Journal articles: 'Visualization Computer security'

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Ma, Kwan-Liu. "Visualization for security." ACM SIGGRAPH Computer Graphics 38, no. 4 (November 2004): 4–6. http://dx.doi.org/10.1145/1039140.1039146.

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Yuan, Xiaohong, Percy Vega, Yaseen Qadah, Ricky Archer, Huiming Yu, and Jinsheng Xu. "Visualization Tools for Teaching Computer Security." ACM Transactions on Computing Education 9, no. 4 (January 2010): 1–28. http://dx.doi.org/10.1145/1656255.1656258.

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Zhang, Yanping, Yang Xiao, Min Chen, Jingyuan Zhang, and Hongmei Deng. "A survey of security visualization for computer network logs." Security and Communication Networks 5, no. 4 (May 11, 2011): 404–21. http://dx.doi.org/10.1002/sec.324.

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Barrera, David, and Paul C. van Oorschot. "Accommodating IPv6 Addresses in Security Visualization Tools." Information Visualization 10, no. 2 (November 11, 2010): 107–16. http://dx.doi.org/10.1057/ivs.2010.9.

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Visualization is used by security analysts to help detect patterns and trends in large volumes of network traffic data. With IPv6 slowly being deployed around the world, network intruders are beginning to adapt their tools and techniques to work over IPv6 (versus IPv4). Many tools for visualizing network activity, while useful for detecting large-scale attacks and network behavior anomalies, still only support IPv4. In this article, we explore the current state of IPv6 support in some popular security visualization tools and identify the roadblocks preventing those tools from supporting the new protocol. We propose a filtering technique that helps reduce the occlusion of IPv6 sources on graphs and enables IPv4 visualization tools to display both IPv4 and IPv6 sources on a single graph. We also suggest using treemaps for visually representing the vast space of remote addresses in IPv6.

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Lobachev, Oleg. "Direct visualization of cryptographic keys for enhanced security." Visual Computer 34, no. 12 (December 27, 2017): 1749–59. http://dx.doi.org/10.1007/s00371-017-1466-6.

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Conti, G., K. Abdullah, J. Grizzard, J. Stasko, J. A. Copeland, M. Ahamad, H. L. Owen, and C. Lee. "Countering security information overload through alert and packet visualization." IEEE Computer Graphics and Applications 26, no. 2 (March 2006): 60–70. http://dx.doi.org/10.1109/mcg.2006.30.

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Tri Dang, Tran, and Tran Khanh Dang. "Visualization of web form submissions for security analysis." International Journal of Web Information Systems 9, no. 2 (June 14, 2013): 165–80. http://dx.doi.org/10.1108/ijwis-12-2012-0036.

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Goodall, John R. "An Evaluation of Visual and Textual Network Analysis Tools." Information Visualization 10, no. 2 (April 2011): 145–57. http://dx.doi.org/10.1057/ivs.2011.2.

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User testing is an integral component of user-centered design, but has only rarely been applied to visualization for cyber security applications. This article presents the results of a comparative evaluation between a visualization-based application and a more traditional, table-based application for analyzing computer network packet captures. We conducted this evaluation as part of the user-centered design process. Participants performed both structured, well-defined tasks and exploratory, open-ended tasks with both tools. We measured accuracy and efficiency for the well-defined tasks, number of insights was measured for exploratory tasks and user perceptions were recorded for each tool. The results of this evaluation demonstrated that users performed significantly more accurately in the well-defined tasks, discovered a higher number of insights and demonstrated a clear preference for the visualization tool. The study design presented may be useful for future researchers performing user testing on visualization for cyber security applications.

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Jin Liu, Jing Sun, Zheng Q. Xu, and Lu Gao. "Security Web Release and Visualization of Remote Sensing Images." International Journal of Digital Content Technology and its Applications 4, no. 3 (June 30, 2010): 146–53. http://dx.doi.org/10.4156/jdcta.vol4.issue3.15.

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Novikova, Evgenia Sergeevna, and Igor Vitalievich Kotenko. "Analysis of the Visualization Techniques used for Information Security in the Computer Networks." SPIIRAS Proceedings 4, no. 23 (March 17, 2014): 7. http://dx.doi.org/10.15622/sp.23.1.

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Khanh Dang, Tran, and Tran Tri Dang. "A survey on security visualization techniques for web information systems." International Journal of Web Information Systems 9, no. 1 (March 29, 2013): 6–31. http://dx.doi.org/10.1108/17440081311316361.

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Xu, Ya Ning. "Research on Process Control of Human Resource Management Based on Visualization Technology." Applied Mechanics and Materials 687-691 (November 2014): 2258–62. http://dx.doi.org/10.4028/www.scientific.net/amm.687-691.2258.

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With the development of computer and multimedia technology, social media platforms are widely used in various fields, so this paper introduces the design of network multimedia platform in the human resources management system, and designs a kind of new human resources management computer system. In order to improve the level of human resource management, it can introduce more talents and rational allocation human resources for enterprises, so we must improve the user generated content quality of social networking platform, eliminating spam behavior, and improving the social network human resource platform reputation. This paper establishes the security mechanism related mathematical model of social network human resources system. Through the VB programming control, it can implement the security of social network content, the automatic removal of rubbish short message and the optimal audit mechanism of system human resource management, which provide innovative solutions for the enterprise human resource management.

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Одиноков, С. Б., В. В. Колючкин, Д. В. Кузьмин, В. Е. Талалаев, П. А. Ханевич, А. В. Смирнов, and Л. И. Смирнов. "Метод персонализации фотополимерных защитных голограмм на основе записи скрытых кодированных цифровых изображений." Оптика и спектроскопия 129, no. 4 (2021): 393. http://dx.doi.org/10.21883/os.2021.04.50765.299-20.

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This article deals with the problem of embedding personal data into replicated photopolymer security holograms with a maximal preservation of the hologram area during its visualization. A method of recording personalized security holograms on a photopolymer material is proposed. By this method main security hologram with a visualized image includes an additional computer-generated Fourier microhologram with individual personalized data. The synthesis algorithm and a technical implementation of the Fourier microhologram recording method are presented. The efficiency of the proposed method is confirmed by experimental studies on recording and reading of personalizing Fourier microholograms.

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Yu, Xiaoying, and Qi Liao. "User password repetitive patterns analysis and visualization." Information & Computer Security 24, no. 1 (March 14, 2016): 93–115. http://dx.doi.org/10.1108/ics-06-2015-0026.

