20 research outputs found

    Comparative analysis of attack detection methods in Delay Tolerant Network

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    Delay Tolerant Network is a new kind of wireless network which includes Radio Frequency (RF) and acoustic (sonar) technologies. DTN developed for an interplanetary network where the speed of light is slow. DTN is derived from deep space communication. DTN is distinguished as long delay and intermittent connectivity. The Delay Tolerant Network is more vulnerable to different kinds of attacks like flooding attack, blackhole and greyhole attacks, due to limited connectivity. There is no end-to-end connectivity between source & destination in DTN. So that it uses a store, carry and forward mechanism to transfer the data from one node to another node. The Delay Tolerant Network was developed to solve technical problems in the end-to-end network. DTN is becoming more and more important because communication networks are ubiquitous today. It provides automotive communication solutions. DTN is a decentralized and self-managed system with unique network attributes; however, attributes such as high mobility nodes, network uplinks and downlinks, and separate routing can cause network vulnerabilities. These vulnerabilities include the host being compromised, which in turn will bring security risks, because the compromised host may destroy the routing protocol in the network. This article analyses the various types of attack detection methods

    Comparative analysis of attack detection methods in Delay Tolerant Network

    Get PDF
    Delay Tolerant Network is a new kind of wireless network which includes Radio Frequency (RF) and acoustic (sonar) technologies. DTN developed for an interplanetary network where the speed of light is slow. DTN is derived from deep space communication. DTN is distinguished as long delay and intermittent connectivity. The Delay Tolerant Network is more vulnerable to different kinds of attacks like flooding attack, blackhole and greyhole attacks, due to limited connectivity. There is no end-to-end connectivity between source & destination in DTN. So that it uses a store, carry and forward mechanism to transfer the data from one node to another node. The Delay Tolerant Network was developed to solve technical problems in the end-to-end network. DTN is becoming more and more important because communication networks are ubiquitous today. It provides automotive communication solutions. DTN is a decentralized and self-managed system with unique network attributes; however, attributes such as high mobility nodes, network uplinks and downlinks, and separate routing can cause network vulnerabilities. These vulnerabilities include the host being compromised, which in turn will bring security risks, because the compromised host may destroy the routing protocol in the network. This article analyses the various types of attack detection methods

