Jongyoul Park

JavaCard-based Two-Level User Key Management for IP Conditional Access Systems

To prohibit the unauthorized accesses on premium contents of the Pay-TV system, a conditional access system (CAS) scrambles the contents with a scrambling key. In order to securely send the scrambling key for descrambling, the CAS transmits the scrambling key after encrypting it with another encryption key. The encryption keys are generally transmitted by entitlement management message (EMM). In this paper, we propose a two-level user key management scheme for the IP CAS used in the IPTV system. A user key for every subscriber is subdivided into permanent subscriber key (SK) and updatable user key (UK). The SK is used to obtain the UK by an authentication protocol. According to the authentication protocol, the authentication server requests the results of cryptographic operations to the authentication client to verify the authentication client. The UK is used to encrypt the next encryption key. The proposed scheme strengthens the security of the IP CAS because the use of the UK for the EMMs enables the lifetime of the SK to be infinite and the replacement of the smartcard to be eliminated. In addition, the IP CAS adopts Java card instead of Smart card because Java card applets are able to be dynamically reloaded.

Developing Ontology for Intelligent Home Service Framework

Home services are all kind of services which are provided in home environment. Legacy Researches was focused on controlling home devices and appliances. And recent works focus on the multimedia services. In the future, devices existing in the home would infer the status and intention of users and provide intelligent home services without much intervention of users. To do this, there must be context-aware technologies [1]. This research focused on the ontology which is the core technology of the context information management [2]. Through developing ontology for the home services, we classified services into several categories and, described requirements for the service execution. And then, we adopted the ontology for the intelligent home service framework called iHSF. Ontology designed for the home services consists of the concept of users, places (semantic locations), environment around the specific places, devices and individual services and subordinate concepts of them, which all concepts have properties and relations among them [2]. Ontology for the iHSF has form of RDF (resource description framework) [3, 4, 5] and OWL (web ontology language) [6, 7] in order to be interpreted by devices. Ontology should mirror the constantly varying environment of the home dynamically. iHSF using well-designed ontology reacts to the constantly varying .context on a real time basis.

A Dynamic Conditional Access System for IPTV Multimedia Systems

An IPTV system that transmits contents through anIP network needs to adopt a conditional access system allowingonly authorized subscribers to view premium content as inother Pay-TV systems. IPTV systems adopting one ofconditional access systems provided by a specific major vendorhave a difficulty in changing the conditional access systemloaded on a set-top box or on a removable hardware device,such as Smart card. However, a software download schemethrough an IP network enables an IPTV set-top box to changethe existing conditional access system in a secure way. Thispaper proposes a dynamic conditional access system for anIPTV set-top box that securely downloads cryptographicsoftware and dynamically executes the cryptographic softwarewhen it is required. Therefore, the proposed system enables anIPTV multimedia system to provide seamless conditionalaccess services to IPTV subscribers without rebooting theIPTV set-top box or replacing a hardware security devicewhile changing the running cryptographic software.

Achieving Interoperability in Conditional Access Systems through the Dynamic Download and Execution of Cryptographic Software for the IPTV System

An IPTV system that transmits multimedia contents through the IP network needs to adopt a conditional access system allowing the only entitled subscribers to view the premium content as other pay-TV systems do. Although several standard specifications have been published for interoperable models of conditional access systems, the proposed models are based on the unidirectional or restricted bidirectional broadcasting network and do not utilize the characteristics of the IP network. However, software download scheme through the bidirectional IP network enables it to change existing conditional access systems in a secure way. This paper introduces an interoperable conditional access system that can update any cryptographic software provided by different conditional access system vendors through downloading and executing dynamically the downloaded conditional access software only if the software follows the pre-defined interfaces.

A seamless remote user interface system supporting multi-screen services in smart devices

Many smart devices getting introduced to the market provide multimedia services and various interactive applications. Efficient collaboration among these devices helps improve user convenience, user mobility, and multi-screen services. In this paper, we propose an architecture for a seamless remote user interface system supporting multi-screen services in smart devices that guarantees smooth user interface transition through efficient collaboration.

Performance Monitoring for Multimedia Traffic using Differentiated Probe (DiffProbe)

Guaranteeing end-to-end QoS for multimedia traffic in the IP transport network is a challenging issue. Monitoring the one way delay of the multimedia traffic is necessary but no clear solution for the performance monitoring in the core network exists. In the previous work, we introduced an one-way delay monitoring mechanism called DiffProbe. We introduced the basic concept and the implementation details in the MPLS core network. In this paper, we provided an analytical model of the scheme and investigated the performance of the proposed delay measurement mechanism. We evaluate the accuracy of the delay measurement mechanism and the efficiency of the control mechanism with the simulation. The numerical result shows that our proposed algorithm captures the delay performance of the real traffic when the traffic load is high.