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Purpose – Passwords have been designed to protect individual privacy and security and widely used in almost every area of our life. The strength of passwords is therefore critical to the security of our systems. However, due to the explosion of user accounts and increasing complexity of password rules, users are struggling to find ways to make up sufficiently secure yet easy-to-remember passwords. This paper aims to investigate whether there are repetitive patterns when users choose passwords and how such behaviors may affect us to rethink password security policy. Design/methodology/approach – The authors develop a model to formalize the password repetitive problem and design efficient algorithms to analyze the repeat patterns. To help security practitioners to analyze patterns, the authors design and implement a lightweight, Web-based visualization tool for interactive exploration of password data. Findings – Through case studies on a real-world leaked password data set, the authors demonstrate how the tool can be used to identify various interesting patterns, e.g. shorter substrings of the same type used to make up longer strings, which are then repeated to make up the final passwords, suggesting that the length requirement of password policy does not necessarily increase security. Originality/value – The contributions of this study are two-fold. First, the authors formalize the problem of password repetitive patterns by considering both short and long substrings and in both directions, which have not yet been considered in past. Efficient algorithms are developed and implemented that can analyze various repeat patterns quickly even in large data set. Second, the authors design and implement four novel visualization views that are particularly useful for exploration of password repeat patterns, i.e. the character frequency charts view, the short repeat heatmap view, the long repeat parallel coordinates view and the repeat word cloud view.

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Sonmez, Ferda Ozdemir, and Banu Gunel Kilic. "Holistic Web Application Security Visualization for Multi-Project and Multi-Phase Dynamic Application Security Test Results." IEEE Access 9 (2021): 25858–84. http://dx.doi.org/10.1109/access.2021.3057044.

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Chang, Juan, Jian Hua Zhang, Dian Ji Zhang, and Zhi Gang Liu. "Research on Computer Information System of Disaster Warning Based on ANSYS and MATLAB." Applied Mechanics and Materials 484-485 (January 2014): 958–62. http://dx.doi.org/10.4028/www.scientific.net/amm.484-485.958.

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In this paper, we use the software of ANSYS and MATLAB to do research on early computer warning system. ANSYS can check the intensity of early warning system, and MATLAB can realize the visual function of warning system. In this paper we established the process model of ANSYS intensity checking, and designed the calculation process of order flow. We use the disaster warning when opencast mining to underground mining as an example to verify the model and the algorithm. Through the calculation we get the correlation table between calculated and measured value. Finally we get the biggest stress nephogram of chamber center by using ANSYS software, and through the MATLAB software we realized visualization of surrounding rock stress. It provides the theoretical reference for the research on computer warning system in mining process. With the development of computer hardware and software technology, computer information early warning system begins to appear in many engineering fields. This system can carry on security issues of real-time detection and warning in the process of project implementation, and through the visualization software to display this information.

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Bai, Bing, Xue Jun Chen, En Qiang Zhu, Wan Xiao Xue, and Jie Yu. "Digital Urban Three-Dimensional Technique Base on OpenGL." Advanced Materials Research 726-731 (August 2013): 4568–71. http://dx.doi.org/10.4028/www.scientific.net/amr.726-731.4568.

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With the fast development of computer multimedia technology, space technology, visualization technology, digital geomatics technology and computer graphics technology, using three-dimensional GIS technology to realize virtual visualization scene become reality. Three-dimensional GIS had already been applied to a lot of fields, such as country resource management, urban planning, public security system, electric power telecom branch. The paper had paid great attention to the popular three-dimensional GIS technology which had been in progress studying nowadays. It has summarized the research content and developed condition of current three-dimensional GIS and expatiates on the comprehensive application foreground of three-dimensional GIS. It had discussed and studied the three-dimensional GIS modeling method and the key visualization technology which based on OpenGL. It designed and realized a three-dimensional GIS simulation system. The paper had done the main studies as follows: (1) 3D GIS modeling theory and method had been discussed in this paper, and the paper had realized 3D modeling based on 3dsmax become reality; (2) It had designed and realized a three-dimensional GIS simulation system based on visualization technology which based on OpenGL.

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Jang, Sejun, Shuyu Li, and Yunsick Sung. "FastText-Based Local Feature Visualization Algorithm for Merged Image-Based Malware Classification Framework for Cyber Security and Cyber Defense." Mathematics 8, no. 3 (March 24, 2020): 460. http://dx.doi.org/10.3390/math8030460.

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The importance of cybersecurity has recently been increasing. A malware coder writes malware into normal executable files. A computer is more likely to be infected by malware when users have easy access to various executables. Malware is considered as the starting point for cyber-attacks; thus, the timely detection, classification and blocking of malware are important. Malware visualization is a method for detecting or classifying malware. A global image is visualized through binaries extracted from malware. The overall structure and behavior of malware are considered when global images are utilized. However, the visualization of obfuscated malware is tough, owing to the difficulties encountered when extracting local features. This paper proposes a merged image-based malware classification framework that includes local feature visualization, global image-based local feature visualization, and global and local image merging methods. This study introduces a fastText-based local feature visualization method: First, local features such as opcodes and API function names are extracted from the malware; second, important local features in each malware family are selected via the term frequency inverse document frequency algorithm; third, the fastText model embeds the selected local features; finally, the embedded local features are visualized through a normalization process. Malware classification based on the proposed method using the Microsoft Malware Classification Challenge dataset was experimentally verified. The accuracy of the proposed method was approximately 99.65%, which is 2.18% higher than that of another contemporary global image-based approach.

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Wu, Lili, Ganesh K. Venayagamoorthy, and Jinfeng Gao. "Online Steady-State Security Awareness Using Cellular Computation Networks and Fuzzy Techniques." Energies 14, no. 1 (December 30, 2020): 148. http://dx.doi.org/10.3390/en14010148.

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Power system steady-state security relates to its robustness under a normal state as well as to withstanding foreseeable contingencies without interruption to customer service. In this study, a novel cellular computation network (CCN) and hierarchical cellular rule-based fuzzy system (HCRFS) based online situation awareness method regarding steady-state security was proposed. A CCN-based two-layer mechanism was applied for voltage and active power flow prediction. HCRFS block was applied after the CCN prediction block to generate the security level of the power system. The security status of the power system was visualized online through a geographic two-dimensional visualization mechanism for voltage magnitude and load flow. In order to test the performance of the proposed method, three types of neural networks were embedded in CCN cells successively to analyze the characteristics of the proposed methodology under white noise simulated small disturbance and single contingency. Results show that the proposed CCN and HCRFS combined situation awareness method could predict the system security of the power system with high accuracy under both small disturbance and contingencies.

