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Web page malicious code detection based on embedded fingerprints

Qinghua Daxue Xuebao/Journal of Tsinghua University 2009年第SUPPL. 2期49卷 2208-2214页

作者： Huang, Jianjun Liang, Bin Key Laboratory of Data Engineering and Knowledge Engineering of Ministry of Education School of Information Renmin University of China Beijing 100872 China

Web sites have become the main targets of many attackers. Signature-based detection needs to maintain a large signature database and Honeypot based methods are not efficient. Since attackers always make the malicious codes in Web pages difficult to detect by the browser users, their methods can be classified into various fingerprints. Various malicious codes were analyzed to identify 6 types of fingerprints. The system utilizes a spider integrated with script interpretation to fetch target Web pages and extract specific tags for detection by HTML parsing for matching with the fingerprints to detect malicious codes. This method needs fewer fingerprints than traditional detection methods and is more efficient. Results for 60 websites show that the system has a false negative rate of 2.63% and a false positive rate of 1.99%.

关键词： Websites

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Bring User Feedback into keyword Search over databases

Bring User Feedback into Keyword Search over Databases

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Web information Systems and Applications Conference (WISA)

作者： Zhaohui Peng Jun Zhang Shan Wang Changliang Wang School of Computer Science & Technology Shandong University Jinan China Key Laboratory of Data Engineering & Knowledge Engineering Ministry of Education Beijing China School of Computer Science & Technology Dalian Maritime University Dalian China Hong Kong University of Science and Technology Hong Kong China

keyword search over relational databases (KSORD) enables casual users to use keyword queries (a set of keywords) to search relational databases just like searching the Web, without any knowledge of the database schema or any need of writing SQL queries. In KSORD, retrieval of user's initial query is often unsatisfying. User has to reformulate his query and execute the new query, which costs much time and effort. A method of automatically reformulating user queries by user feedback aimed at the results of KSORD is introduced in this paper, which is named UFBP (user feedback based on probability). After the first time of retrieval, according to the users' feedback information, UFBP computes terms to be added into the expanded query based on probability and reformulates the new query using query expansion. After KSORD executing the new query automatically, more relevant results are presented to user. Experimental results verify its effectiveness.

关键词： Feedback keyword search Relational databases Tree graphs information retrieval computer science Educational technology Writing information systems Application software

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ARRAY: A Non-application-Related, Secure, Wide-Area Disaster Recovery Storage System

ARRAY: A Non-application-Related, Secure, Wide-Area Disaster...

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International Symposium on Parallel and Distributed Processing with Applications, ISPA

作者： Lingfang Zeng Dan Feng Bharadwaj Veeravalli Qingsong Wei Division of Data Storage System Wuhan National Laboratory for Optoelectronics Key Laboratory of Information Storage Ministry of Education School of Computer Science and Technology Huazhong University of Science and Technology Wuhan China Department of Electrical and Computer Engineering National University of Singapore Singapore Data Storage Institute Singapore

With our society more information-driven, we have begun to distribute data in wide-area storage systems. At the same time, both physical failure and logic error have made it difficult to bring the necessary recovery to bear on remote data disaster, and understanding this proceeding. We describe ARRAY, a system architecture for data disaster recovery that combines reliability, storage space, and security to improve performance for data recovery applications. The paper presents an exhaustive analysis of the design space of ARRAY systems, focusing on the trade-offs between reliability, storage space, security, and performance that ARRAY must make. We present RSRAII (Replication-based Snapshot Redundant Array of Independent Imagefiles) which is a configurable RAID-like data erasure-coding, and also others benefits come from consolidation both erasure-coding and replication strategies. A novel algorithm is proposed to improve snapshot performance referred to as SMPDP (Snapshot based on Multi-Parallel Degree Pipeline).

关键词： Secure storage Network servers Bandwidth Redundancy data security Cities and towns Laboratories Educational technology Hardware History

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Using IACO and QPSO to solve spatial clustering with obstacles constraints

Using IACO and QPSO to solve spatial clustering with obstacl...

