18530879
Detection of Hidden Information in Webpages Based on Randomness
An effective detection algorithm based on the randomness is devised in this paper for stego-webpages with different steganographies. The parts where secret information embedded in a webpage can generally be represented as two states, which can be described in binary code string. The randomness of the states varies a great deal depending on the webpage part carrying secret information or not. This paper presents a procedure to transform the binary code string into octal string to capture the randomness, from which some statistical features have been discovered. The theoretical description and proof are given that these features can be employed as a criterion to test whether a webpage contains secret information or not. Experiments show that this algorithm can effectively detect the stego-webpages based on letter changing in tags and invisible characters embedding.
15413027
Research on Steganalysis for Text Steganography Based on Font Format
In the research area of text steganography, algorithms based on font format have advantages of great capacity, good imperceptibility and wide application range. However, little work on steganalysis for such algorithms has been reported in the literature. Based on the fact that the statistic features of font format will be changed after using font-format-based steganographic algorithms, we present a novel Support Vector Machine-based steganalysis algorithm to detect whether hidden information exists or not. This algorithm can not only effectively detect the existence of hidden information, but also estimate the hidden information length according to variations of font attribute value. As shown by experimental results, the detection accuracy of our algorithm reaches as high as 99.3% when the hidden information length is at least 16 bits.
235091
Efficient detection of empty-result queries
Frequently encountered in query processing, empty query results usually do not provide users with much useful information. Yet, users might still have to wait for a long time before they disappointingly realize that their results are empty. To significantly reduce such unfavorable delays, in this paper, we propose a novel method to quickly detect, without actual execution, those queries that will return empty results. Our key idea is to remember and reuse the results from previously-executed, empty-result queries. These results are stored in the form of so-called atomic query parts so that the (partial) results from multiple queries can be combined together to handle a new query without incurring much overhead. To increase our chance of detecting empty-result queries with only a limited storage, our method (1) stores the most "valuable" information about empty-result queries, (2) removes redundant information among different empty-result queries, (3) continuously updates the stored information to adapt to the current query pattern, and (4) utilizes a set of special properties of empty results. We evaluate the efficiency of our method through a theoretical analysis and an initial implementation in PostgreSQL. The results show that our method has low overhead and can often successfully avoid executing empty-result queries.
14222932
Design and Evaluation of the iMed Intelligent Medical Search Engine
Searching for medical information on the Web is popular and important. However, medical search has its own unique requirements that are poorly handled by existing medical Web search engines. This paper presents iMed, the first intelligent medical Web search engine that extensively uses medical knowledge and questionnaire to facilitate ordinary Internet users to search for medical information. iMed introduces and extends expert system technology into the search engine domain. It uses several key techniques to improve its usability and search result quality. First, since ordinary users often cannot clearly describe their situations due to lack of medical background, iMed uses a questionnaire-based query interface to guide searchers to provide the most important information about their situations. Second, iMed uses medical knowledge to automatically form multiple queries from a searcher' answers to the questions. Using these queries to perform search can significantly improve the quality of search results. Third, iMed structures all the search results into a multi-level hierarchy with explicitly marked medical meanings to facilitate searchers' viewing. Lastly, iMed suggests diversified, related medical phrases at each level of the search result hierarchy. These medical phrases are extracted from the MeSH ontology and can help searchers quickly digest search results and refine their inputs. We evaluated iMed under a wide range of medical scenarios. The results show that iMed is effective and efficient for medical search.
6675274
Software Testing Based on SDL Specifications with Save
The signal save construct is one of the features distinguishing SDL from traditional high-level specification and programming languages. However, this feature increases the difficulties of testing SDL-specified software. We present a testing approach consisting of the following three phases: SDL specifications are first abstracted into finite state machines with save constructs, called SDL-machines; the resulting SDL-machines are then transformed into equivalent finite state machines without save constructs if this is possible; and, finally, test cases are selected from the resulting finite state machines. Since there are many existing methods for the first and third phases, we mainly concentrate upon the second phase and come up with a method of transforming SDL-machines into equivalent finite state machines, which preserve the same input/output relationship as in the original SDL-machines. The transformation method is useful not only for testing but also for verifying SDL-specified software. >
6634048
Content-based filtering for efficient online materialized view maintenance
Real-time materialized view maintenance has become increasingly popular, especially in real-time data warehousing and data streaming environments. Upon updates to base relations, maintaining the corresponding materialized views can bring a heavy burden to the RDBMS. A traditional method to mitigate this problem is to use the where clause condition in the materialized view definition to detect whether an update to a base relation is relevant and can affect the materialized view. However, this detection method does not consider the content in the base relations and hence misses a large number of filtering opportunities. In this paper, we propose a content-based method for detecting irrelevant updates to base relations of a materialized view. At the cost of using more space, this method increases the probability of catching irrelevant updates by judiciously designing filtering relations to capture the content in the base relations. Based on the content-based method, a prototype real-time data warehouse has been implemented on top of IBM's System S using IBM DB2. Using an analytical model and our prototype, we show that the content-based method can catch most (or all) irrelevant updates to base relations that are missed by the traditional method. Thus, when the fraction of irrelevant updates is non-negligible, the load on the RDBMS due to materialized view maintenance can be significantly reduced.
53228070
Transaction reordering with application to synchronized scans
Traditional workload management methods mainly focus on the current system status while information about the interaction between queued and running transactions is largely ignored. An exception to this is the transaction reordering method, which reorders the transaction sequence submitted to the RDBMS and improves the transaction throughput by considering both the current system status and information about the interaction between queued and running transactions. The existing transaction reordering method only considers the reordering opportunities provided by analyzing the lock conflict information among multiple transactions. This significantly limits the applicability of the transaction reordering method. In this paper, we extend the existing transaction reordering method into a general transaction reordering framework that can incorporate various factors as the reordering criteria. We show that by analyzing the resource utilization information of transactions, the transaction reordering method can also improve the system throughput by increasing the resource sharing opportunities among multiple transactions. We provide a concrete example on synchronized scans and demonstrate the advantages of our method through experiments with a commercial parallel RDBMS.