves" into the system to be attacked. The "wolf" means an input value which can be falsely accepted as a match with multiple templates. WAP is defined as a maximum success probability of the wolf attack with one wolf sample. In this paper, we give a rigorous definition of the new security measure which gives strength estimation of an individual biometric authentication system against impersonation attacks. We show that if one reestimates using our WAP measure, a typical fingerprint algorithm turns out to be much weaker than theoretically estimated by Ratha et al. Moreover, we apply the wolf attack to a finger-vein-pattern based algorithm. Surprisingly, we show that there exists an extremely strong wolf which falsely matches all templates for any threshold value.

With the multiplication of attacks against computer networks, system administrators are required to monitor carefully the traffic exchanged by the networks they manage. However, that monitoring task is increasingly laborious because of the augmentation of the amount of data to analyze. And that trend is going to intensify with the explosion of the number of devices connected to computer networks along with the global rise of the available network bandwidth. So system administrators now heavily rely on automated tools to assist them and simplify the analysis of the data. Yet, these tools provide limited support and, most of the time, require highly skilled operators. Recently, some research teams have started to study the application of visualization techniques to the analysis of network traffic data. We believe that this original approach can also allow system administrators to deal with the large amount of data they have to process. In this paper, we introduce a tool for network traffic monitoring using visualization techniques that we developed in order to assist the system administrators of our corporate network. We explain how we designed the tool and some of the choices we made regarding the visualization techniques to use. The resulting tool proposes two linked representations of the network traffic and activity, one in 2D and the other in 3D. As 2D and 3D visualization techniques have different assets, we resulted in combining them in our tool to take advantage of their complementarity. We finally tested our tool in order to evaluate the accuracy of our approach.

PIN diodes for digital X-ray detection as a single photon counting sensor were fabricated on a floating-zone (FZ) n-type (111), high resistivity (5-10 kΩcm) silicon substrates (500 µm thickness). Its electrical properties such as the leakage current and the breakdown voltage were characterized. The size of pixels was 100 µm100 µm. The p+ guard-ring was formed around the active area to reduce the leakage current. After the p+ active area and guard-ring were fabricated by the ion-implantation, the extrinsic-gettering on the wafer backside was performed to reduce the leakage current by n+ ion-implantation. PECVD oxide was deposited as an IMD layer on front side and then, metal lines were formed on both sides of wafers. The leakage current of detectors was significantly reduced with a guard-ring when compared with that without a guard ring. The leakage current showed the strong dependency on the gap distance between the active area and the guard ring. It was possible to achieve the leakage current lower than 0.2 nA/cm2.

MUSIC-based estimation of direction of arrival (DOA) using universal steering vector (USV) is experimentally studied. A four-element array antenna and a four-channel receiver are employed for the experiment. In order to improve the accuracy of DOA estimation, USV which has already included the effect of mutual coupling between array elements and effect of array elements themselves is compensated to further include the electric delay and loss of four channels in the receiver. The compensated USV (C-USV) approach proposed in this paper does not need the time-consuming measurement of array element pattern because the compensating matrix for USV is obtained by measuring the S parameters between RF input ports of the feeding cables and IF output ports of the receiver. The experimental results of MUSIC-based DOA estimation show that C-USV approach is an accurate, effective and practical method for the MUSIC-based DOA estimation.

Tag collision is a major problem in the field of multi-tag identification in RFID systems. To solve this problem, many RFID systems adopt their own collision arbitration algorithms based on framed-structure slotted Aloha (FSSA) due to the simplicity of implementation. The frame size, meaning the number of slots in a frame, is a very important factor to inventory tags' responses in the FSSA. How to assign the frame size is therefore crucial to the collision arbitration performance. Since the existing collision arbitration methods do not consider the slot times of each slot when assigning frame size, they may increase overall identification time. By involving the slot times, we improve the collision arbitration performance of the conventional methods. Simulation results show that collision arbitration based on the proposed method is superior to that based on the conventional methods, irrespective of the number of tags.

Efforts have been devoted to maximizing memory array densities. However, as the devices are scaled down in dimension and getting closer to each other, electrical interference phenomena among devices become more prominent. Various features of 3-D memory devices are proposed for the enhancement of memory array density. In this study, we mention 3-D NAND flash memory device having pillar structure as the representative, and investigate the paired cell interference (PCI) which inevitably occurs in the read operation for 3-D memory devices in this feature. Furthermore, criteria for setting up the read operation bias schemes are also examined in existence with PCI.

