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Vulnerability Digging for Software-Defined Network Controller Using Event Flow Graph Analysis

Zehui Wu, Wenbin Zhang, Yunchao Wang, Chenyu Yan, Mohammad Ayoub Khan
2022 Security and Communication Networks  
Different from file processing software, network software is driven by events, and the event flow can more accurately and comprehensively reflect the execution process.  ...  Vulnerabilities in the SDN controller can paralyze the whole network.  ...  At the same time, the frequent evolution patterns of dynamic event flow graphs are mined.  ... 
doi:10.1155/2022/9642517 fatcat:kqyot4be2zgnpe4kwjpo6oimxm

Incremental local community identification in dynamic social networks

Mansoureh Takaffoli, Reihaneh Rabbany, Osmar R. Zaïane
2013 Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining - ASONAM '13  
Communities in a dynamic social network span over periods of time and are affected by changes in the underlying population, i.e. they have fluctuating members and can grow and shrink over time.  ...  Examining how the structure of these networks changes over time provides insights into their evolution patterns, factors that trigger the changes, and ultimately predict the future structure of these networks  ...  CONCLUSION One of the challenging research problems in dynamic social networks is to mine communities and analyze their evolution over the observation time.  ... 
doi:10.1145/2492517.2492633 dblp:conf/asunam/TakaffoliRZ13 fatcat:jpti6h2dwfdynipanilk7dyaie

Modeling dynamics of social networks: A survey

Saoussen Aouay, Salma Jamoussi, Faiez Gargouri, Ajith Abraham
2014 2014 6th International Conference on Computational Aspects of Social Networks  
By tradition, social network analysis (SNA) is performed on static graphs but this representation is very limited for a sound, network analysis.  ...  This paper does the survey of complex networks models and methods which are proposed to reproduce structural changes of these graphs.  ...  Then, they tried to discover association rules between frequent patterns of interaction (sub-graphs) to illustrate the evolution of the network.  ... 
doi:10.1109/cason.2014.6920421 dblp:conf/cason/AouayJGA14 fatcat:ctrfprio6bga3bkrdxmj2453ry

Incremental Community Mining in Location-based Social Network

Loubna Boujlaleb, Ali Idarrou, Driss Mammass
2018 International Journal of Advanced engineering Management and Science  
The goal of this paper is to study community detection in dynamic social network in the context of location -based social network.  ...  A social network can be defined as a set of social entities connected by a set of social relations. These relations often change and differ in time.  ...  The pseudo code related to the previous process is given in algorithm 1. 3.2.2 Overlapping setting In the case of overlapping communities, we apply the same process given in algorithm 1 by changing the  ... 
doi:10.22161/ijaems.4.8.8 fatcat:aorzhp7nfrfg3ik6hgads5putu

Graph Data Management and Mining: A Survey of Algorithms and Applications [chapter]

Charu C. Aggarwal, Haixun Wang
2010 Managing and Mining Graph Data  
localization and computer networking.  ...  Graph mining and management has become a popular area of research in recent years because of its numerous applications in a wide variety of practical fields, including computational biology, software bug  ...  The problem of community detection is particularly interesting in the context of dynamic analysis of evolving networks in which we try to determine how the communities in the graph may change over time  ... 
doi:10.1007/978-1-4419-6045-0_2 dblp:series/ads/AggarwalW10a fatcat:tzo627bhpndl3iedhtru6vv6vy

Research Challenges for Data Mining in Science and Engineering [chapter]

Jiawei Han, Jing Gao
2008 Chapman & Hall/CRC Data Mining and Knowledge Discovery Series  
In this paper, we discuss the research challenges in science and engineering, from the data mining perspective, with a focus on the following issues: (1) information network analysis, (2) discovery, usage  ...  text, Web, and other unstructured data, (7) data cube-oriented multidimensional online analytical mining, (8) visual data mining, and (9) data mining by integration of sophisticated scientific and engineering  ...  Moreover, frequent patterns have been used for effective classification by top-k rule generation for long patterns and discriminative frequent pattern analysis [7] .  ... 
doi:10.1201/9781420085877.pt1 fatcat:ljs2uybdofgkxfpouawfekdaz4

A Method of Ontology Evolution and Concept Evaluation Based on Knowledge Discovery in the Heavy Haul Railway Risk System [chapter]

Tiancheng Cao, Wenxin Mu, Aurélie Montarnal, Anne-Marie Barthe-Delanoë
2019 IFIP Advances in Information and Communication Technology  
Under collaborative relationships formed by reasoning rules between context and risk, this paper establishes evolution mechanism of SRAC to introduce new knowledge, such as knowledge extracted from device  ...  detection data.  ...  The presented research works have been supported by "the National Science Foundation for Young Scientists of China" (61703032, Context based Multi-dimension ontology modeling and alignment).  ... 
doi:10.1007/978-3-030-28464-0_20 fatcat:vcydvw6surebtagjyvu7m3bpma

Evolutionary Network Analysis

Charu Aggarwal, Karthik Subbian
2014 ACM Computing Surveys  
When a network evolves, the results of data mining algorithms such as community detection need to be correspondingly updated.  ...  This survey provides an overview of the vast literature on graph evolution analysis and the numerous applications that arise in different contexts.  ...  ACKNOWLEDGMENTS Research was sponsored by the Army Research Laboratory and was accomplished under Cooperative Agreement Number W911NF-09-2-0053.  ... 
doi:10.1145/2601412 fatcat:hvm37apdbzgnzkgilt2te6gfba