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IEEE International Conference on Automation and Logistics

作者： Xueping Zhang Hongmei Zhang Yanxia Zhu Yawei Liu Tengfei Yang Taogai Zhang Key Laboratory of Spatial Data Mining & Information Sharing of Ministry of Education Fuzhou University Fuzhou China School of Computer Science & Engineering Henan University of Technology Zhengzhou Henan China Department of Computer Science & Engineering Henan University of Engineering Zhengzhou China

ISBN: (纸本)9781424447947

Spatial clustering has been an active research area in the data mining community. Spatial clustering is not only an important effective method but also a prelude of other task for spatial data mining (SDM). In this paper, we propose an improved ant colony optimization (IACO) and quantum particle swarm optimization (QPSO) method for spatial clustering with obstacles constraints (SCOC). In the process of doing so, we first use IACO to obtain the shortest obstructed distance, and then we develop a novel QPKSCOC based on QPSO and K-Medoids to cluster spatial data with obstacles. The experimental results demonstrate that the proposed method, performs better than Improved K-Medoids SCOC in terms of quantization error and has higher constringency speed than Genetic K-Medoids SCOC.

关键词： Ant colony optimization data mining Particle swarm optimization computer science Quantization Genetics Clustering algorithms Automation Logistics data engineering

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PEJA:Progressive Energy-Efficient Join Processing for Sensor Networks

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Journal of computer Science & Technology 2008年第6期23卷 957-972页

作者：赖永炫陈毅隆陈红 School of Information Renmin University of China Key Laboratory of Data Engineering and Knowledge Engineering Ministry of Education

Sensor networks are widely used in many applications to collaboratively collect information from the physical environment. In these applications, the exploration of the relationship and linkage of sensing data within multiple regions can be naturally expressed by joining tuples in these regions. However, the highly distributed and resource-constraint nature of the network makes join a challenging query. In this paper, we address the problem of processing join query among different regions progressively and energy-efficiently in sensor networks. The proposed algorithm PEJA （Progressive Energy-efficient Join Algorithm） adopts an event-driven strategy to output the joining results as soon as possible, and alleviates the storage shortage problem in the in-network nodes. It also installs filters in the joining regions to prune unmatchable tuples in the early processing phase, saving lots of unnecessary transmissions. Extensive experiments on both synthetic and real world data sets indicate that the PEJA scheme outperforms other join algorithms, and it is effective in reducing the number of transmissions and the delay of query results during the join processing.

关键词： progressive join minimal join set in-network processing sensor network

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Static vulnerabilities detection method based on security state tracing and checking

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Jisuanji Xuebao/Chinese Journal of computers 2009年第5期32卷 899-909页

作者： Liang, Bin Hou, Kan-Kan Shi, Wen-Chang Liang, Zhao-Hui School of Information Renming University of China Beijing 100872 China MOE Key Laboratory of Data Engineering and Knowledge Engineering Beijing 100872 China

The main problem of existing static vulnerability detection methods based source code analysis is their high false positive and false negative rates. One main reason is lack of accurate and effective identification and analysis of security-related program elements, e.g. data validation checking, tainted data source, etc. A static vulnerability detection method based on data security state tracing and checking is proposed. In this method, the state space of state machine model is extended;the security state of a variable is identified by a vector that may correspond to multiple security-related properties rather than by a single property;Fine-grained state transition is provided to support accurate recognition of program security-related behaviors;The recognition of validation checking is introduced in vulnerability state machine to reduce false positives;and a systematic discrimination mechanism for tainted data is constructed to prevent false negatives result from neglecting tainted data sources. The experimental results of a prototype system show that this method can effectively detect buffer overflow and other type's vulnerabilities in software systems, and with obviously lower false positive than existing mainstream static detection methods and avoid some serious false negatives of these methods.

