Network Situation Awareness Research Articles

Network Intrusion Detection Based on Directed Acyclic Graph and Belief Rule Base

Intrusion detection is very important for network situation awareness. While a few methods have been proposed to detect network intrusion, they cannot directly and effectively utilize semi-quantitative information consisting of expert knowledge and quantitative data. Hence, this paper proposes a new detection model based on a directed acyclic graph (DAG) and a belief rule base (BRB). In the proposed model, called DAG-BRB, the DAG is employed to construct a multi-layered BRB model that can avoid explosion of combinations of rule number because of a large number of types of intrusion. To obtain the optimal parameters of the DAG-BRB model, an improved constraint covariance matrix adaption evolution strategy (CMA-ES) is developed that can effectively solve the constraint problem in the BRB. A case study was used to test the efficiency of the proposed DAG-BRB. The results showed that compared with other detection models, the DAG-BRB model has a higher detection rate and can be used in real networks.

Improving Disturbance Management with Combined Electricity and Mobile Network Situation Awareness System

This paper presents a new method to improve the disturbance management of electricity networks and mobile networks with a situation awareness system that was developed in this study. The system is based on combining the disturbance information from electricity and mobile networks. Both of the networks provide useful information for disturbance management: electricity outage areas from the electricity network systems and coverage outage areas from the cellular network operators. The outage information from an electricity network is received through the Distribution Management System (DMS) service and combined with customer identification codes to find out whether mobile network base stations lack electricity. This information is combined with operational mobile network coverage areas calculated beforehand with an empirical Okumura-Hata path loss model in order to visualize coverage outage areas. A situation awareness system that combines these parts provides new disturbance management insights and shows the disturbances of both networks with one glance. Thus, the restoration plans for both networks can be sped up and critical areas can be more easily prioritized since a clear visual presentation of the situation is easy to comprehend. Therefore, this new method improves the resilience of society, especially during major disturbances.

Situation awareness and computational intelligence in opportunistic networks to support the data transmission of urban sensing applications

Smart cities can be seen as large-scale Cyber-Physical Systems with sensors monitoring cyber and physical indicators and with actuators dynamically changing the complex urban environment in some way. In this context, urban sensing is a new paradigm that exploits human-carried or vehicle-mounted sensors to ubiquitously collect data to provide a holistic view of the city. A challenge in this scenario is the transmission of sensed data in situations where the networking infrastructure is intermittent or unavailable. This paper outlines our research into an engine that uses opportunistic networks to support the data transmission of urban sensing applications. It applies situation awareness and computational intelligence approaches to perform routing, adaptation, and decision-making procedures. We carried out simulations within a simulated environment that showed our engine had 12% less overhead than other compared approaches.

SWN: An SDN based framework for carrier grade Wi-Fi networks

With the rapid growth of mobile data traffic and vast traffic offloaded from cellular network, Wi-Fi has been considered as an essential component to cope with the tremendous growth of mobile data traffic. Although operators have deployed a lot of carrier grade Wi-Fi networks, but there are still a multitude of arrears for nowadays Wi-Fi networks, such as supporting seamless handover between APs, automatic network access and unified authentication, etc. In this paper, we propose an SDN based carrier grade Wi-Fi network framework, namely SWN. The key conceptual contribution of SWN is a principled refactoring of Wi-Fi networks into control and data planes. The control plane has a centralized global view of the whole network, can perceive the underlying network state by network situation awareness (NAS) technique, and bundles the perceived information and network management operations into northbound Application Programming Interface (API) for upper applications. In the data plane, we construct software access point (SAP) to abstract the connection between user equipment (UE) and access point (AP). Network operators can design network applications by utilizing these APIs and the SAP abstraction to configure and manage the whole network, which makes carrier grade Wi-Fi networks more flexible, user-friendly, and scalable.

Immune-Based Systems on Network Security Situation Awareness and Risk Prediction Model

In this paper, the process of the developments and changes of the network intrusion behaviors were analyzed. An improved epidemic spreading model was proposed to study the mechanisms of aggressive behaviors spreading, to predict the future course of an outbreak and to evaluate strategies to control a network epidemic. Based on Artificial Immune Systems, the concepts and formal definitions of immune cells were given. And in this paper, the forecasting algorithm based on Markov chain theory was proposed to improve the precision of network risk forecasting. The data of the Memory cells were analyzed directly and kinds of state-spaces were formed, which can be used to predict the risk of network situation by analyzing the cells status and the classification of optimal state. Experimental results show that the proposed model has the features of real-time processing for network situation awareness.

On the Relevance of Using Bayesian Belief Networks in Wireless Sensor Networks Situation Recognition

Achieving situation recognition in ubiquitous sensor networks (USNs) is an important issue that has been poorly addressed by both the research and practitioner communities. This paper describes some steps taken to address this issue by effecting USN middleware intelligence using an emerging situation awareness (ESA) technology. We propose a situation recognition framework where temporal probabilistic reasoning is used to derive and emerge situation awareness in ubiquitous sensor networks. Using data collected from an outdoor environment monitoring in the city of Cape Town, we illustrate the use of the ESA technology in terms of sensor system operating conditions and environmental situation recognition.

Assessing Situation Awareness in Networks of Cooperating Entities: A Mathematical Approach

Assessing Situation Awareness in Networks of Cooperating Entities: A Mathematical Approach

Dynamic Policy-Based Network Management for a Secure Coalition Environment

This article reports the latest results of an R&D effort to develop a prototype implementation of a dynamic policy-based network management (PBNM) system that can be used to configure and manage a secure network for a coalition environment across an unsecured wide area network. The prototype, based on a distributed architecture, includes capabilities for policy creation and management, dynamic policy negotiation, and dynamic policy provisioning. The policy negotiation facilitates the rapid deployment of a coalition network while the dynamic policy provisioning automates the configuration and management of network services including firewalls, virtual private network connections, routing, quality of service (QoS), and domain name services. Such a PBNM system enhances an organization's ability to react to network incidents identified by a network situational awareness assessment. Although the focus of the current research is a military coalition environment, the system can be used in any distributed enterprise or collaborative environment