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Fu Lu, Liang, Jia Wan Zhang, Mao Lin Huang, and Lei Fu. "A new concentric-circle visualization of multi-dimensional data and its application in network security." Journal of Visual Languages & Computing 21, no. 4 (August 2010): 194–208. http://dx.doi.org/10.1016/j.jvlc.2010.05.002.

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Dilla, William, Diane J. Janvrin, and Robyn Raschke. "Interactive Data Visualization: New Directions for Accounting Information Systems Research." Journal of Information Systems 24, no. 2 (September 1, 2010): 1–37. http://dx.doi.org/10.2308/jis.2010.24.2.1.

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ABSTRACT: Many companies today utilize interactive data visualization to present accounting information to external users on their investor relations websites and to internal users in applications such as enterprise resource planning, Balanced Scorecard, network security, and fraud detection systems. We develop a taxonomy for examining the current state of interactive data visualization research related to accounting decision making. We organize our review around three themes: the relationship between task characteristics and interactive data visualization techniques, the relationship between decision maker characteristics and interactive data visualization techniques, and the impact of interactive data visualization techniques on decision processes and outcomes. The review categorizes relevant research, describes the research questions addressed, and suggests avenues for further research.

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Benito-Santos, Alejandro, and Roberto Therón Sánchez. "Defragmenting Research Areas with Knowledge Visualization and Visual Text Analytics." Applied Sciences 10, no. 20 (October 16, 2020): 7248. http://dx.doi.org/10.3390/app10207248.

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The increasing specialization of science is motivating the fragmentation of traditional and well-established research areas into interdisciplinary communities of practice that focus on cooperation between experts to solve problems in a wide range of domains. This is the case of problem-driven visualization research (PDVR), in which groups of scholars use visualization techniques in different application domains such as the digital humanities, bioinformatics, sports science, or computer security. In this paper, we employ the findings obtained during the development of a novel visual text analytics tool we built in previous studies, GlassViz, to automatically detect interesting knowledge associations and groups of common interests between these communities of practice. Our proposed method relies on the statistical modeling of author-assigned keywords to make its findings, which are demonstrated in two use cases. The results show that it is possible to propose interactive, semisupervised visual approaches that aim at defragmenting a body of research using text-based, automatic literature analysis methods.

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Abid, Adnan, Ansar Abbas, Adel Khelifi, Muhammad Shoaib Farooq, Razi Iqbal, and Uzma Farooq. "An architectural framework for information integration using machine learning approaches for smart city security profiling." International Journal of Distributed Sensor Networks 16, no. 10 (October 2020): 155014772096547. http://dx.doi.org/10.1177/1550147720965473.

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In the past few decades, the whole world has been badly affected by terrorism and other law-and-order situations. The newspapers have been covering terrorism and other law-and-order issues with relevant details. However, to the best of our knowledge, there is no existing information system that is capable of accumulating and analyzing these events to help in devising strategies to avoid and minimize such incidents in future. This research aims to provide a generic architectural framework to semi-automatically accumulate law-and-order-related news through different news portals and classify them using machine learning approaches. The proposed architectural framework discusses all the important components that include data ingestion, preprocessor, reporting and visualization, and pattern recognition. The information extractor and news classifier have been implemented, whereby the classification sub-component employs widely used text classifiers for a news data set comprising almost 5000 news manually compiled for this purpose. The results reveal that both support vector machine and multinomial Naïve Bayes classifiers exhibit almost 90% accuracy. Finally, a generic method for calculating security profile of a city or a region has been developed, which is augmented by visualization and reporting components that maps this information onto maps using geographical information system.

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Liu, Zhaoli, Xiaohong Guan, Shancang Li, Tao Qin, and Chao He. "Behavior Rhythm: A New Model for Behavior Visualization and Its Application in System Security Management." IEEE Access 6 (2018): 73940–51. http://dx.doi.org/10.1109/access.2018.2882812.

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Meng, Linhao, Yating Wei, Rusheng Pan, Shuyue Zhou, Jianwei Zhang, and Wei Chen. "VADAF: Visualization for Abnormal Client Detection and Analysis in Federated Learning." ACM Transactions on Interactive Intelligent Systems 11, no. 3-4 (December 31, 2021): 1–23. http://dx.doi.org/10.1145/3426866.

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Federated Learning (FL) provides a powerful solution to distributed machine learning on a large corpus of decentralized data. It ensures privacy and security by performing computation on devices (which we refer to as clients) based on local data to improve the shared global model. However, the inaccessibility of the data and the invisibility of the computation make it challenging to interpret and analyze the training process, especially to distinguish potential client anomalies. Identifying these anomalies can help experts diagnose and improve FL models. For this reason, we propose a visual analytics system, VADAF, to depict the training dynamics and facilitate analyzing potential client anomalies. Specifically, we design a visualization scheme that supports massive training dynamics in the FL environment. Moreover, we introduce an anomaly detection method to detect potential client anomalies, which are further analyzed based on both the client model’s visual and objective estimation. Three case studies have demonstrated the effectiveness of our system in understanding the FL training process and supporting abnormal client detection and analysis.

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de Paula, Rogério, Xianghua Ding, Paul Dourish, Kari Nies, Ben Pillet, David F. Redmiles, Jie Ren, Jennifer A. Rode, and Roberto Silva Filho. "In the eye of the beholder: A visualization-based approach to information system security." International Journal of Human-Computer Studies 63, no. 1-2 (July 2005): 5–24. http://dx.doi.org/10.1016/j.ijhcs.2005.04.021.

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Golubev, Alexandr, Peter Bogatencov, and Grigore Secrieru. "DICOM data processing optimization in medical information systems." Scalable Computing: Practice and Experience 19, no. 2 (May 10, 2018): 189–201. http://dx.doi.org/10.12694/scpe.v19i2.1399.

