2012-IEEE-Clustering with Multiviewpoint-Based Similarity Measure

Clustering with Multiviewpoint-Based Similarity Measure

Abstract

            All clustering methods have to assume some cluster relationship among the data objects that they are applied on. Similarity between a pair of objects can be defined either explicitly or implicitly. In this paper, we introduce a novel multiviewpoint-based similarity measure and two related clustering methods. The major difference between a traditional dissimilarity /similarity measure and ours is that the former uses only a single viewpoint, which is the origin, while the latter utilizes many different viewpoints, which are objects assumed to not be in the same cluster with the two objects being measured. Using multiple viewpoints, more informative assessment of similarity could be achieved. Theoretical analysis and empirical study are conducted to support this claim. Two criterion functions for document clustering are proposed based on this new measure. We compare them with several well-known clustering algorithms that use other popular similarity measures on various document collections to verify the advantages of our proposal.

2012-IEEE-Efficient Fuzzy Type-Ahead Search in XML Data

Efficient Fuzzy Type-Ahead Search in XML Data

Abstract

            In a traditional keyword-search system over XML data, a user composes a keyword query, submits it to the system, and retrieves relevant answers. In the case where the user has limited knowledge about the data, often the user feels "left in the dark" when issuing queries, and has to use a try-and-see approach for finding information. In this paper, we study fuzzy type-ahead search in XML data, a new information-access paradigm in which the system searches XML data on the fly as the user types in query keywords. It allows users to explore data as they type, even in the presence of minor errors of their keywords. Our proposed method has the following features: 1) Search as you type: It extends Auto complete by supporting queries with multiple keywords in XML data. 2) Fuzzy: It can find high-quality answers that have keywords matching query keywords approximately. 3) Efficient: Our effective index structures and searching algorithms can achieve a very high interactive speed. We study research challenges in this new search framework. We propose effective index structures and top-k algorithms to achieve a high interactive speed. We examine effective ranking functions and early termination techniques to progressively identify the top-k relevant answers. We have implemented our method on real data sets, and the experimental results show that our method achieves high search efficiency and result quality.

2012-IEEE-A Network Coding Equivalent Content Distribution Scheme for Efficient Peer-to-Peer Interactive VoD Streaming

A Network Coding Equivalent Content Distribution Scheme for Efficient Peer-to-Peer Interactive VoD Streaming

Abstract

            Although random access operations are desirable for on-demand video streaming in peer-to-peer systems, they are difficult to efficiently achieve due to the asynchronous interactive behaviors of users and the dynamic nature of peers. In this paper, we propose a network coding equivalent content distribution (NCECD) scheme to efficiently handle interactive video-on-demand (VoD) operations in peer-to-peer systems. In NCECD, videos are divided into segments that are then further divided into blocks. These blocks are encoded into independent blocks that are distributed to different peers for local storage. With NCECD, a new client only needs to connect to a sufficient number of parent peers to be able to view the whole video and rarely needs to find new parents when performing random access operations. In most existing methods, a new client must search for parent peers containing specific segments; however, NCECD uses the properties of network coding to cache equivalent content in peers, so that one can pick any parent without additional searches. Experimental results show that the proposed scheme achieves low startup and jump searching delays and requires fewer server resources. In addition, we present the analysis of system parameters to achieve reasonable block loss rates for the proposed scheme.

2012-IEEE-Distributed Packet Buffers for High-Bandwidth Switches and Routers

Distributed Packet Buffers for High-Bandwidth Switches and Routers

Abstract

            High-speed routers rely on well-designed packet buffers that support multiple queues, provide large capacity and short response times. Some researchers suggested combined SRAM/DRAM hierarchical buffer architectures to meet these challenges. However, these architectures suffer from either large SRAM requirement or high time-complexity in the memory management. In this paper, we present scalable, efficient, and novel distributed packet buffer architecture. Two fundamental issues need to be addressed to make this architecture feasible: 1) how to minimize the overhead of an individual packet buffer; and 2) how to design scalable packet buffers using independent buffer subsystems. We address these issues by first designing an efficient compact buffer that reduces the SRAM size requirement by (k - 1)/k. Then, we introduce a feasible way of coordinating multiple subsystems with a load-balancing algorithm that maximizes the overall system performance. Both theoretical analysis and experimental results demonstrate that our load-balancing algorithm and the distributed packet buffer architecture can easily scale to meet the buffering needs of high bandwidth links and satisfy the requirements of scale and support for multiple queues.

