7043785
A new family of authentication protocols
We present a related family of authentication and digital signature protocols based on symmetric cryptographic primitives which perform substantially better than previous constructions. Previously, one-time digital signatures based on hash functions involved hundreds of hash function computations for each signature; we show that given online access to a timestamping service, we can sign messages using only two computations of a hash function. Previously, techniques to sign infinite streams involved one such one-time signature for each message block; we show that in many realistic scenarios a small number of hash function computations is sufficient. Previously, the Diffie Hellman protocol enabled two principals to create a confidentiality key from scratch: we provide an equivalent protocol for integrity, which enables two people who do not share a secret to set up a securely serialised channel into which attackers cannot subsequently intrude. In addition to being of potential use in real applications, our constructions also raise interesting questions about the definition of a digital signature, and the relationship between integrity and authenticity.
223678
Automatic classification of digestive organs in wireless capsule endoscopy videos
Wireless Capsule Endoscopy (WCE) allows a physician to examine the entire small intestine without any surgical operation. With the miniaturization of wireless and camera technologies the ability comes to view the entire gestational track with little effort. Although WCE is a technical break-through that allows us to access the entire intestine without surgery, it is reported that a medical clinician spends one or two hours to assess a WCE video, It limits the number of examinations possible, and incur considerable amount of costs. To reduce the assessment time, it is critical to develop a technique to automatically discriminate digestive organs such as esophagus, stomach, small intestinal (i.e., duodenum, jejunum, and ileum) and colon. In this paper, we propose a novel technique to segment a WCE video into these anatomic parts based on color change pattern analysis. The basic idea is that the each digestive organ has different patterns of intestinal contractions that are quantified as the features. We present the experimental results that demonstrate the effectiveness of the proposed method.
17811625
A Graph-Based Approach for Modeling and Indexing Video Data
In this work, we propose new graph-based data model and indexing to organize and manage video data. To consider spatial and temporal characteristics of video, we introduce a new graph-based data model called spatio-temporal region graph (STRG). Unlike existing graph-based data structures which provide only spatial features, the proposed STRG further provides temporal features, which represent temporal relationships among spatial objects. The STRG is decomposed into its subgraphs object graphs (OGs) and background graphs (BGs). In addition, a new distance measure, called extended graph edit distance (EGED), is introduced in metric space for matching and indexing. Based on clustering and EGED, we propose a new indexing method STRG-index, which is faster and more accurate. We compare the STRG-Index with the M-tree, which is a popular tree-based indexing method for multimedia data. The STRG-index outperforms the M-tree in terms of cost and speed
13494624
Security policies
A security policy is a high-level specification of the security properties that a given system should possess. It is a means for designers, domain experts and implementers to communicate with each other, and a blueprint that drives a project from design through implementation and validation. We offer a survey of the most significant security policy models in the literature, showing how “security” may mean very different things in different contexts, and we review some of the mechanisms typically used to implement a given security policy.
12522566
Real Time Video Data Mining for Surveillance Video Streams
We extend our previous work [1] of the general framework for video data mining to further address the issue such as how to mine video data using motions in video streams. To extract and characterize these motions, we use an accumulation of quantized pixel differences among all frames in a video segment. As a result, the accumulated motions of segment are represented as a two dimensional matrix. Further, we develop how to capture the location of motions occurring in a segment using the same matrix generated for the calculation of the amount. We study how to cluster those segmented pieces using the features (the amount and the location of motions) we extract by the matrix above. We investigate an algorithm to find whether a segment has normal or abnormal events by clustering and modeling normal events, which occur mostly. In addition to deciding normal or abnormal, the algorithm computes Degree of Abnormality of a segment, which represents to what extent a segment is distant to the existing segments in relation with normal events. Our experimental studies indicate that the proposed techniques are promising.
11550445
Multimedia Data Mining Framework for Raw Video Sequences
In this paper, we propose a general framework for real time video data mining to be applied to the raw videos (traffic videos, surveillance videos, etc.). We investigate whether the existing techniques would be applicable to this type of videos. Then, we introduce new techniques which are essential to process them in real time. The first step of our frame work for mining raw video data is grouping input frames to a set of basic units which are relevant to the structure of the video. We call this unit as segment. This is one of the most important tasks since it is the step to construct the building blocks for video database and video data mining. The second step is characterizing each segment to cluster into similar groups, to discover unknown knowledge, and to detect interesting patterns. To do this, we extract some features (motion, object, colors, etc.) from each segment. In our framework, we focus on motion as a feature, and study how to compute and represent it for further processes. The third step of our framework is to cluster the decomposed segments into similar groups. In our clustering, we employ a multi-level hierarchical clustering approach to group segments using category and motion. Our preliminary experimental studies indicate that the proposed framework is promising.