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The problem of storage and visualization of medical images collected by various medical equipment is actual for latest 10 years for every medical institution. On the other hand, access to the medical investigation datasets and solving the problem of personal patient data security is important for scientific community and institutions that require this data. "DICOM Network" project was developed for solving these problems for different actors in the system based on the various customized roles. This article describes the problems and possible solutions for optimization of medical images storing, providing stable and secure access, based on the distributed warehouse for huge volumes of data with different levels of access. .

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Novikova, Evgenia, Igor Kotenko, and Ivan Murenin. "The Visual Analytics Approach for Analyzing Trajectories of Critical Infrastructure Employers." Energies 13, no. 15 (August 1, 2020): 3936. http://dx.doi.org/10.3390/en13153936.

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Employees of different critical infrastructures, including energy systems, are considered to be a security resource, and understanding their behavior patterns may leverage user and entity behavior analytics and improve organization capabilities in information threat detection such as insider threat and targeted attacks. Such behavior patterns are particularly critical for power stations and other energy companies. The paper presents a visual analytics approach to the exploratory analysis of the employees’ routes extracted from the logs of the access control system. Key elements of the approach are interactive self-organizing Kohonen maps used to detect groups of employees with similar movement trajectories, and heat maps highlighting possible anomalies in their movement. The spatiotemporal patterns of the routes are presented using a Gantt chart-based visualization model named BandView. The paper also discusses the results of efficiency assessment of the proposed analysis and visualization models. The assessment procedure was implemented using artificially generated and real-world data. It is demonstrated that the suggested approach may significantly increase the efficiency of the exploratory analysis especially under the condition when no prior information on existing employees’ moving routine is available.

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Si, Nianwen, Wenlin Zhang, Dan Qu, Xiangyang Luo, Heyu Chang, and Tong Niu. "Spatial-Channel Attention-Based Class Activation Mapping for Interpreting CNN-Based Image Classification Models." Security and Communication Networks 2021 (May 31, 2021): 1–13. http://dx.doi.org/10.1155/2021/6682293.

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Convolutional neural network (CNN) has been applied widely in various fields. However, it is always hindered by the unexplainable characteristics. Users cannot know why a CNN-based model produces certain recognition results, which is a vulnerability of CNN from the security perspective. To alleviate this problem, in this study, the three existing feature visualization methods of CNN are analyzed in detail firstly, and a unified visualization framework for interpreting the recognition results of CNN is presented. Here, class activation weight (CAW) is considered as the most important factor in the framework. Then, the different types of CAWs are further analyzed, and it is concluded that a linear correlation exists between them. Finally, on this basis, a spatial-channel attention-based class activation mapping (SCA-CAM) method is proposed. This method uses different types of CAWs as attention weights and combines spatial and channel attentions to generate class activation maps, which is capable of using richer features for interpreting the results of CNN. Experiments on four different networks are conducted. The results verify the linear correlation between different CAWs. In addition, compared with the existing methods, the proposed method SCA-CAM can effectively improve the visualization effect of the class activation map with higher flexibility on network structure.

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Wang, Weichao, and Aidong Lu. "Interactive Wormhole Detection and Evaluation." Information Visualization 6, no. 1 (January 25, 2007): 3–17. http://dx.doi.org/10.1057/palgrave.ivs.9500144.

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Wormhole attacks in wireless networks can severely deteriorate network performance and compromise security through spoiling the routing protocols and weakening the security enhancements. This paper develops an approach, interactive visualization of wormholes (IVoW), to monitor and detect such attacks in large-scale wireless networks in real time. We characterize the topology features of a network under wormhole attacks through the node position changes and visualize the information at dynamically adjusted scales. We integrate an automatic detection algorithm with appropriate user interactions to handle complicated scenarios that include a large number of moving nodes and multiple wormhole attackers. Various visual forms have been adopted to assist in the understanding and analysis of reconstructed network topology and to improve the detection accuracy. Extended simulation has demonstrated that the proposed approach can effectively locate the fake neighbor connections without introducing many false alarms. IVoW does not require the wireless nodes to be equipped with any special hardware, thus avoiding any additional cost. We have performed user studies to evaluate the effectiveness of our approach and demonstrate that visual analysis can be successfully combined with network security mechanisms to greatly improve intrusion detection capabilities.

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Figueiredo, Ciro, and Caroline Mota. "Learning Preferences in a Spatial Multiple Criteria Decision Approach: An Application in Public Security Planning." International Journal of Information Technology & Decision Making 18, no. 04 (July 2019): 1403–32. http://dx.doi.org/10.1142/s0219622019500251.

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This study presents a model to identify and classify vulnerable places regarding violence in public areas. The model considers multiple objectives and multiple viewpoints by using a graphical visualization for exploring vulnerability. The methodology is supported by a Dominance-based rough set approach in conjunction with preference learning and Geographic Information Systems, and requires the use of decision-makers’ (DMs’) previous knowledge for holistic assessment to get individual results. We considered an original approach for aggregating those individual results to obtain a recommendation from the final output. The preferences are assessed interactively to decrease the cognitive effort of each DM, starting from a small subset of holistic evaluations and expanding the process by incrementing new information in each stage of the model. We also assigned indicators to identify the quality of the results, participation in the individual preferences, and to avoid inconsistencies. We used the model to identify areas that merit more resources to combat crime and employed several criteria that assess types and levels of violence. These results may help policy-makers and planners to draw up and refine public policy interventions in the public security context.

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Baciu, George, Chenhui Li, Yunzhe Wang, and Xiujun Zhang. "Cloudet." International Journal of Cognitive Informatics and Natural Intelligence 10, no. 1 (January 2016): 12–31. http://dx.doi.org/10.4018/ijcini.2016010102.

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Streaming data cognition has become a dominant problem in interactive visual analytics for event detection, meteorology, cosmology, security, and smart city applications. In order to interact with streaming data patterns in an elastic cloud environment, we present a new elastic framework for big data visual analytics in the cloud, the Cloudet. The Cloudet is a self-adaptive cloud-based platform that treats both data and compute nodes as elastic objects. The main objective is to readily achieve the scalability and elasticity of cloud computing platforms in order to process large streaming data and adapt to potential interactions between data stream features. Our main contributions include a robust cloud-based framework called the Cloudet. This is a cloud profile manager that attempts to optimize resource parameters in order to achieve expressivity, scalability, reliability, and the proper aggregation of the compute nodes and data streams into several density maps for the purpose of dynamic visualization.