This paper presents a new QoS model for end-to-end service provisioning in multi-hop wireless networks. In legacy IEEE 802.11e based multi-hop wireless networks, the fixed assignment of service classes according to flow's priority at every node causes priority inversion problem when performing end-to-end service differentiation. Thus, this paper proposes a new QoS provisioning model called Dynamic Hop Service Differentiation (DHSD) to alleviate the problem and support effective service differentiation between end-to-end nodes. Many previous works for QoS model through the 802.11e based service differentiation focus on packet scheduling on several service queues with different service rate and service priority. Our model, however, concentrates on a dynamic class selection scheme, called Per Hop Class Assignment (PHCA), in the node's MAC layer, which selects a proper service class for each packet, in accordance with queue states and service requirement, in every node along the end-to-end route of the packet. The proposed QoS solution is evaluated using the OPNET simulator. The simulation results show that the proposed model outperforms both best-effort and 802.11e based strict priority service models in mobile ad hoc environments.

A dispersion diagram is useful in interpreting the characteristics of a periodic structure. In particular, the fast-wave region, where the wave is radiating, and the slow-wave region, where the wave is guided, can be determined from the dispersion diagram. An electronically-controlled composite right/left-handed (CRLH) transmission line (TL) was previously proposed and utilized as a leaky-wave (LW) antenna operating in the fast-wave region. However, since a guided-wave application operates in the slow-wave region, it is meaningful to study slow-wave effects of the proposed TL. In this paper, the dispersion diagram is used to investigate the slow-wave factor (SWF), which is necessary to understand the fast/slow-wave operations. Furthermore, the frequency characteristics are measured to find the cut-off frequencies in the LH and RH regions. Based on experimental results, it is observed at a fixed frequency, 2.6-GHz, that the phase of a proposed 6-cell structure can be changed by up to 280 in the LH slow-wave region.

An all CMOS variable gain amplifier (VGA) which features wide dB-linear gain range per stage (45 dB), low power consumption (1.32 mW), small chip size (0.13 mm2), and low supply voltage (1.2 V) is described. The dB-linear range is extended by reducing the supply voltage of the conventional V-to-I converter. The two-stage VGA implemented in 0.18 µm CMOS offers 90 dB of gain variation, 3 dB bandwidth of greater than 21 MHz, and max/min input IP3 and P1 dB, respectively, of -5/-42 and -12/-50 dBm.

Today, users themselves are becoming subjects of content creation. The fact that blog, wiki, and UCC have become very popular shows that users want to participate to create and modify digital content. Users who participate in composing content also want to have their copyrights on their modification parts. Thus, a copyright protection system for the content which can be modified by multiple users is required. However, the conventional DRM (Digital Rights Management) systems like OMA DRM are not suitable for the modifiable content because they do not support the content created and modified by different users. Therefore in this paper, we propose a new copyright protection system which allows each modifier of the content created and modified by multiple users to have one's own copyright. We propose data formats and protocols, and analyze the proposed system in terms of the correctness and security. Performance evaluation in the view of response time shows that the proposed system is 2 to 18 times shorter than other comparative schemes.

This paper proposes a spectroscopic method and system for preventing spoofing of biometric authentication. One of its focus is to enhance biometrics authentication with a spectroscopic method in a multi-factor manner such that a person's unique 'spectral signatures' or 'spectral factors' are recorded and compared in addition to a non-spectroscopic biometric signature to reduce the likelihood of imposter getting authenticated. By using the 'spectral factors' extracted from reflectance spectra of real fingers and employing cluster analysis, it shows how the authentic fingerprint image presented by a real finger can be distinguished from an authentic fingerprint image embossed on an artificial finger, or molded on a fingertip cover worn by an imposter. This paper also shows how to augment two widely used biometrics systems (fingerprint and iris recognition devices) with spectral biometrics capabilities in a practical manner and without creating much overhead or inconveniencing their users.

This research considers an efficient method for calculating the transition matrix in an MPL (Max-Plus Linear) state-space representation. This matrix can be generated by applying the Kleene star operator to an adjacency matrix. The proposed method, based on the idea of a topological sort in graph theory and block splitting, is able to calculate the transition matrix efficiently.

