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Full-Text Articles in Physical Sciences and Mathematics
Objsim: Efficient Testing Of Cyber-Physical Systems, Jun Sun, Zijiang Yang
Objsim: Efficient Testing Of Cyber-Physical Systems, Jun Sun, Zijiang Yang
Research Collection School Of Computing and Information Systems
Cyber-physical systems (CPSs) play a critical role in automating public infrastructure and thus attract wide range of attacks. Assessing the effectiveness of defense mechanisms is challenging as realistic sets of attacks to test them against are not always available. In this short paper, we briefly describe smart fuzzing, an automated, machine learning guided technique for systematically producing test suites of CPS network attacks. Our approach uses predictive ma- chine learning models and meta-heuristic search algorithms to guide the fuzzing of actuators so as to drive the CPS into different unsafe physical states. The approach has been proven effective on two …
Graphh: High Performance Big Graph Analytics In Small Clusters, Peng Sun, Yonggang Wen, Nguyen Binh Duong Ta, Xiaokui Xiao
Graphh: High Performance Big Graph Analytics In Small Clusters, Peng Sun, Yonggang Wen, Nguyen Binh Duong Ta, Xiaokui Xiao
Research Collection School Of Computing and Information Systems
It is common for real-world applications to analyze big graphs using distributed graph processing systems. Popular in-memory systems require an enormous amount of resources to handle big graphs. While several out-of-core approaches have been proposed for processing big graphs on disk, the high disk I/O overhead could significantly reduce performance. In this paper, we propose GraphH to enable highperformance big graph analytics in small clusters. Specifically, we design a two-stage graph partition scheme to evenly divide the input graph into partitions, and propose a GAB (GatherApply-Broadcast) computation model to make each worker process a partition in memory at a time. …
Visualization For Anomaly Detection And Data Management By Leveraging Network, Sensor And Gis Techniques, Zhaoxia Wang, Chee Seng Chong, Rick S. M. Goh, Wanqing Zhou, Dan Peng, Hoong Chor Chin
Visualization For Anomaly Detection And Data Management By Leveraging Network, Sensor And Gis Techniques, Zhaoxia Wang, Chee Seng Chong, Rick S. M. Goh, Wanqing Zhou, Dan Peng, Hoong Chor Chin
Research Collection School Of Computing and Information Systems
This paper studies the importance of visualization for discerning and interpreting patterns of data and its application for solving real problems, such as anomaly detection and data management. There are various ways to realize visualization to cater to the needs of numerous real life applications. Depending on needs, a combination of some of these ways may be required for presenting an effective visualization. The authors present visualization schemes for anomaly detection/condition monitoring and data management by leveraging network techniques and combining them with modern techniques such as sensor, database, mobile communication, GPS and GIS techniques. Two case studies are presented …
On Integrating Existing Bibliographic Databases And Structured Databases, Ying Lu, Ee Peng Lim
On Integrating Existing Bibliographic Databases And Structured Databases, Ying Lu, Ee Peng Lim
Research Collection School Of Computing and Information Systems
It is widely accepted that future digital library applications have to be built upon different kinds of database servers to draw different forms of data from them. These data include bibliographic data, text data, multimedia data, and structured data. We address the problem of integrating existing bibliographic and structured databases which reside at different locations in the network. To integrate bibliographic data and structured data, we extended the well-known SQL model to represent bibliographic related attributes and queries. In particular, we have added a new data type to model attributes in the bibliographic database. We have also designed specialized predicates …