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Hingant, Javier, Marcelo Zambrano, Francisco J. Pérez, Israel Pérez, and Manuel Esteve. "HYBINT: A Hybrid Intelligence System for Critical Infrastructures Protection." Security and Communication Networks 2018 (August 27, 2018): 1–13. http://dx.doi.org/10.1155/2018/5625860.

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Cyberattacks, which consist of exploiting security vulnerabilities of computer networks and systems for any kind of malicious purpose (e.g., extortion, data steal, assets hijacking), have been continuously increasing worldwide in recent years. Cyberspace appears today as a new battlefield, along with physical world scenarios (land, sea, air, and space), for the organizations defence and security. Besides, by the fact that attacks from the physical world may have significant implications in the cyber world and vice versa, these dimensions cannot be understood independently. However, the most common intelligence systems offer an insufficient situational awareness exclusively focused on one of these decision spaces. This article introduces HYBINT, an enhanced intelligence system that provides the necessary decision-making support for an efficient critical infrastructures protection by combining the real-time situation of the physical and cyber domains in a single visualization space. HYBINT is a real cross-platform solution which supplies, through Big Data analytical methods and advanced representation techniques, hybrid intelligence information from significant data of both physical and cyber data sources in order to bring an adequate hybrid situational awareness (HSA) of the cyber-physical environment. The proposal will be validated in a detailed scenario in which HYBINT system will be evaluated.

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Fan, Youping, Xin Li, and Peng Zhang. "Integrated Approach for Online Dynamic Security Assessment With Credibility and Visualization Based on Exploring Connotative Associations in Massive Data." IEEE Access 5 (2017): 16555–67. http://dx.doi.org/10.1109/access.2017.2739818.

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Kagawa, Takuhiro, Sachio Saiki, and Masahide Nakamura. "Analyzing street crimes in Kobe city using PRISM." International Journal of Web Information Systems 15, no. 2 (June 17, 2019): 183–200. http://dx.doi.org/10.1108/ijwis-04-2018-0032.

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Purpose In a previous research, the authors proposed a security information service, called Personalized Real-time Information with Security Map (PRISM), which personalizes the incident information based on living area of individual users. The purpose of this paper is to extend PRISM to conduct sophisticated analysis of street crimes. The extended features enable to look back on past incident information and perform statistical analysis. Design/methodology/approach To analyze street crimes around living area in more detail, the authors add three new features to PRISM: showing a past heat map, showing a heat map focused on specified type of incidents and showing statistics of incidents for every type. Using these features, the authors visualize the dynamic transition of street crimes in a specific area and the whole region within Kobe city. They also compare different districts by statistics of street crimes. Findings Dynamical visualization clarifies when, where and what kind of incident occurs frequently. Most incidents occurred along three train lines in Kobe city. Wild boars are only witnessed in a certain region. Statistics shows that the characteristics of street crimes is completely different depending on living area. Originality/value Previously, many studies have been conducted to clarify factors relevant to street crimes. However, these previous studies mainly focus on interesting regions as a whole, but do not consider individual’s living area. In this paper, the authors analyze street crimes according to users’ living area using personalized security information service PRISM.

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Ossio, Raul, O. Isaac Garcia-Salinas, Diego Said Anaya-Mancilla, Jair S. Garcia-Sotelo, Luis A. Aguilar, David J. Adams, and Carla Daniela Robles-Espinoza. "VCF/Plotein: visualization and prioritization of genomic variants from human exome sequencing projects." Bioinformatics 35, no. 22 (June 4, 2019): 4803–5. http://dx.doi.org/10.1093/bioinformatics/btz458.

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Abstract Motivation Identifying disease-causing variants from exome sequencing projects remains a challenging task that often requires bioinformatics expertise. Here we describe a user-friendly graphical application that allows medical professionals and bench biologists to prioritize and visualize genetic variants from human exome sequencing data. Results We have implemented VCF/Plotein, a graphical, fully interactive web application able to display exome sequencing data in VCF format. Gene and variant information is extracted from Ensembl. Cross-referencing with external databases and application-based gene and variant filtering have also been implemented. All data processing is done locally by the user’s CPU to ensure the security of patient data. Availability and implementation Freely available on the web at https://vcfplotein.liigh.unam.mx. Website implemented in JavaScript using the Vue.js framework, with all major browsers supported. Source code freely available for download at https://github.com/raulossio/VCF-plotein. Supplementary information Supplementary data are available at Bioinformatics online.

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Dihl, Leandro, Leandro Cruz, and Nuno Gonçalves. "Card3DFace—An Application to Enhance 3D Visual Validation in ID Cards and Travel Documents." Applied Sciences 11, no. 19 (September 23, 2021): 8821. http://dx.doi.org/10.3390/app11198821.

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The identification of a person is a natural way to gain access to information or places. A face image is an essential element of visual validation. In this paper, we present the Card3DFace application, which captures a single-shot image of a person’s face. After reconstructing the 3D model of the head, the application generates several images from different perspectives, which, when printed on a card with a layer of lenticular lenses, produce a 3D visualization effect of the face. The image acquisition is achieved with a regular consumer 3D camera, either using plenoptic, stereo or time-of-flight technologies. This procedure aims to assist and improve the human visual recognition of ID cards and travel documents through an affordable and fast process while simultaneously increasing their security level. The whole system pipeline is analyzed and detailed in this paper. The results of the experiments performed with polycarbonate ID cards show that this end-to-end system is able to produce cards with realistic 3D visualization effects for humans.

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Wanner, Franz, Wolfgang Jentner, Tobias Schreck, Andreas Stoffel, Lyubka Sharalieva, and Daniel A. Keim. "Integrated visual analysis of patterns in time series and text data - Workflow and application to financial data analysis." Information Visualization 15, no. 1 (April 1, 2015): 75–90. http://dx.doi.org/10.1177/1473871615576925.

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In this article, we describe a workflow and tool that allows a flexible formation of hypotheses about text features and their combinations, which are significantly connected in time to quantitative phenomena observed in stock data. To support such an analysis, we combine the analysis steps of frequent quantitative and text-oriented data using an existing a priori method. First, based on heuristics, we extract interesting intervals and patterns in large time series data. The visual analysis supports the analyst in exploring parameter combinations and their results. The identified time series patterns are then input for the second analysis step, in which all identified intervals of interest are analyzed for frequent patterns co-occurring with financial news. An a priori method supports the discovery of such sequential temporal patterns. Then, various text features such as the degree of sentence nesting, noun phrase complexity, and the vocabulary richness, are extracted from the news items to obtain meta-patterns. Meta-patterns are defined by a specific combination of text features which significantly differ from the text features of the remaining news data. Our approach combines a portfolio of visualization and analysis techniques, including time, cluster, and sequence visualization and analysis functionality. We provide a case study and an evaluation on financial data where we identify important future work. The workflow could be generalized to other application domains such as data analysis of smart grids, cyber physical systems, or the security of critical infrastructure, where the data consist of a combination of quantitative and textual time series data.

