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Recently, phishing, a new type of crime, has increased due to the expansion of the use of smart phones, and financial losses have been increasingly reported. As damage cases, which have become sophisticated through the use of smart phones, crimes occurring in relation to smart phones are becoming a concern. In this paper, we discuss crimes such as phishing, voice phishing, and smishing, which can occur in a smart phone environment. In particular, we discuss the issue of smishing attacks, as well as the problems and preventive measures of these attacks.

As the right to be forgotten and privacy protection are becoming more important in modern society, the security threats that exist on Social Networking Services (SNS) create critical problems. Information leaked from security accidents on SNS is provided to a third party and used for malicious intentions, generating additional damages. This study discusses the concept of the right to be forgotten and the security threats on SNS that invade the privacy of an owner of information. In addition, it proposes a model that has User Privacy Policy (UPP), Dual Watermarking Scheme, and FaceCloak functions that provide strong information controllability so that we can resolve security threats and realize the right to be forgotten.

The second author’s affiliation was wrong in the original version. The correct affiliation is given below

Electronic structures of quantum rings strongly depend on the strain profiles caused by the material environment around the ring. We will investigate the strain distributions and electronic structures of quantum rings capped by a support material of which lattice constant is smaller than those of the substrate and active material, and compare the results with a conventional quantum ring. The support material considerably weakens the longitudinal strains and biaxial strain of quantum rings as well as the hole confinement potentials. The unique band alignment of the structure enables the coexistence of type-I and type-II band alignments.

In this paper, we propose the hardware architecture of bilateral filter that can smooth image while preserving edges for the real-time image processing. Bilateral filter is nonlinear combination of nearby image values. As the time complexity of bilateral filter is O (total pixel size ∗ filter kernel size 2), the real-time processing is difficult. We reduce the time complexity of bilateral filter using parallel architecture to achieve real-time performance.

In this paper, a recovery method using extendible hashing in a shared-nothing spatial database cluster is proposed. The purpose is to increase the recovery performance and to decrease overhead of the system. In the case of failure, the recovery method in a database cluster restores the database using replicated data from neighbor node. When detect a failure, neighbor node writes the cluster log, and it must be transferred to a failure node. However, in neighbor node, one transaction makes several logs, and increase transferring log size. Also, this increases the recovery time and overhead of the internal network. The proposed method defines a novel cluster log that is composed of update type and a pointer to a record through RID or primary key. This is managed by extendible hashing in main memory. The last transaction replaces the cluster log. Through sending of last updated data, the number of cluster logs and transaction count in failure node are decreased. As a result, the method in this paper increased the availability of the database cluster.

Spatio-temporal OLAP is an operation providing the spatial hierarchy and the temporal hierarchy for decision making. In this paper, we propose the extended R-tree for spatio-temporal OLAP operations. The proposed method focuses on using a hybrid index of the extended aggregation R-tree and the temporal hash table. The aggregation R-tree is extended for the spatial hierarchy, which is based on the R-tree. It provides a pre-aggregation for fast retrieval of aggregated values. For a temporal hierarchy, the temporal hash table has buckets which are added levels of temporal unit. It is transformed for the temporal hierarchy. It provides pre-aggregation of each temporal unit as year, month and so on. The proposed method supports spatio-temporal analysis since it provides the spatio-temporal hierarchy and the pre-aggregated value.

According to increase of spatial data, many decision support systems require the fast spatio-temporal analysis. This paper proposes the improved index for efficient OLAP in a spatial data warehouse. The main idea is to use the hybrid index of the extended aggregation R-tree and the sorted hash table. The extended R-tree supports the spatial hierarchy with the level of R-tree. Also, it provides pre-aggregation for fast retrieval of the aggregated value. The sorted hash table is the transformed hash table for supporting the temporal hierarchy. So, it provides pre-aggregation of each temporal unit, year, month and etc. By the proposed hybrid index, an efficient spatio-temporal analysis can be sup-ported since it provides the spatio-temporal hierarchy and the pre-aggregated value.

