Intrusion Detection in Mobile Ad Hoc Networks Using Classification Algorithms

In this paper we present the design and evaluation of intrusion detection models for MANETs using supervised classification algorithms. Specifically, we evaluate the performance of the MultiLayer Perceptron (MLP), the Linear classifier, the Gaussian Mixture Model (GMM), the Naive Bayes classifier and the Support Vector Machine (SVM). The performance of the classification algorithms is evaluated under different traffic conditions and mobility patterns for the Black Hole, Forging, Packet Dropping, and Flooding attacks. The results indicate that Support Vector Machines exhibit high accuracy for almost all simulated attacks and that Packet Dropping is the hardest attack to detect.Comment: 12 pages, 7 figures, presented at MedHocNet 200

Exploring The Dynamics Of Change In European Municipal Settings: A Case Study Of Two Research And Development Projects

Transformational initiatives concerning electronic forms of governance occur increasingly often in our time. However most of them are characterised by lack of deeper understanding of the dynamics and possibilities of organizational and technological change in governmental settings. This paper endeavours an investigation of the undercurrent processes of organizational and technological change in the field of electronic governance. We base our research on the interpretive analysis of research data that were gathered through participant observation of two European research and development e-Government projects. In addition some more general implications are offered, based on our case studies, concerning the transformation of business processes, the changes in analysis, design and implementation of IS for e-Government, and electronic governance strategies. We believe that these implications can prove useful in both analyses and implementations of electronic governance

Detecting unauthorized and compromised nodes in mobile ad hoc networks

Security of mobile ad-hoc networks (MANET) has become a more sophisticated problem than security in other networks, due to the open nature and the lack of infrastructure of such networks. In this paper, the security challenges in intrusion detection and authentication are identified and the different types of attacks are discussed. We propose a two-phase detection procedure of nodes that are not authorized for specific services and nodes that have been compromised during their operation in MANET. The detection framework is enabled with the main operations of ad-hoc networking, which are found at the link and network layers. The proposed framework is based on zero knowledge techniques, which are presented through proofs

LIDF: Layered intrusion detection framework for ad-hoc networks

As ad-hoc networks have different characteristics from a wired network, the intrusion detection techniques used for wired networks are no longer sufficient and effective when adapted directly to a wireless ad-hoc network. In this article, first τhe security challenges in intrusion detection for ad-hoc networks are identified and the related work for anomaly detection is discussed. We then propose a layered intrusion detection framework, which consists of collection, detection and alert modules that are handled by local agents. The collection, detection and alert modules are uniquely enabled with the main operations of ad-hoc networking, which are found at the OSI link and network layers. The proposed modules are based on interpolating polynomials and linear threshold schemes. An experimental evaluation of these modules shows their efficiency for several attack scenarios, such as route logic compromise, traffic patterns distortion and denial of service attacks

Fast and reliable LoRa-based data transmissions

LoRaWAN is a recently proposed MAC layer protocol which manages communications between LoRa-based gate-ways and end-devices. It has attracted much scientific attention due its physical layer characteristics, but mainly due to its versatile configuration parameters. However, it is known that LoRaWAN-based transmissions suffer from extensive collisions due to the unregulated access to the medium. For this reason, various techniques that alleviate the burst of collisions have been proposed in the literature. In this paper, we deal with the problem of fast data delivery in LoRa-based networks. We model a network where transmissions follow a Poisson process. We compute the average packet success probability per Spreading Factor (SF) assuming orthogonal transmissions. We, then, formulate an SF optimization problem to maximize the success probability given an amount of data per node and a maximum data collection time window. We show - both theoretically and using simulations - that the overall success probability can be improved by approximately 100% using optimal SF assignments. We validate our findings using a 10-node testbed and extensive experiments. Despite that experiments reveal the existence of inter-SF interference, our solution still provides the best performance compared to other LoRaWAN configurations

Layered security design for mobile ad hoc networks

When security of a given network architecture is not properly designed from the beginning, it is difficult to preserve confidentiality, authenticity, integrity and non-repudiation in practical networks. Unlike traditional mobile wireless networks, ad hoc networks rely on individual nodes to keep all the necessary interconnections alive. In this article we investigate the principal security issues for protecting mobile ad hoc networks at the data link and network layers. The security requirements for these two layers are identified and the design criteria for creating secure ad hoc networks using multiple lines of defense against malicious attacks are discussed