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Robertson, George, David Ebert, Stephen Eick, Daniel Keim, and Ken Joy. "Scale and Complexity in Visual Analytics." Information Visualization 8, no. 4 (January 2009): 247–53. http://dx.doi.org/10.1057/ivs.2009.23.

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The fundamental problem that we face is that a variety of large-scale problems in security, public safety, energy, ecology, health care and basic science all require that we process and understand increasingly vast amounts and variety of data. There is a growing impedance mismatch between data size/complexity and the human ability to understand and interact with data. Visual analytic tools are intended to help reduce that impedance mismatch by using analytic tools to reduce the amount of data that must be viewed, and visualization tools to help understand the patterns and relationships in the reduced data. But visual analytic tools must address a variety of scalability issues if they are to succeed. In this paper, we characterize the scalability and complexity issues in visual analytics. We discuss some highlights on progress that has been made in the past 5 years, as well as key areas where more progress is needed.

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Obagbuwa, Ibidun Christiana, and Ademola P. Abidoye. "South Africa Crime Visualization, Trends Analysis, and Prediction Using Machine Learning Linear Regression Technique." Applied Computational Intelligence and Soft Computing 2021 (June 8, 2021): 1–14. http://dx.doi.org/10.1155/2021/5537902.

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South Africa has been classified as one of the most homicidal, violent, and dangerous places across the globe. However, the two elements that pushed South Africa high in the crime rank are the rates of social violence and homicide. It was reported by Business Insider that South Africa is among the most top 15 ferocious nations on earth. By 1995, South Africa was rated the second highest in terms of murder. However, the crime rate has reduced for some years and suddenly rose again in recent years. Due to social violence and crime rates in South Africa, foreign investors are no longer interested in continuing or starting a business with the nation, and hence, its economy is declining. South Africa’s government is looking for solutions to the crime issue and to redeem the image of the country in terms of high crime ranking and boost the confidence of the investors. Many traditional approaches to data analysis in crime-related studies have been done in South Africa, but the machine learning approach has not been adequately considered. The police station and many other agencies that deal with crime hold a lot of databases that can be used to predict or analyze criminal happenings across the provinces of South Africa. This research work aimed at offering a solution to the problem by building a model that can predict crime. The machine learning approach shall be used to extract useful information from South Africa's nine provinces' crime data. A crime prediction system that can analyze and predict crime is proposed. To accomplish this, South Africa crime data on 27 crime categories were obtained from the popular data repository “Kaggle.” Diverse data analytics steps were applied to preprocess the datasets, and a machine learning algorithm (linear regression) was used to build a predictive model to analyze data and predict future crime. The appropriate authorities and security agencies in South Africa can have insight into the crime trends and alleviate them to encourage the foreign stakeholders to continue their businesses.

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Cook, Kristin, Georges Grinstein, and Mark Whiting. "The VAST Challenge: history, scope, and outcomes: An introduction to the Special Issue." Information Visualization 13, no. 4 (July 12, 2013): 301–12. http://dx.doi.org/10.1177/1473871613490678.

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The annual Visual Analytics Science and Technology (VAST) challenge provides Visual Analytics researchers, developers, and designers an opportunity to apply their best tools and techniques against invented problems that include a realistic scenario, data, tasks, and questions to be answered. Submissions are processed much like conference papers, contestants are provided reviewer feedback, and excellence is recognized with awards. A day-long VAST Challenge workshop takes place each year at the IEEE VAST conference to share results and recognize outstanding submissions. Short papers are published each year in the annual VAST proceedings. Over the history of the challenge, participants have investigated a wide variety of scenarios, such as bioterrorism, epidemics, arms smuggling, social unrest, and computer network attacks, among many others. Contestants have been provided with large numbers of realistic but synthetic Coast Guard interdiction records, intelligence reports, hospitalization records, microblog records, personal RFID tag locations, huge amounts of cyber security log data, and several hours of video. This paper describes the process for developing the synthetic VAST Challenge datasets and conducting the annual challenges. This paper also provides an introduction to this special issue of Information Visualization, focusing on the impacts of the VAST Challenge.

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Huang, Ruhua, Chunying Wang, Xiaoyu Zhang, Dan Wu, and Qingwen Xie. "Design, develop and evaluate an open government data platform: a user-centred approach." Electronic Library 37, no. 3 (June 3, 2019): 550–62. http://dx.doi.org/10.1108/el-02-2019-0037.

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Purpose The purpose of this paper is to describe the process of designing, developing and evaluating a prototype of an open government data (OGD) platform that provided user-centred experiences. Design/methodology/approach Based on the OGD lifecycle, an OGD prototype was created, which involved the system functionality, user interface, standard specification and security mechanism. The main functionalities of the system included data acquisition, data processing and data management. A usability test was conducted following the prototype implementation. Findings The usability test indicated that an OGD platform was desired to help the public to find, access, reuse and share government data effectively and efficiently. Functions, such as visualization, local download and digital watermark should be provided and integrated into the platform. Originality/value This paper provided a complete case study on the design of an OGD platform and a reference for information system developers to design such system in the future.

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Schweitzer, Dino, Jeff Boleng, Colin Hughes, and Louis Murphy. "Visualizing Keyboard Pattern Passwords." Information Visualization 10, no. 2 (November 18, 2010): 127–33. http://dx.doi.org/10.1057/ivs.2010.12.

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Passwords are fundamental security vulnerabilities in many systems. Several researchers have investigated the trade-off between password memorability versus resiliency to cracking and have looked at alternative systems such as graphical passwords and biometrics. To create stronger passwords, many systems enforce rules regarding the required length and types of characters passwords must contain. Another suggested approach is to use passphrases to combat dictionary attacks. One common ‘trick’ used to remember passwords that conform to complex rules is to select a pattern of keys on the keyboard. Although appearing random, the pattern is easy to remember. The purpose of this research was to investigate how often patterns are used, whether patterns could be classified into common categories, and whether those categories could be used to attack and defeat pattern-based passwords. Visualization techniques were used to collect data and assist in pattern categorization. The approach successfully identified 2 out of 11 passwords in a real-world password file that were not discovered with a traditional dictionary attack. This article will present the approach used to collect and categorize patterns, and describe the resulting attack method that successfully identified passwords in a live system.