Hierarchically linked infinite hidden Markov model based trajectory analysis and semantic region retrieval in a trajectory dataset

A novel model for trajectories and semantic regions (sest-hiHMM) is proposed.A sticky version of sest-hiHMMs is proposed for reducing redundant semantic regions.An extended definition of semantic regions covers actual regions, not sets of points.Our models concern the temporal dependency of observations in a trajectory.Our models retrieve reasonable semantic regions from a real trajectory dataset. With an increasing attempt of finding latent semantics in a video dataset, trajectories have become key components since they intrinsically include concise characteristics of object movements. An approach to analyze a trajectory dataset has concentrated on semantic region retrieval, which extracts some regions in which have their own patterns of object movements. Semantic region retrieval has become an important topic since the semantic regions are useful for various applications, such as activity analysis. The previous literatures, however, have just revealed semantically relevant points, rather than actual regions, and have less consideration of temporal dependency of observations in a trajectory. In this paper, we propose a novel model for trajectory analysis and semantic region retrieval. We first extend the meaning of semantic regions that can cover actual regions. We build a model for the extended semantic regions based on a hierarchically linked infinite hidden Markov model, which can capture the temporal dependency between adjacent observations, and retrieve the semantic regions from a trajectory dataset. In addition, we propose a sticky extension to diminish redundant semantic regions that occur in a non-sticky model. The experimental results demonstrate that our models well extract semantic regions from a real trajectory dataset.

Adaptive Transformation for a Scalable User Interface Framework Supporting Multi-screen Services

Nowadays many smart devices getting introduced to the market have different performance and capabilities in terms of CPU, memory, screen size, screen resolution, and etc. In this paper, we propose an adaptive transformation for a scalable user interface (SUI) framework supporting multi-screen services which is capable of providing a uniform user experience irrespective of devices of varying size and capabilities. The proposed adaptive transformation dynamically adapts user interfaces to make it suitable for smart devices using transformation policy including layout, content, and appearance of user interfaces as well as device profiles regarding device capabilities.

Trajectory Segmentation Based on Spatio-Temporal Locality with Multidimensional Index Structures

Despite the remarkable growth of video analysis technologies, human operators still suffer from the difficulties of careful monitoring of a lot of videos in many industrial applications. Since a number of methods for understanding videos usually consider object movements, it is also concentrated on trajectory analysis. Due to the high and variable dimensionality of trajectories, trajectory analysis is not trivial. Some studies divided each trajectory into several pieces. However, the lack of discussions on how to segment concerning trajectory analysis led to flood too naive or too complicated methods. In this paper, we propose a simple but effective method of trajectory segmentation concerning spaito-temporal locality. Using multidimensional index structures and some temporal concerns, a great set of trajectory segments can be constructed in a short time. In addition, we extracted semantic regions, as an example of trajectory analysis, with the results of trajectory segmentation. The experiments showed that trajectory segments reflect on the spatio-temporal locality, and semantic regions were well extracted, which indicated that our segmentation had potential for trajectory analysis.

UnAMT: unsupervised adaptive matting tool for large-scale object collections

Unsupervised matting, whose goal is to extract interesting foreground components from arbitrary and natural background regions without any additional information of the contents of the corresponding scenes, plays an important role in many computer vision and graphics applications. Especially, the precisely extracted object images from the matting process can be useful for automatic generation of large-scale annotated training sets with more accuracy, as well as for improving the performance of a variety of applications including content-based image retrieval. However, unsupervised matting problem is intrinsically ill-posed so that it is hard to generate a perfect segmented object matte from a given image without any prior knowledge. This additional information is usually fed by means of a trimap which is a rough pre-segmented image consisting of three subregions of foreground, background and unknown. When such matting process is applied to object collections in a large-scale image set, the requirement for manually specifying every trimap for each of independent input images can be a serious drawback definitely. Recently, automatic detection of salient object regions in images has been widely researched in computer vision tasks including image segmentation, object recognition and so on. Although there are many different types of proposal measures in methodology under the common perceptual assumption of a salient region standing out its surrounding neighbors and capturing the attention of a human observer, most final saliency maps having lots of noises are not sufficient to take advantage of the consequent computational processes of highly accurate low-level representation of images.