关键词： Static analysis

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A new dynamic hash index for flash-based storage

A new dynamic hash index for flash-based storage

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9th International Conference on Web-Age information Management, WAIM 2008

作者： Xiang, Li Zhou, Da Meng, Xiaofeng School of Information Renmin University of China Key Laboratory of Data Engineering and Knowledge Engineering MOE

ISBN: (纸本)9780769531854

Compared with traditional magnetic disks, Flash memory has many advantages and has been used as external storage media for a wide spectrum of electronic devices (such as PDA, MP3, Digital Camera and Mobile Phone) in recent years. As the capacity increases and price drops, it looks like a perfect alternative for magnetic disks. However, due to hardware limitations of flash memory, techniques including storage subsystem and indexing originally designed for magnetic disks can not run smoothly in a flash memory without any modification. In this paper we explore problems of indexing flash-resided data and present a new dynamical hash index for flash memory in two schemas. The analysis and experimental results validate the efficiency of our design. © 2008 IEEE.

关键词： Flash memory

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Moment+: Mining closed frequent itemsets over data stream

Moment+: Mining closed frequent itemsets over data stream

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4th International Conference on Advanced data Mining and Applications, ADMA 2008

作者： Li, Haifeng Chen, Hong Key Laboratory of Data Engineering and Knowledge Engineering School of Information Renmin University of China Beijing 100872 China

ISBN: (纸本)3540881913

Closed frequent itemsets(CFI) mining uses less memory to store the entire information of frequent itemsets thus is much suitable for mining stream. In this paper, we discuss recent CFI mining methods over stream and presents an improved algorithm Moment+ based on the existent one Moment. Moment+ focuses on the problem of mining CFI over data stream sliding window and proposes a new structure Extended Closed Enumeration Tree(ECET) to store the CFIs and nodes' BPN which is introduced to reduce the search space, with which new mining method is designed to mine more rapidly with little memory cost sacrifice. The experimental results show that this method is effective and efficient. © 2008 Springer-Verlag Berlin Heidelberg.

关键词： Mining

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Evolving sequential patterns mining model over click stream with Levenshtein-Automata

Evolving sequential patterns mining model over click stream ...

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3rd International Conference on Innovative Computing information and Control, ICICIC'08

作者： Li, Haifeng Chen, Hong Key Laboratory of Data Engineering and Knowledge Engineering School of Information Renmin University of China Beijing 100872 China

ISBN: (纸本)9780769531618

Sequential pattern mining is an important problem in continuous, fast, dynamic and unlimited stream mining. Recently approximate mining algorithms are proposed which spend too many system resources and can only obtain the partial feature of stream. In this paper, a multi-level evolving sequential pattern mining model ESPMM is presented to address this problem thus the mostly entire stream feature is obtained. Furthermore, because of the smaller support of sequential patterns in each level, a mining method BMLA based on Levenshtein-Automata is proposed which builds state conversion model to compute sequences' similarity in linear time. The experiment results show this model is effective and efficient. © 2008 IEEE.

关键词： Automata theory

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LOB: Bucket based index for range queries

LOB: Bucket based index for range queries

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9th International Conference on Web-Age information Management, WAIM 2008

作者： Wang, Jieping Du, Xiaoyong Key Laboratory of Data Engineering and Knowledge Engineering MOE Beijing 100872 China School of Information Renmin University of China Beijing 100872 China

ISBN: (纸本)9780769531854

database-as-a-Service is a promising data management paradigm in which data is encrypted before being sent to the untrusted server. Efficient querying on encrypted data is a performance critical problem which has various solutions, among which bucket based index is an effective and flexible one. In previous research some metrics are proposed to measure security and efficiency. In this paper, we illustrate by example the limitations of these metrics and introduce a new security metric based on probability distribution variance and efficiency metric based on overlapping ratio. Based on these metrics we propose a local overlapping bucket algorithm (LOB) with time complexity of O(nlogn), where n represents the cardinality of the table. Experiments on synthetic and real dataset show that our algorithm can achieve higher security by trading off efficiency. © 2008 IEEE.

关键词： information management

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