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Lakhno, Valeriy, Volodimir Malyukov, Berik Akhmetov, Dmytro Kasatkin, and Liubov Plyska. "Development of a model for choosing strategies for investing in information security." Eastern-European Journal of Enterprise Technologies 2, no. 3 (110) (April 30, 2021): 43–51. http://dx.doi.org/10.15587/1729-4061.2021.228313.

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This paper has proposed a model of the computational core for the decision support system (DSS) when investing in the projects of information security (IS) of the objects of informatization (OBI). Including those OBI that can be categorized as critically important. Unlike existing solutions, the proposed model deals with decision-making issues in the ongoing process of investing in the projects to ensure the OBI IS by a group of investors. The calculations were based on the bilinear differential quality games with several terminal surfaces. Finding a solution to these games is a big challenge. It is due to the fact that the Cauchy formula for bilinear systems with arbitrary strategies of players, including immeasurable functions, cannot be applied in such games. This gives grounds to continue research on finding solutions in the event of a conflict of multidimensional objects. The result was an analytical solution based on a new class of bilinear differential games. The solution describes the interaction of objects investing in OBI IS in multidimensional spaces. The modular software product "Cybersecurity Invest decision support system " (Ukraine) for the Windows platform is described. Applied aspects of visualization of the results of calculations obtained with the help of DSS have been also considered. The Plotly library for the Python algorithmic language was used to visualize the results. It has been shown that the model reported in this work can be transferred to other tasks related to the development of DSS in the process of investing in high-risk projects, such as information technology, cybersecurity, banking, etc.

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Kwon, Hyun, Hyunsoo Yoon, and Ki-Woong Park. "Selective Poisoning Attack on Deep Neural Networks †." Symmetry 11, no. 7 (July 8, 2019): 892. http://dx.doi.org/10.3390/sym11070892.

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Studies related to pattern recognition and visualization using computer technology have been introduced. In particular, deep neural networks (DNNs) provide good performance for image, speech, and pattern recognition. However, a poisoning attack is a serious threat to a DNN’s security. A poisoning attack reduces the accuracy of a DNN by adding malicious training data during the training process. In some situations, it may be necessary to drop a specifically chosen class of accuracy from the model. For example, if an attacker specifically disallows nuclear facilities to be selectively recognized, it may be necessary to intentionally prevent unmanned aerial vehicles from correctly recognizing nuclear-related facilities. In this paper, we propose a selective poisoning attack that reduces the accuracy of only the chosen class in the model. The proposed method achieves this by training malicious data corresponding to only the chosen class while maintaining the accuracy of the remaining classes. For the experiment, we used tensorflow as the machine-learning library as well as MNIST, Fashion-MNIST, and CIFAR10 as the datasets. Experimental results show that the proposed method can reduce the accuracy of the chosen class by 43.2%, 41.7%, and 55.3% in MNIST, Fashion-MNIST, and CIFAR10, respectively, while maintaining the accuracy of the remaining classes.

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Han, Zhike, Xiuchao Wu, Meng Chi, Jun Tang, and Lijing Yang. "A Novel Approach to Transform Bitmap to Vector Image for Data Reliable Visualization considering the Image Triangulation and Color Selection." Security and Communication Networks 2020 (November 2, 2020): 1–13. http://dx.doi.org/10.1155/2020/8871588.

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Vector image is a type of image composed of many geometric primitives. Compared with bitmaps, vector images have the ability to save memory as well as to enlarge without distortion. Meanwhile, it has been commonly adopted in data visualization (image data) because it can be scaled to multiple sizes to fit different scenes. For instance, it can be applied for the illustrations in newspapers and magazines, the logo on the web, the background for poster, the design of text, and traffic signs. However, transforming a bitmap to vector image is still a challenging problem because of the complicated content of a bitmap, which tends to consist of more than just simple geometry. Aiming at this issue, there is a new approach proposed to transform from bitmaps to vector images, which is based on triangle units and consists of three steps. In detail, firstly, there is an initial mesh constructed for one image in pixel level after detecting features. Then, the initial mesh will be simplified by collapsing two vertices as the initial mesh is too dense to represent one image. Specifically, there are two main parts in this step, which are collapse conditions and collapse influences. In the step of collapsing, issues such as overlap and sharp triangles can be conquered by a sort-edge method (which will be illustrated specifically later). The final step is to select one color for each triangle, since it is helpful to save the memory and speed up the process of this method. In addition, one color will represent one triangle; hence, in the final step, the four-triangle sample method will be applied in order to prevent a vector image from generating too large color discontinuity. Once the pretest proceeds without mistake, the method above is able to work for the general bitmaps. Note that our method can be applied to information security and privacy, since one image can be encoded to some triangles and colors.

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Babu, MVS, KNS Suman, and P. Srinivasa Rao. "Drafting software as a practicing tool for engineering drawing-based courses: Content planning to its evaluation in client–server environment." International Journal of Mechanical Engineering Education 47, no. 2 (January 25, 2018): 118–34. http://dx.doi.org/10.1177/0306419017754226.

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In under graduate engineering education, engineering drawing is a basic course offered to 1st semester engineering students. With the advent of computers, the traditional engineering drawing practice in both industry and academia is being extensively replaced with computer aided engineering drawing. The present scenario in Indian engineering educational institutions has been studied and based on it an approach is proposed in the present paper, which involves the integration of software-based practice with client–server architecture. The proposed approach has been implemented to practice in our institute for few years. The use of this approach is required proper planning of the course content, delivery, practice and evaluation. The detailed discussion on the approach and its implications are examined through results. All the stakeholders are benefited by adopting this approach. The present paper focuses on the use of drafting software for the practice of engineering drawing-based courses in a secured client–server environment. This proposed approach guarantees multiple cascading advantages of improved understanding and enhanced spatial visualization among students. The proposed approach has been implemented for the students who admitted in the academic year 2014–15. The end exam results of these students have been compared with results of the batch admitted in academic year 2013–14. It was observed that the number of failures in the proposed approach were reduced up to 85% compared to conventional mode. Further, it facilitates to modernize the conduct of courses, provides data security, optimizes the utilization of computing facilities and most importantly it tests the students for the understanding of the topic and not for their artistic skills. Ultimately, it makes the engineering students industry-ready by enhancing their employability skills.