Design of Complex Network Distributed Computing Information Mining Method

Yiran Wang, Guang Zheng
2015 International Journal of Grid and Distributed Computing  
The information that caused by the complex network is massive, but because of a large amount of information, so the use of traditional data analysis has been unable to meet the search and mining complex  ...  This paper presents a data mining model matrix, according to this model can integrate different information, optimization of data mining, so as to improve the efficiency of complex network distributed  ...  No 142300410334), the funding scheme for young backbone teachers of colleges and universities in Henan Province, China.  ... 
doi:10.14257/ijgdc.2015.8.5.09 fatcat:oxmndlmbjze37jdxf6dpd4ynle

Relational mining for discovering changes in evolving networks

Corrado Loglisci, Michelangelo Ceci, Donato Malerba
2015 Neurocomputing  
Discovery of change patterns Change mining in networked data a b s t r a c t Networks are data structures more and more frequently used for modeling interactions in social and biological phenomena, as  ...  by heterogeneous nodes and/or heterogeneous relationships, and (ii) by proposing a novel algorithm for discovering changes in the structure of a dynamic network over time.  ...  GERM operates directly on the cumulative graph from which it mines frequent sub-graphs that express the evolutions.  ... 
doi:10.1016/j.neucom.2014.08.079 fatcat:cijjp2otjbcihppe6mh2ojuhvy

Efficient frequent subgraph mining on large streaming graphs

Abhik Ray, Lawrence B. Holder, Albert Bifet
2019 Intelligent Data Analysis  
The problem of finding frequent subgraphs in large dynamic graphs has so far only considered a dynamic graph as being represented by a series of static snapshots taken at various points in time.  ...  This representation of a dynamic graph does not lend itself well to real time processing of real world graphs like social networks or internet traffic which consist of a stream of nodes and edges.  ...  This material is based upon work supported by the National Science Foundation under Grant No. 1318913.  ... 
doi:10.3233/ida-173705 fatcat:gqz4butjafagvfi726joa3fmu4

Vertex-centred Method to Detect Communities in Evolving Networks [chapter]

Maël Canu, Marie-Jeanne Lesot, Adrien Revault d'Allonnes
2016 Studies in Computational Intelligence  
The proposed algorithm, named Dyn-LOCNeSs, detects communities by scanning and evaluating each vertex neighbourhood by means of a preference measure, using these preferences to handle community changes  ...  Finding communities in evolving networks is a difficult task and raises issues different from the classic static detection case. We introduce an approach based on the recent vertex-centred paradigm.  ...  Most community detection methods to date were designed to process static networks (see Section 2), however complex networks change over time and require methods able to take into account their dynamic  ... 
doi:10.1007/978-3-319-50901-3_22 fatcat:q5a3i32dyfeifiexdusyykglga

Vertex-centred Method to Detect Communities in Evolving Networks [article]

Maël Canu, Adrien Revault d'Allonnes
2016 arXiv   pre-print
It is done by means of a preference measure, using these preferences to handle community changes.  ...  Finding communities in evolving networks is a difficult task and raises issues different from the classic static detection case. We introduce an approach based on the recent vertex-centred paradigm.  ...  Most community detection methods to date were designed to process static networks (see Section 2), however complex networks change over time and require methods able to take into account their dynamic  ... 
arXiv:1611.08484v1 fatcat:6wst744ctfcdhccyxk6svnorv4

Algorithms for Mining the Evolution of Conserved Relational States in Dynamic Networks

Rezwan Ahmed, George Karypis
2011 2011 IEEE 11th International Conference on Data Mining  
in these networks.  ...  This paper presents a new data mining method that analyzes the time-persistent relations or states between the entities of the dynamic networks and captures all maximal non-redundant evolution paths of  ...  ACKNOWLEDGEMENT This work was supported in part by NSF (IIS-0905220, OCI-1048018, and IOS-0820730) and by the DOE grant USDOE/DE-SC0005013 and the Digital Technology Center at the University of Minnesota  ... 
doi:10.1109/icdm.2011.20 dblp:conf/icdm/AhmedK11 fatcat:jcdrbbvl25efnfhlnt474dszqu

Discovering descriptive rules in relational dynamic graphs

Kim-Ngan T. Nguyen, Loïc Cerf, Marc Plantevit, Jean-Françcois Boulicaut, Ruggero G. Pensa, Francesca Cordero, Céine Rouveirol, Rushed Kanawati
2013 Intelligent Data Analysis  
Graph mining methods have become quite popular and a timely challenge is to discover dynamic properties in evolving graphs or networks.  ...  We consider the so-called relational dynamic oriented graphs that can be encoded as n-ary relations with n 3 and thus represented by Boolean tensors.  ...  Acknowledgements This work was partly funded by the ANR project FOSTER (COSINUS 2010), by FAPEMIG, and by a grant from the Vietnamese government.  ... 
doi:10.3233/ida-120567 fatcat:s4ck47vfqnczfmeq4kdjsrc63q
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