2012-IEEE-Efficient and Effective Duplicate Detection in Hierarchical Data

Efficient and Effective Duplicate Detection in Hierarchical Data

Abstract

            Although there is a long line of work on identifying duplicates in relational data, only a few solutions focus on duplicate detection in more complex hierarchical structures, like XML data. In this paper, we present a novel method for XML duplicate detection, called XMLDup. XMLDup uses a Bayesian network to determine the probability of two XML elements being duplicates, considering not only the information within the elements, but also the way that information is structured. In addition, to improve the efficiency of the network evaluation, a novel pruning strategy, capable of significant gains over the unoptimized version of the algorithm, is presented. Through experiments, we show that our algorithm is able to achieve high precision and recall scores in several datasets. XMLDup is also able to outperform another state of the art duplicate detection solution, both in terms of efficiency and of effectiveness. Finally, we also study how important the structure of elements is in the duplicate detection process. We observe that, not only structure can clearly influence the outcome, but also that, by ensuring a structure that is adequate to the characteristics of the data, we can actually improve the quality of the results.

2012-IEEE-Footprint: Detecting Sybil Attacks in Urban Vehicular Networks

Footprint: Detecting Sybil Attacks in Urban Vehicular Networks

Abstract

            In urban vehicular networks, where privacy, especially the location privacy of anonymous vehicles is highly concerned, anonymous verification of vehicles is indispensable. Consequently, an attacker who succeeds in forging multiple hostile identifies can easily launch a Sybil attack, gaining a disproportionately large influence. In this paper, we propose a novel Sybil attack detection mechanism, Footprint, using the trajectories of vehicles for identification while still preserving their location privacy. More specifically, when a vehicle approaches a road-side unit (RSU), it actively demands an authorized message from the RSU as the proof of the appearance time at this RSU. We design a location-hidden authorized message generation scheme for two objectives: first, RSU signatures on messages are signer ambiguous so that the RSU location information is concealed from the resulted authorized message; second, two authorized messages signed by the same RSU within the same given period of time (temporarily linkable) are recognizable so that they can be used for identification. With the temporal limitation on the likability of two authorized messages, authorized messages used for long-term identification are prohibited. With this scheme, vehicles can generate a location-hidden trajectory for location-privacy-preserved identification by collecting a consecutive series of authorized messages. Utilizing social relationship among trajectories according to the similarity definition of two trajectories, Footprint can recognize and therefore dismiss "communities" of Sybil trajectories. Rigorous security analysis and extensive trace-driven simulations demonstrate the efficacy of Footprint.

2012-IEEE-On Optimizing Overlay Topologies for Search in Unstructured Peer-to-Peer Networks

On Optimizing Overlay Topologies for Search in Unstructured Peer-to-Peer Networks

Abstract

            Unstructured peer-to-peer (P2P) file-sharing networks are popular in the mass market. As the peers participating in unstructured networks interconnect randomly, they rely on flooding query messages to discover objects of interest and thus introduce remarkable network traffic. Empirical measurement studies indicate that the peers in P2P networks have similar preferences, and have recently proposed unstructured P2P networks that organize participating peers by exploiting their similarity. The resultant networks may not perform searches efficiently and effectively because existing overlay topology construction algorithms often create unstructured P2P networks without performance guarantees. Thus, we propose a novel overlay formation algorithm for unstructured P2P networks. Based on the file sharing pattern exhibiting the power-law property, our proposal is unique in that it poses rigorous performance guarantees. Theoretical performance results conclude that in a constant probability, 1) searching an object in our proposed network efficiently takes hops (where c is a small constant), and 2) the search progressively and effectively exploits the similarity of peers. In addition, the success ratio of discovering an object approximates 100 percent. We validate our theoretical analysis and compare our proposal to competing algorithms in simulations. Based on the simulation results, our proposal clearly outperforms the competing algorithms in terms of 1) the hop count of routing a query message, 2) the successful ratio of resolving a query, 3) the number of messages required for resolving a query, and 4) the message overhead for maintaining and formatting the overlay.

