Information2015, 6(2), 183-211; doi:10.3390/info6020183 - published 18 May 2015 Show/Hide Abstract
Abstract: The recent emergence of the targeted use of malware in cyber espionage versus industry requires a systematic review for better understanding of its impact and mechanism. This paper proposes a basic taxonomy to document major cyber espionage incidents, describing and comparing their impacts (geographic or political targets, origins and motivations) and their mechanisms (dropper, propagation, types of operating systems and infection rates). This taxonomy provides information on recent cyber espionage attacks that can aid in defense against cyber espionage by providing both scholars and experts a solid foundation of knowledge about the topic. The classification also provides a systematic way to document known and future attacks to facilitate research activities. Geopolitical and international relations researchers can focus on the impacts, and malware and security experts can focus on the mechanisms. We identify several dominant patterns (e.g., the prevalent use of remote access Trojan and social engineering). This article concludes that the research and professional community should collaborate to build an open data set to facilitate the geopolitical and/or technical analysis and synthesis of the role of malware in cyber espionage.
Information2015, 6(2), 162-182; doi:10.3390/info6020162 - published 4 May 2015 Show/Hide Abstract
Abstract: There is little knowledge regarding the exchange of academic information on religious contexts. The objective of this informational study was to perform an overall analysis of all Buddhism-related communications collected in the Web of Science (WoS) from 1993 to 2011. The studied informational parameters include the growth in number of the scholarly communications, as well as the language-, document-, subject category-, source-, country-, and organization-wise distribution of the communications. A total of 5407 scholarly communications in this field of study were published in the selected time range. The most preferred WoS subject category was Asian Studies with 1773 communications (22.81%), followed by Religion with 1425 communications (18.33%) and Philosophy with 680 communications (8.75%). The journal with the highest mean number of citations is Numen: International Review for the History of Religions—with 2.09 citations in average per communication. The United States was the top productive country with 2159 communications (50%), where Harvard University topped the list of organization with 85 communications (12%).
Information2015, 6(2), 152-161; doi:10.3390/info6020152 - published 24 April 2015 Show/Hide Abstract
Abstract: As a dominant method for face recognition, the subspace learning algorithm shows desirable performance. Manifold learning can deal with the nonlinearity hidden in the data, and can project high dimensional data onto low dimensional data while preserving manifold structure. Sparse representation shows its robustness for noises and is very practical for face recognition. In order to extract the facial features from face images effectively and robustly, in this paper, a method called graph regularized within-class sparsity preserving analysis (GRWSPA) is proposed, which can preserve the within-class sparse reconstructive relationship and enhances separatability for different classes. Specifically, for each sample, we use the samples in the same class (except itself) to represent it, and keep the reconstructive weight unchanged during projection. To preserve the manifold geometry structure of the original space, one adjacency graph is constructed to characterize the interclass separability and is incorporated into its criteria equation as a constraint in a supervised manner. As a result, the features extracted are sparse and discriminative and helpful for classification. Experiments are conducted on the two open face databases, the ORL and YALE face databases, and the results show that the proposed method can effectively and correctly find the key facial features from face images and can achieve better recognition rate compared with other existing ones.
Information2015, 6(2), 134-151; doi:10.3390/info6020134 - published 21 April 2015 Show/Hide Abstract
Abstract: Taxi GPS traces, which contain a great deal of valuable information as regards to human mobility and city traffic, can be extracted to improve the quality of our lives. Since the method of visualized analysis is believed to be an effective way to present information vividly, we develop our analysis and visualization method based on a city’s short-dated taxi GPS traces, which can provide recommendation to help cruising taxi drivers to find potential passengers with optimal routes. With our approach, hot spots for loading and unloading passenger(s) are extracted using an improved DBSCAN algorithm after data preprocessing including cleaning and filtering. Then, this paper describes the start-end point-based similar trajectory method to get coarse-level trajectories clusters, together with the density-based ε distance trajectory clustering algorithm to identify recommended potential routes. A weighted tree is defined including such factors as driving time, velocity, distance and endpoint attractiveness for optimal route evaluation from vacant to occupied hot spots. An example is presented to show the effectiveness of our visualization method.
Information2015, 6(2), 122-133; doi:10.3390/info6020122 - published 27 March 2015 Show/Hide Abstract
Abstract: Aiming at the common problems of intelligent document platform-dependency, this paper proposes an MVC-based (Model View Controller-based) intelligent document model using UIML (User Interface Markup Language). The model is made on the basis of the previous work of our team, and the difference is that the new model separates user interface and interaction descriptions from the view component to make the intelligent document model much more independent of platform and programming language. To verify the intelligent document model, we implemented a prototype, which can support intelligent operations. The test result shows that our approach is correct. The model not only follows MVC framework, but also provides good flexibility and independence.
Information2015, 6(2), 111-121; doi:10.3390/info6020111 - published 27 March 2015 Show/Hide Abstract
Abstract: Taking both OOXML and UOF standards as examples, we empirically evaluate the interoperability of office document formats from the view of translation practice. With the aim of covering the complete feature set of OOXML and UOF, a novel UOF-Open XML Translator is developed in this study. Thorough experiments demonstrate that our translator implements bidirectional conversion of 80.4% features perfectly and 9.9% features with acceptable discrepancy. Regarding the remaining 9.7% features, more efforts would be taken in future work.