Semantic concept recognition from structured and unstructured inputs within cyber security domain

Hoşsucu, Alp Gökhan
Linked data initiative has been quite successful in terms of publishing and interlinking data over ontological structures. The success is due to answering semantically rich queries over highly structured data. The utilization of linked data structures are widely used in various domains to solve the problem of producing domain specific knowledge which can be interpreted by automated agents without any human interference. Cyber security field is one of the domains that suffer from the excessiveness of the raw data and lacking of the knowledge which constantly requires incorporation of subject matter experts in security analyzes or reasoning processes. The principle aim of this study is to propose an automated approach for cyber-security related knowledge base generation from scratch by utilizing from both structured and unstructured domain related data. The proposed approach is based on the automatic extraction of significant phrases and conversion of them into semantic concepts within the scope of already existing cyber security databases CWE, CPE, VVS and CCE. The system utilizes this raw data, differentiates the structured and unstructured parts which are processed in different modules for knowledge extraction. These concepts are represented in RDF format which includes all the relationships between entities to construct ontology for cyber security domain. To enhance the knowledge extraction process, NLP oriented approaches including Key Phrase Extraction methodologies are used and data augmentation techniques are applied to the concepts by interlinking them to the entities in Freebase and Wikipedia indexes. As a consequence of these operation series, a modular system is developed which is capable of extracting knowledge from the given cyber security related data. This accumulated knowledge constitutes a basis for cyber-security ontology which can be used for further vulnerability identification and prevention.


Computational platform for predicting lifetime system reliability profiles for different structure types in a network
Akgül, Ferhat (2004-01-01)
This paper presents a computational platform for predicting the lifetime system reliability profiles for different structure types located in an existing network. The computational platform has the capability to incorporate time-variant live load and resistance models. Following a review of the theoretical basis, the overall architecture of the computational platform is described. Finally, numerical examples of three existing bridges (i.e., a steel, a prestressed concrete, and a hybrid steel-concrete bridge...
Multiobjective relational data warehouse design for the cloud
Dökeroğlu, Tansel; Coşar, Ahmet; Department of Computer Engineering (2014)
Conventional distributed DataWarehouse (DW) design techniques seek to assign data tables/fragments to a given static database hardware setting optimally. However; it is now possible to use elastic virtual resources provided by the Cloud environment, thus achieve reductions in both the execution time and the monetary cost of a DW system within predefined budget and response time constraints. Finding an optimal assignment plan for database tables to machines for this design problem is NP-Hard. Therefore, robu...
Data sharing and access with a corba data distribution service implementation
Dursun, Mustafa; Bilgen, Semih; Department of Electrical and Electronics Engineering (2006)
Data Distribution Service (DDS) specification defines an API for Data-Centric Publish-Subscribe (DCPS) model to achieve efficient data distribution in distributed computing environments. Lack of definition of interoperability architecture in DDS specification obstructs data distribution between different and heterogeneous DDS implementations. In this thesis, DDS is implemented as a CORBA service to achieve interoperability and a QoS policy is proposed for faster data distribution with CORBA features.
Semantic information-based alternative plan generation for multiple query optimization
Polat, Faruk; Alhajj, R (Elsevier BV, 2001-09-01)
This paper addresses the impact of semantic information about queries on alternative plan generation (APG) for multiple query optimization (MQO). MQO covers optimizing the execution of a set of queries together where each query in the set to be optimized has several alternative execution plans. A multiple query optimizer selects an alternative plan for each query to obtain an optimal global execution plan. Our approach uses information such as common relations, common possible joins and common conditions to...
A systematic approach to the integration of overlapping partitions in service-oriented data grids
Sunercan, H. Kevser; Alpdemir, M. Nedim; Çiçekli, Fehime Nihan (Elsevier BV, 2011-06-01)
This paper aims to provide a service-oriented data integration solution over data Grids for cases where distributed data sources are partitioned with overlapping sections of various proportions. This is an interesting variation which combines both replicated and partitioned data within the same data management framework. Thus, the data management infrastructure has to deal with specific challenges regarding the identification, access and aggregation of partitioned data with varying proportions of overlappin...
Citation Formats
A. G. Hoşsucu, “Semantic concept recognition from structured and unstructured inputs within cyber security domain,” M.S. - Master of Science, Middle East Technical University, 2015.