Sukhoon Kang

A Fully Embedded LTCC Multilayer BPF for 3-D Integration of 40-GHz Radio

This paper demonstrates a low loss fully embedded multilayer bandpass filter (BPF) using low-temperature cofired ceramic (LTCC) technology for 3-D integration of 40-GHz multimedia wireless system (MWS) radio. The LTCC filter implemented in a stripline configuration occupies an area of only 5.5 times 2.3 times 0.6 mm including shielding structure and coplanar waveguide (CPW) transitions. The measured insertion loss was as small as 1.9 dB at a center frequency of 41.8 GHz, and the return loss was 12.2 dB including the loss associated with two CPW-to-stripline transitions. This six-layer BPF showed 3-dB bandwidth of 10.5% from 39.6 to 44.0 GHz at a center frequency of 41.8 GHz and suppressed the local oscillator (LO) signal to 20.2 dB at a local oscillator frequency of 38.8 GHz, making it suitable for the 40 GHz MWS applications.

A probe detection model using the analysis of the fuzzy cognitive maps

The rapid growth of network-based information systems has resulted in continuous research of security issues. Intrusion Detection Systems (IDS) is an area of increasing concerns in the Internet community. Recently, a number of IDS schemes have been proposed based on various technologies. However, the techniques, which have been applied in many systems, are useful only for the existing patterns of intrusion. They can not detect new patterns of intrusion. Therefore, it is necessary to develop a new IDS technology that can find new patterns of intrusion. Most of IDS sensors provide less than 10% rate of false positives. In this paper, we proposed a new network-based probe detection model using the fuzzy cognitive maps that can detect intrusion by the Denial of Service (DoS) attack detection method utilizing the packet analyses. The probe detection systems using fuzzy cognitive maps (PDSuF) capture and analyze the packet information to detect SYN flooding attack. Using the results of the analysis of decision module, which adopts the fuzzy cognitive maps, the decision module measures the degree of risk of the DoS and trains the response module to deal with attacks. For the performance evaluation, the “IDS Evaluation Data Set” created by MIT was used. From the simulation we obtained the average true positive rate of 97.094% and the average false negative rate of 2.936%.

Supervised IAFC neural network based on the fuzzification of learning vector quantization

In this paper, a fuzzy LVQ(Learning Vector Quantization) is proposed which is based on the fuzzification of LVQ. The proposed FLVQ(Fuzzy Learning Vector Quantization) uses the different learning rate depending on the correctness of classification. When the classification is correct, the amount of update is determined by consideration of location of the input vector relative to the decision boundary. When the classification is not correct, the amount of update is determined by the degree of belongingness of the input vector to the winning class. The supervised IAFC(Integrated Adaptive Fuzzy Clustering) neural network 3, which uses FLVQ, is introduced in this paper. The supervised IAFC neural network 3 is both stable and plastic because it uses the control structure which is similar to that of Adaptive Resonance Theory(ART)-1 neural network. We used iris data set to compare the performance of the supervised IAFC neural network 3 with those of LVQ algorithm and backpropagation neural network. The supervised IAFC neural network 3 yielded fewer misclassifications than LVQ algorithm and backpropa-gation neural network.

Two-phase identification algorithm based on fuzzy set and voting for intelligent multi-sensor data fusion

Multi-sensor data fusion techniques combine data from multiple sensors in order to get more accurate and efficient meaningful information through several intelligent process levels that may not be possible from a single sensor alone. One of the most important parts in the intelligent data fusion system is the identification fusion, and it can be categorized into physical models, parametric classification and cognitive-based models. In this paper, we present a novel identification fusion method by integrating two fusion approaches such as the parametric classification techniques and the cognitive-based models for achieving high intelligent decision support. We also have confirmed that the reliability and performance of two-phase identification algorithm never fall behind other fusion methods. We thus argue that our heuristics are required for effective decision making in real time for intelligent military situation assessment.

An intelligent event-driven interface agent for interactive digital contents in ubiquitous environments

Interactive digital contents in the field of networked media and ubiquitous computing enable the consumers to test the features of the product from their handheld computers as if they were using it in real life, by simulating the actions and responses of the product. This new type of digital content can be used extensively to make sales personnel training manuals, sales tools, user manuals and user trouble shooting documents. In this paper, we present the enhanced characteristics of the event flow chart with which the events in an intelligent event-driven interface agent for interactive digital contents in ubiquitous environments, named PlayMo-based agent, are structured. A tree structure can be formed from the array of options or functions. PlayMo-based agent generates the events and gives action commands according to this tree structure, allowing user to perfectly simulate the features and functions of a product simply and directly. The solution to provide intelligent interaction between human and digital contents makes it possible to recreate digital contents by bringing interactivity and intelligence into it.

A transaction processing model for performance analysis in multilevel-secure database systems

Although many concurrency control schemes have been developed, a thorough understanding of their actual performance is not enough. Numerous performance studies in non-secure centralized databases have been done in the past decade. However, their results cannot be directly applied to multilevel-secure databases, since in addition to single-level concurrency control, multilevel-secure databases deal with new problems of convert channel due to read-down conflict operations. Investigating their impact on transaction scheduling is a crucial issue. The concurrency control requirements for tran-saction processing in an MLS/DBMS are different from those in conventional transaction processing systems with respect to inclusion of covert-channel freeness. In particular, there is the need to coordinate transactions at different security levels avoiding both potential covert timing channels and the starvation of transactions at high security levels. Using a secure transaction processing model, we can evaluate the throughput and response time characteristics of multilevel-secure concurrency control schemes under a wide variety of database workloads and system configurations.

A covert timing channel-free optimistic concurrency control scheme for multilevel secure database management systems

This paper presents a set of multilevel-secure optimistic concurrency control (MLS/OCC) scheme that has several desirable properties: If lower-level transactions were somehow allowed to continue with its execution in spite of the conflict of high-level transactions, covert timing channel-freeness would be satisfied. This sort of optimistic approach for conflict insensitiveness and the properties of non-blocking and deadlock freedom make the optimistic concurrency control scheme especially attractive to multilevel-secure transaction processing. Unlike pessimistic approaches, the MLS/OCC scheme never delays or rejects an operation submitted by a lower-level transaction which is passed the mandatory access control. Instead, the read and write operations are processed freely without updating the actual database. Therefore, it is reasonable to assert that MLS/OCC scheme is allowed to avoid the abort of lower-level transactions in order to close covert timing channel, nevertheless guaranteeing conflict-preserving serializability. The basic refinement philosophy for the solution on starvation problem is an incorporation of multiple versions of low-level datainto MLS/OCC. This kind of intelligent channel-free concurrency control scheme satisfies the B3 or higher level of the US TCSEC requirements.