2012-IEEE-Self Adaptive Contention Aware Routing Protocol for Intermittently Connected Mobile Networks

Self Adaptive Contention Aware Routing Protocol for Intermittently Connected Mobile Networks

Abstract

            This paper introduces a novel multi-copy routing protocol, called Self Adaptive Utility-based Routing Protocol (SAURP), for Delay Tolerant Networks (DTNs) that are possibly composed of a vast number of devices in miniature such as smart phones of heterogeneous capacities in terms of energy resources and buffer spaces. SAURP is characterized by the ability of identifying potential opportunities for forwarding messages to their destinations via a novel utility function based mechanism, in which a suite of environment parameters, such as wireless channel condition, nodal buffer occupancy, and encounter statistics, are jointly considered. Thus, SAURP can reroute messages around nodes experiencing high buffer occupancy, wireless interference, and/or congestion, while taking a considerably small number of transmissions. The developed utility function in SAURP is proved to be able to achieve optimal performance, which is further analyzed via a stochastic modeling approach. Extensive simulations are conducted to verify the developed analytical model and compare the proposed SAURP with a number of recently reported encounter-based routing approaches in terms of delivery ratio, delivery delay, and the number of transmissions required for each message delivery. The simulation results show that SAURP outperforms all the counterpart multi-copy encounter-based routing protocols considered in the study.

2012-IEEE-Cooperative Provable Data Possession for Integrity Verification in Multi-Cloud Storage (DOTNET)

Cooperative Provable Data Possession for Integrity Verification in Multi-Cloud Storage

Abstract

            Provable data possession (PDP) is a technique for ensuring the integrity of data in storage outsourcing. In this paper, we address the construction of an efficient PDP scheme for distributed cloud storage to support the scalability of service and data migration, in which we consider the existence of multiple cloud service providers to cooperatively store and maintain the clients' data. We present a cooperative PDP (CPDP) scheme based on homomorphic verifiable response and hash index hierarchy. We prove the security of our scheme based on multi-prover zero-knowledge proof system, which can satisfy completeness, knowledge soundness, and zero- knowledge properties. In addition, we articulate performance optimization mechanisms for our scheme, and in particular present an efficient method for selecting optimal parameter values to minimize the computation costs of clients and storage service providers. Our experiments show that our solution introduces lower computation and communication overheads in comparison with non-cooperative approaches.

2012-IEEE-Handwritten Chinese Text Recognition by Integrating Multiple Contexts

Handwritten Chinese Text Recognition by Integrating Multiple Contexts

Abstract

            This paper presents an effective approach for the offline recognition of unconstrained handwritten Chinese texts. Under the general integrated segmentation-and-recognition framework with character oversegmentation, we investigate three important issues: candidate path evaluation, path search, and parameter estimation. For path evaluation, we combine multiple contexts (character recognition scores, geometric and linguistic contexts) from the Bayesian decision view, and convert the classifier outputs to posterior probabilities via confidence transformation. In path search, we use a refined beam search algorithm to improve the search efficiency and, meanwhile, use a candidate character augmentation strategy to improve the recognition accuracy. The combining weights of the path evaluation function are optimized by supervised learning using a Maximum Character Accuracy criterion. We evaluated the recognition performance on a Chinese handwriting database CASIA-HWDB, which contains nearly four million character samples of 7,356 classes and 5,091 pages of unconstrained handwritten texts. The experimental results show that confidence transformation and combining multiple contexts improve the text line recognition performance significantly. On a test set of 1,015 handwritten pages, the proposed approach achieved character-level accurate rate of 90.75 percent and correct rate of 91.39 percent, which are superior by far to the best results reported in the literature.

2012-IEEE-Publishing Search Logs – A Comparative Study Of Privacy Guarantees

Publishing Search Logs – A Comparative Study

Of Privacy Guarantees

 

Abstract:

            Search engine companies collect the “database of intentions”, the histories of their users’ search queries. These search logs are a gold mine for researchers. Search engine companies, however, are wary of publishing search logs in order not to disclose sensitive information. In this paper we analyze algorithms for publishing frequent keywords, queries and clicks of a search log. We first show how methods that achieve variants of k-anonymity are vulnerable to active attacks. We then demonstrate that the stronger guarantee ensured by differential privacy unfortunately does not provide any utility for this problem. Our paper concludes with a large experimental study using real applications where we compare ZEALOUS and previous work that achieves k-anonymity in search log publishing. Our results show that ZEALOUS yields comparable utility to k−anonymity while at the same time achieving much stronger privacy guarantees.