Biblio
In military operations, Commander's Intent describes the desired end state and purpose of the operation, expressed in a concise and clear manner. Command by intent is a paradigm that empowers subordinate units to exercise measured initiative to meet mission goals and accept prudent risk within commander's intent. It improves agility of military operations by allowing exploitation of local opportunities without an explicit directive from the commander to do so. This paper discusses what the paradigm entails in terms of architectural decisions for data fusion systems tasked with real-time information collection to satisfy operational mission goals. In our system, information needs of decisions are expressed at a high level, and shared among relevant nodes. The selected nodes, then, jointly operate to meet mission information needs by forwarding and caching relevant data without explicit directives regarding the objects to fetch and sources to contact. A preliminary evaluation of the system is presented using a target tracking application, set in the context of a NATO-based mission scenario, called Anglova. Evaluation results show that delegating some decision authority to the data fusion system (in terms of objects to fetch and sources to contact) allows it to save more network resources, while also increasing mission success rate. The system is therefore particularly well-suited to operation in partially denied or contested environments, where resource bottlenecks caused by adversarial activity impair one's ability to collect real-time information for mission-critical decision making.
Botnets are a growing threat to the security of data and services on a global level. They exploit vulnerabilities in networks and host machines to harvest sensitive information, or make use of network resources such as memory or bandwidth in cyber-crime campaigns. Bot programs by nature are largely automated and systematic, and this is often used to detect them. In this paper, we extend upon existing work in this area by proposing a network event correlation method to produce graphs of flows generated by botnets, outlining the implementation and functionality of this approach. We also show how this method can be combined with statistical flow-based analysis to provide a descriptive chain of events, and test on public datasets with an overall success rate of 94.1%.
Mobile ad hoc networks (MANETs) play a significant role for communication whenever infrastructure is not available. In MANET, the group communication-based applications use the multicast routing protocol, where there is a single sender node and a group of receiver nodes. The benefits of multicast routing protocols are the capability to reduce the communication costs and saving the network resources by reproduction of the message over a shared network. The security is the main concern for multicast routing protocol in MANET, as it includes large number of participants. The security issues become more rigorous in a multicast communication due to its high variedness and routing difficulty. In this paper, we consider the internal attack, namely Multicast Announcement Packet Fabrication Attack on PUMA (Protocol for Unified Multicasting through Announcements). We proposed the security approach to detect the attacks as multicast activity-based overhearing technique, i.e., traffic analysis-based detection method with a unique key value. The performance analysis, shows an improved network performance of proposed approach over PUMA.
Software Defined Networking (SDN) is an emerging paradigm that changes the way networks are managed by separating the control plane from data plane and making networks programmable. The separation brings about flexibility, automation, orchestration and offers savings in both capital and operational expenditure. Despite all the advantages offered by SDN it introduces new threats that did not exist before or were harder to exploit in traditional networks, making network penetration potentially easier. One of the key threat to SDN is the authentication and authorisation of network applications that control network behaviour (unlike the traditional network where network devices like routers and switches are autonomous and run proprietary software and protocols to control the network). This paper proposes a mechanism that helps the control layer authenticate network applications and set authorisation permissions that constrict manipulation of network resources.
Distributed Denial of Service (DDoS) attack is a congestion-based attack that makes both the network and host-based resources unavailable for legitimate users, sending flooding attack packets to the victim's resources. The non-existence of predefined rules to correctly identify the genuine network flow made the task of DDoS attack detection very difficult. In this paper, a combination of unsupervised data mining techniques as intrusion detection system are introduced. The entropy concept in term of windowing the incoming packets is applied with data mining technique using Clustering Using Representative (CURE) as cluster analysis to detect the DDoS attack in network flow. The data is mainly collected from DARPA2000, CAIDA2007 and CAIDA2008 datasets. The proposed approach has been evaluated and compared with several existing approaches in terms of accuracy, false alarm rate, detection rate, F. measure and Phi coefficient. Results indicates the superiority of the proposed approach with four out five detected phases, more than 99% accuracy rate 96.29% detection rate, around 0% false alarm rate 97.98% F-measure, and 97.98% Phi coefficient.
Cloud-based communications system is now widely used in many application fields such as medicine, security, environment protection, etc. Its use is being extended to the most demanding services like multimedia delivery. However, there are a lot of constraints when cloud-based sensor networks use the standard IEEE 802.15.3 or IEEE 802.15.4 technologies. This paper proposes a channel characterization scheme combined to a cross-layer admission control in dynamic cloud-based multimedia sensor networks to share the network resources among any two nodes. The analysis shows the behavior of two nodes using different network access technologies and the channel effects for each technology. Moreover, the existence of optimal node arrival rates in order to improve the usage of dynamic admission control when network resources are used is also shown. An extensive simulation study was performed to evaluate and validate the efficiency of the proposed dynamic admission control for cloud-based multimedia sensor networks.