We propose an algorithm for finding heavy hitters in terms of cardinality (the number of distinct items in a set) in massive traffic data using a small amount of memory. Examples of such cardinality heavy-hitters are hosts that send large numbers of flows, or hosts that communicate with large numbers of other hosts. Finding these hosts is crucial to the provision of good communication quality because they significantly affect the communications of other hosts via either malicious activities such as worm scans, spam distribution, or botnet control or normal activities such as being a member of a flash crowd or performing peer-to-peer (P2P) communication. To precisely determine the cardinality of a host we need tables of previously seen items for each host (e.g., flow tables for every host) and this may infeasible for a high-speed environment with a massive amount of traffic. In this paper, we use a cardinality estimation algorithm that does not require these tables but needs only a little information called the cardinality summary. This is made possible by relaxing the goal from exact counting to estimation of cardinality. In addition, we propose an algorithm that does not need to maintain the cardinality summary for each host, but only for partitioned addresses of a host. As a result, the required number of tables can be significantly decreased. We evaluated our algorithm using actual backbone traffic data to find the heavy-hitters in the number of flows and estimate the number of these flows. We found that while the accuracy degraded when estimating for hosts with few flows, the algorithm could accurately find the top-100 hosts in terms of the number of flows using a limited-sized memory. In addition, we found that the number of tables required to achieve a pre-defined accuracy increased logarithmically with respect to the total number of hosts, which indicates that our method is applicable for large traffic data for a very large number of hosts. We also introduce an application of our algorithm to anomaly detection. With actual traffic data, our method could successfully detect a sudden network scan.

Unforgeability of digital signatures is closely related to the security of hash functions since hashing messages, such as hash-and-sign paradigm, is necessary in order to sign (arbitrarily) long messages. Recent successful collision finding attacks against practical hash functions would indicate that constructing practical collision resistant hash functions is difficult to achieve. Thus, it is worth considering to relax the requirement of collision resistance for hash functions that is used to hash messages in signature schemes. Currently, the most efficient strongly unforgeable signature scheme in the standard model which is based on the CDH assumption (in bilinear groups) is the Boneh-Shen-Waters (BSW) signature proposed in 2006. In their scheme, however, a collision resistant hash function is necessary to prove its security. In this paper, we construct a signature scheme which has the same properties as the BSW scheme but does not rely on collision resistant hash functions. Instead, we use a target collision resistant hash function, which is a strictly weaker primitive than a collision resistant hash function. Our scheme is, in terms of the signature size and the computational cost, as efficient as the BSW scheme.

We propose a token-bucket based rate control algorithm that satisfies both maximum and minimum rate constraints with computational complexity of O(1). The proposed algorithm allocates the remaining bandwidth in a strict priority queuing manner to the flows with different priorities and in a weighted fair queuing manner to the flows within the same priority.

Image quality assessment method is a methodology that measures the difference of quality between the reference image and its distorted one. In this paper, we propose a novel reduced-reference (RR) quality assessment method for JPEG-2000 compressed images, which exploits the statistical characteristics of context information extracted through partial entropy decoding or decoding. These statistical features obtained in the process of JPEG-2000 encoding are transmitted to the receiver as side information and used to estimate the quality of images transmitted over various noisy channels at the decompression side. In the framework of JPEG-2000, the context of a current coefficient is determined depending on the pattern of the significance and/or the sign of its neighbors in three bit-plane coding passes and four coding modes. As the context information represents the local property of images, it can efficiently describe textured pattern and edge orientation. The quality of transmitted images is measured by the difference of entropy of context information between received and original images. Moreover, the proposed quality assessment method can directly process the images in the JPEG-2000 compressed domain without full decompression. Therefore, our proposed can accelerate the work of assessing image quality. Through simulations, we demonstrate that our method achieves fairly good performance in terms of the quality measurement accuracy as well as the computational complexity.

Wireless Mesh Network (WMN) is a promising model with benefits in coverage extension and throughput improvement. In WMN, multiple channels are available for improving system performance through concurrent transmission. For maximum utilization, per-node channel quality and inter-channel interference should be considered in multi-channel assignment. We propose a new multi-channel assignment method. First, we model the mesh network connectivity after a multi-graph which has multiple edges between two nodes. From this connectivity graph, we generate a multi-channel conflict graph, then we allocate multiple channels so that they do not overlap, using list coloring algorithm. We also propose a new sub-graph list coloring algorithm to enhance channel allocation performance. From computer simulations, we verify the performance of the algorithm.