17910425
TMO-structured distributed location information system prototype
To realize location-based services, it is essential to handle the extreme situation that must cope with a very large volume, at least millions, of moving items. In this paper, we describe a location information system prototype of GALIS, which is a cluster-based scalable distributed computing system architecture which consists of multiple data processors, each dedicated to keeping records relevant to a different geographical zone and a different time zone. The proposed system contains all of the major computing nodes of GALIS architecture and is developed as a middleware on top of commercial main-memory database engines and spatial database engines, for short-term data and long-term data processing, respectively. To show the usefulness of our system, some experimental results showing clear advantages of distributed computing are also explained.
13302890
An Efficient and Scalable Management of Ontology
OWL is a recommended language for publishing and sharing ontologies on the Semantic Web. To manage the ontologies, several OWL data management systems have been proposed. However, the existing systems have limitations of the scalability and the reasoning. In this paper, we propose an OWL data management system, ONTOMS, which stores OWL data into class based relations, performs complete inverseOf, symmetric, and transitive reasoning for instances, and efficiently evaluates OWL-QL queries against ontologies in a relational database.
358063
Basic compiler algorithms for parallel programs
Traditional compiler techniques developed for sequential programs do not guarantee the correctness (sequential consistency) of compiler transformations when applied to parallel programs. This is because traditional compilers for sequential programs do not account for the updates to a shared variable by different threads. We present a concurrent static single assignment (CSSA) form for parallel programs containing cobegin/coend and parallel do constructs and post/wait synchronization primitives. Based on the CSSA form, we present copy propagation and dead code elimination techniques. Also, a global value numbering technique that detects equivalent variables in parallel programs is presented. By using global value numbering and the CSSA form, we extend classical common subexpression elimination, redundant load/store elimination, and loop invariant detection to parallel programs without violating sequential consistency. These optimization techniques are the most commonly used techniques for sequential programs. By extending these techniques to parallel programs, we can guarantee the correctness of the optimized program and maintain single processor performance in a multiprocessor environment.
28256456
Double Optimization for Design of Protein Energy Function
We propose an automated protocol for designing the energy landscape suitable for the description of a given set of protein sequences with known structures, by optimizing the parameters of the energy function. The parameters are optimized so that not only the global minimum-energy conformation becomes native-like, but also the conformations distinct from the native structure have higher energies than those close to the native one, for each protein sequence in the set. In order to achieve this goal, one has to sample protein conformations that are local minima of the energy function for given parameters. Then the parameters are optimized using linear approximation, and then local minimum conformations are searched with the new energy parameters. We develop an algorithm that repeats this process of parameter optimization based on linear approximation, and conformational optimization for the current parameters, ultimately leading to the optimization of the energy parameters. We test the feasibility of this algorithm by optimizing a coarse grained energy function, called the UNRES energy function, for a set of ten proteins.
2077132
Continuous query processing in data streams using duality of data and queries
Recent data stream systems such as TelegraphCQ have employed the well-known property of duality between data and queries. In these systems, query processing methods are classified into two dual categories -- data-initiative and query-initiative -- depending on whether query processing is initiated by selecting a data element or a query. Although the duality property has been widely recognized, previous data stream systems do not fully take advantages of this property since they use the two dual methods independently: data-initiative methods only for continuous queries and query-initiative methods only for ad-hoc queries. We contend that continuous query processing can be better optimized by adopting an approach that integrates the two dual methods. Our primary contribution is based on the observation that spatial join is a powerful tool for achieving this objective. In this paper, we first present a new viewpoint of transforming the continuous query processing problem to a multi-dimensional spatial join problem. We then present a continuous query processing algorithm based on spatial join, which we name Spatial Join CQ. This algorithm processes continuous queries by finding the pairs of overlapping regions from a set of data elements and a set of queries, both defined as regions in the multi-dimensional space. The algorithm achieves the advantages of the two dual methods simultaneously. Experimental results show that the proposed algorithm outperforms earlier algorithms by up to 36 times for simple selection continuous queries and by up to 7 times for sliding window join queries.