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Apostolakis, Konstantinos C., Nikolaos Dimitriou, George Margetis, Stavroula Ntoa, Dimitrios Tzovaras, and Constantine Stephanidis. "DARLENE – Improving situational awareness of European law enforcement agents through a combination of augmented reality and artificial intelligence solutions." Open Research Europe 1 (July 30, 2021): 87. http://dx.doi.org/10.12688/openreseurope.13715.1.

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Background: Augmented reality (AR) and artificial intelligence (AI) are highly disruptive technologies that have revolutionised practices in a wide range of domains. Their potential has not gone unnoticed in the security sector with several law enforcement agencies (LEAs) employing AI applications in their daily operations for forensics and surveillance. In this paper, we present the DARLENE ecosystem, which aims to bridge existing gaps in applying AR and AI technologies for rapid tactical decision-making in situ with minimal error margin, thus enhancing LEAs’ efficiency and Situational Awareness (SA). Methods: DARLENE incorporates novel AI techniques for computer vision tasks such as activity recognition and pose estimation, while also building an AR framework for visualization of the inferenced results via dynamic content adaptation according to each individual officer’s stress level and current context. The concept has been validated with end-users through co-creation workshops, while the decision-making mechanism for enhancing LEAs’ SA has been assessed with experts. Regarding computer vision components, preliminary tests of the instance segmentation method for humans’ and objects’ detection have been conducted on a subset of videos from the RWF-2000 dataset for violence detection, which have also been used to test a human pose estimation method that has so far exhibited impressive results and will constitute the basis of further developments in DARLENE. Results: Evaluation results highlight that target users are positive towards the adoption of the proposed solution in field operations, and that the SA decision-making mechanism produces highly acceptable outcomes. Evaluation of the computer vision components yielded promising results and identified opportunities for improvement. Conclusions: This work provides the context of the DARLENE ecosystem and presents the DARLENE architecture, analyses its individual technologies, and demonstrates preliminary results, which are positive both in terms of technological achievements and user acceptance of the proposed solution.

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Lin, Hui, Pei Liu, Wei Li, Lian Peng Zhang, and Ya Zhou Ji. "Construction of Digital Mine and Key Technologies." Advanced Materials Research 524-527 (May 2012): 413–20. http://dx.doi.org/10.4028/www.scientific.net/amr.524-527.413.

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In China, the mine is facing a stern challenge over its environmental protection, the limitation on its structure and function within its subsystem, optimization of its limited manpower, financial and material resources and its sustainable development. Digital mine is come up with to deal with all these problems. The Digital Mine can be liken to “a logistics supply chain”, the basic characteristic is the high-speed network, with broadband and two-way communication system, used as “path map”, which shall make sure the fast delivery of all the data within all the relevant enterprises in the country; It consists of vehicles, which refers to the techniques of Mine CAD, virtual reality, mine simulation, scientific calculation, artificial intelligence, visualization and office automation; goods, which refers to mine data and mind application model; package, which refers to 3DGM(3-Dimensional Geographical Model) and data mining; security system, which refers to the collection and renewal system of mine data; and dispatching system, which refers to MGIS(Mine Geographical Information System), the common carrier of the entire information and office decisions, controlling the use and operation of all vehicles as well as all of the goods production and the package system. The basic structure of the Digital Mine is composed of two parts: digital ground and digital mine. The digital ground is a management information system based on the EPR (Enterprise Resource Planning) and spatial information infrastructure and information system based on 3S technology and computer network. The digital mine regards the mine geology and surveying data as basic information data for spatial positioning, furthermore, inputting other relevant information if necessary, such as mining working-face, excavating working-face, underground chamber, mechanical and electronic equipments, ventilation and safety device, underground pipeline and communication and others, forming a spatial database. Thus, the entire mine’s information system of management and service and decision support system is established. The Digital Mine is a huge systematic project, involving 3S (GIS, GPS, RS), IT (Information technology), mine science, virtual reality technology and visualization technology. Based on computers and network communication, the Digital Mine realizes the digitization of storing, transporting, expressing and applying of all the relevant spatial data and attribute data, including mine construction, exploration, development, mining, environmental protection and control. In addition, it is also a huge artificial intellectual system that integrates digital construction, digital exploration, digital mining, digital environmental protection and digital forecasting based on data dictionary technology, data warehouse technology, WebGIS, virtual reality technology, multimedia technology, CASE technology and artificial intelligence technology.

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., Himanshi, Trisha Gulati, and Yasha Hasija. "Biometrics in Healthcare." INTERNATIONAL JOURNAL OF ADVANCED PRODUCTION AND INDUSTRIAL ENGINEERING 3, no. 2 (April 15, 2018): 13–17. http://dx.doi.org/10.35121/ijapie201804223.

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Biometrics is the discipline to measure physical human characteristics for the identification and authentication of an individual. Since ancient times, people have used voice, face, and other characteristics for the identification of an individual. With evolution, we take the individual characteristics like fingerprint scans, retina and iris images, etc., as inputs to the computer systems and then store or verify them with existing records. This report discusses biometrics and its recent roles found in the field of healthcare, medicine, genetics, and biotechnology. It includes the concept of biometrics, the system used for biometric recognition and its working, types of biometric systems, the different system algorithms applied, and system modules which are well illustrated with flow charts and block diagrams. Some of the health institutes in developed countries have started using biometric systems for checking patients and/or doctors. Biometry has enabled the proper organization and storage of the health records of individuals in medical institutes. Biometric authentication is also finding a distinct role in foiling medical claims fraud highlighting the advantages it. Even after processing via a very accurate biometric system, there is a chance of a false result due to some disease or injury to the body part subjected to biometry or faulty system leading to some error. There is also a possibility that the biometric system may harm our bodies. Moreover, biometric records need really tight system security to prevent any kind of misuse. Biometrics has a great potential to find a lot more uses in the field of healthcare. Many ideas are being proposed for implementation. In the future, biometrics can be used to detect potential disease and risks by using methods like adiposity measurement and Gas Discharge Visualization (GDV).

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Journal articles on the topic 'Visualization Computer security'

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