Biblio

This paper presents an ontological approach to perceive the current security status of the network. Computer network is a dynamic entity whose state changes with the introduction of new services, installation of new network operating system, and addition of new hardware components, creation of new user roles and by attacks from various actors instigated by aggressors. Various security mechanisms employed in the network does not give the complete picture of security of complete network. In this paper we have proposed taxonomy and ontology which may be used to infer impact of various events happening in the network on security status of the network. Vulnerability, Network and Attack are the main taxonomy classes in the ontology. Vulnerability class describes various types of vulnerabilities in the network which may in hardware components like storage devices, computing devices or networks devices. Attack class has many subclasses like Actor class which is entity executing the attack, Goal class describes goal of the attack, Attack mechanism class defines attack methodology, Scope class describes size and utility of the target, Automation level describes the automation level of the attack Evaluation of security status of the network is required for network security situational awareness. Network class has network operating system, users, roles, hardware components and services as its subclasses. Based on this taxonomy ontology has been developed to perceive network security status. Finally a framework, which uses this ontology as knowledgebase has been proposed.
 

The objective of this paper is to explore the current notions of systems and “System of Systems” and establish the case for quantitative characterization of their structural, behavioural and contextual facets that will pave the way for further formal development (mathematical formulation). This is partly driven by stakeholder needs and perspectives and also in response to the necessity to attribute and communicate the properties of a system more succinctly, meaningfully and efficiently. The systematic quantitative characterization framework proposed will endeavor to extend the notion of emergence that allows the definition of appropriate metrics in the context of a number of systems ontologies. The general characteristic and information content of the ontologies relevant to system and system of system will be specified but not developed at this stage. The current supra-system, system and sub-system hierarchy is also explored for the formalisation of a standard notation in order to depict a relative scale and order and avoid the seemingly arbitrary attributions.
 

Many surveillance cameras are using everywhere, the videos or images captured by these cameras are still dumped but they are not processed. Many methods are proposed for tracking and detecting the objects in the videos but we need the meaningful content called semantic content from these videos. Detecting Human activity recognition is quite complex. The proposed method called Semantic Content Extraction (SCE) from videos is used to identify the objects and the events present in the video. This model provides useful methodology for intruder detecting systems which provides the behavior and the activities performed by the intruder. Construction of ontology enhances the spatial and temporal relations between the objects or features extracted. Thus proposed system provides a best way for detecting the intruders, thieves and malpractices happening around us.

Nowadays, our surrounding environment is more and more scattered with various types of sensors. Due to their intrinsic properties and representation formats, they form small islands isolated from each other. In order to increase interoperability and release their full capabilities, we propose to represent devices descriptions including data and service invocation with a common model allowing to compose mashups of heterogeneous sensors. Pushing this paradigm further, we also propose to augment service descriptions with a discovery protocol easing automatic assimilation of knowledge. In this work, we describe the architecture supporting what can be called a Semantic Sensor Web-of-Things. As proof of concept, we apply our proposal to the domain of smart buildings, composing a novel ontology covering heterogeneous sensing, actuation and service invocation. Our architecture also emphasizes on the energetic aspect and is optimized for constrained environments.