In highly concurrent field such as location based services, massive objects are moving concurrently. Due to continuously changing nature of their location, traditional indexes cannot provide the real-time response since query processing is frequently blocked by node-split or region propagation as the locations of objects change. In this paper, the modified R-tree structure with lock-free querying for multi-dimension data, Rver-tree, is proposed. Basically, Rver-tree uses the new versioning technique. When updating data such as key update(region propagation) and index restructure(node-split), it never physically modify original data, rather creates new version for compensating data intactness. Due to data intactness, search operation can access data without any locking or latching by reading old version. In the performance evaluation, it is proven that search operation of Rver-tree is at least two times faster than a previous work.

WDM networks using wavelength routing are considered to be potential candidates for the next generation backbone networks. One of the critical issues of the future network is a provision of proper QoS guarantees for a wide variety of multimedia multicast service. This paper concerns with the problem of optical multicast routing with QoS guarantees in WDM networks. Using Virtual Source (VS) nodes, we proposes a new MCRWA method for a multicast session, combining the VS-based tree method with Multi-Wavelength Minimum Interference Path Routing (MW-MIPR). This paper also proposes a QoS MCRWA method in combination with QoS constraints and a recovery strategy based on the differentiated QoS service model to provide QoS guarantee for a wide variety of multicast application in the next generation optical networks.

This paper proposes an efficient algorithm for load-sharing and fault-tolerance in Internet-based clustering systems. The algorithm creates a global scheduler based on the Weighted Factoring algorithm. And it applies an adaptive granularity strategy and the refined fixed granularity algorithm for better performance. It may also execute a partial job several times for fault-tolerance. For the simulation, the matrix multiplication using PVM is used in a Internet-based clustering system. Compared to other algorithms such as Send, GSS and Weighted Factoring, the proposed algorithm results in an improvement of performance by 55%, 63% and 20%, respectively. Also, this paper shows that it can process the fault-tolerance.

In mobile database system, a voluntary or involuntary disconnection has happened frequently. This problem causes inconsistency. This paper has proposed the conflict detection method for maintaining consistency. The proposed method uses the histories of transactions consisted of the information of operations and the valid time of transactions processed in off-line. Compared with other methods, the transaction time resembles others and the conflict detection time is decreased about 17%.

Recently, the necessity of using spatial information for webbased and mobile applications has been rapidly increasing. However, there are two challenges against the publication of spatial information. The first one is efficient data transmission, which is both large and complex, through a slow wireless communication link. The second one is how to provide the resultant adapted data for varied and heterogeneous clients. This paper proposes a new transmission method, namely, the Scale-Dependent Transmission method, with the purpose of improving the efficiency of vector spatial data transmission across the Internet. Its main idea is "Transmit what can be seen". Scale is regarded as a factor naturally associated with spatial features so that not all features are visible to users at a certain scale. Additionally, the paper proposes Wavelet-based map generalization algorithm, which achieves O(n) time complexity and adapts data to fit the needs of varying clients. Experiments show that the response times of individual operations were substantially reduced when using the proposed method.

The common bottleneck of web proxy servers is disk I/O. Most general-purpose file systems are very inefficient on handling web cache workload and have high overloads. In this paper we are interested in exploring a way to reduce disk I/O overhead by using raw disk instead of the file system. To show the superior performance potential of raw disk approach, we design a simple Block-structured Storage Management System (BSMS) and implement Web Proxy Server over RAW disk (WPS-RAW) that incorporates BSMS in Squid. Comprehensive experimental evaluations by using the Web Polygraph proxy performance benchmark suggest that raw disk can be a good solution to improve disk I/O performance of web proxy server significantly.

This paper proposes a dynamic partial replication protocol based upon group communication system for use with a web-enable database cluster. It dynamically combines the advantages of both a partial and a full replication model according to a query pattern. Most eager-update replication protocols that have been suggested as the best replication for a database cluster are based on the full replication. However, an actual database cluster system needs partial replication rather than full replication to achieve high throughputs and scalability. The proposed Dynamic partial Replication (DPR) protocol guarantees consistency among replicas and reduces the overhead due to remote access inherent in the previous partial replication protocols. The proposed protocol consists of three parts: partial replica control, scale-out factor estimation and dynamic replica allocation. Partial replica control part is the framework for the DPR protocol. Scale-out factor estimation part determines the optimal number of replicas according to the current query pattern and access frequency to maximize throughput and efficiency. Dynamic replica allocation part creates or removes the temporary replica in a local site. The simulated evaluation shows that the proposed protocol outperforms the existing eager-update protocols, achieving improvements of approximately 16% in response time and 20% in scalability.