    Erkennung und Vermeidung von Fehlverhalten in fahrzeugbasierten DTNs

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    Delay- and Disruption-Tolerant Networks (DTNs) are a suitable technology for many applications when the network suffers from intermittent connections and significant delays. In current vehicular networks, due to the high mobility of vehicles, the connectivity in vehicular networks can be highly unstable, links may change or break soon after they have been established and the network topology varies significantly depending on time and location. When the density of networked vehicles is low, connectivity is intermittent and with only a few transmission opportunities. This makes forwarding packets very difficult. For the next years, until a high penetration of networked vehicles is realized, delay-tolerant methods are a necessity in vehicular networks, leading to Vehicular DTNs (VDTNs). By implementing a store-carry-forward paradigm, VDTNs can make sure that even under difficult conditions, the network can be used by applications. However, we cannot assume that all vehicles are altruistic in VDTNs. Attackers can penetrate the communication systems of vehicles trying their best to destroy the network. Especially if multiple attackers collude to disrupt the network, the characteristics of VDTNs, without continuous connectivity, make most traditional strategies of detecting attackers infeasible. Additionally, selfish nodes may be reluctant to cooperate considering their profit, and due to hard- or software errors some vehicles cannot send or forward data. Hence, efficient mechanisms to detect malicious nodes in VDTNs are imperative. In this thesis, two classes of Misbehavior Detection Systems (MDSs) are proposed to defend VDTNs against malicious nodes. Both MDSs use encounter records (ERs) as proof to document nodes' behavior during previous contacts. By collecting and securely exchanging ERs, depending on different strategies in different classes of MDSs, a reputation system is built in order to punish bad behavior while encouraging cooperative behavior in the network. With independently operating nodes and asynchronous exchange of observations through ERs, both systems are very well suited for VDTNs, where there will be no continuous, ubiquitous network in the foreseeable future. By evaluating our methods through extensive simulations using different DTN routing protocols and different realistic scenarios, we find that both MDS classes are able to efficiently protect the system with low overhead and prevent malicious nodes from further disrupting the network.In Netzwerken mit zeitweisen Unterbrechungen oder langen Verzögerungen sind Delay- and Disruption-Tolerant Networks (DTNs) eine geeignete Technologie für viele Anwendungen. Die Konnektivität in Fahrzeugnetzen ist bedingt durch die hohe Mobilität und die geringe Verbreitung von netzwerkfähigen Fahrzeugen oft instabil. Bis zur flächendeckenden Verbreitung von netzwerkfähigen Fahrzeugen ist es daher zwingend notwendig auf Methoden des Delay Tolerant Networking zurückzugreifen um die bestmögliche Kommunikation zu gewährleisten. In diesem Zusammenhang wird von Vehicular Delay Tolerant Networks (VDTNs) gesprochen. Durch das Store-Carry-Forward-Prinzip kann ein VDTN Kommunikation für Anwendungen ermöglichen. Allerdings ist davon auszugehen, dass sich nicht alle Fahrzeuge altruistisch verhalten: Angreifer können Fahrzeuge übernehmen und das Netzwerk attackieren oder Knoten sind aus egoistischen Motiven oder auf Grund von Defekten unkooperativ. Verfahren, die Fehlverhalten in stabilen Netzen durch direkte Beobachtung erkennen können, sind in VDTNs nicht anwendbar. Daher sind Methoden, die Fehlverhalten in VDTNs nachweisen können, zwingend erforderlich. In dieser Arbeit werden zwei Klassen von Misbehavior Detection Systems (MDSs) vorgestellt. Beide Systeme basieren auf Encounter Records (ERs): Nach einem Kontakt tauschen zwei Knoten kryptografisch signierte Meta-Informationen zu den erfolgten Datentransfers aus. Diese ERs dienen bei darauffolgenden Kontakten mit anderen Netzwerkteilnehmern als vertrauenswürdiger Nachweis für das Verhalten eines Knotens in der Vergangenheit. Basierend auf der Auswertung gesammelter ERs wird ein Reputationssystem entwickelt, das kooperatives Verhalten belohnt und unkooperatives Verhalten bestraft. Dauerhaft unkooperative Knoten werden aus dem Netzwerk ausgeschlossen. Durch den asynchronen Austausch von Informationen kann jeder Knoten das Verhalten seiner Nachbarn selbstständig und unabhängig evaluieren. Dadurch sind die vorgestellten MDS-Varianten sehr gut für den Einsatz in einem VDTN geeignet. Durch umfangreiche Evaluationen wird gezeigt, dass sich die entwickelten MDS-Verfahren für verschiedene Routingprotokolle und in unterschiedlichen Szenarien anwenden lassen. In allen Fällen ist das MDS in der Lage das System mit geringem Overhead gegen Angreifer zu verteidigen und eine hohe Servicequalität im Netzwerk zu gewährleisten

    A Survey on Machine Learning-based Misbehavior Detection Systems for 5G and Beyond Vehicular Networks

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    Advances in Vehicle-to-Everything (V2X) technology and onboard sensors have significantly accelerated deploying Connected and Automated Vehicles (CAVs). Integrating V2X with 5G has enabled Ultra-Reliable Low Latency Communications (URLLC) to CAVs. However, while communication performance has been enhanced, security and privacy issues have increased. Attacks have become more aggressive, and attackers have become more strategic. Public Key Infrastructure (PKI) proposed by standardization bodies cannot solely defend against these attacks. Thus, in complementary of that, sophisticated systems should be designed to detect such attacks and attackers. Machine Learning (ML) has recently emerged as a key enabler to secure future roads. Various V2X Misbehavior Detection Systems (MDSs) have adopted this paradigm. However, analyzing these systems is a research gap, and developing effective ML-based MDSs is still an open issue. To this end, this paper comprehensively surveys and classifies ML-based MDSs as well as discusses and analyses them from security and ML perspectives. It also provides some learned lessons and recommendations for guiding the development, validation, and deployment of ML-based MDSs. Finally, this paper highlighted open research and standardization issues with some future directions

    Analysis of cyber risk and associated concentration of research (ACR)² in the security of vehicular edge clouds

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    Intelligent Transportation Systems (ITS) is a rapidly growing research space with many issues and challenges. One of the major concerns is to successfully integrate connected technologies, such as cloud infrastructure and edge cloud, into ITS. Security has been identified as one of the greatest challenges for the ITS, and security measures require consideration from design to implementation. This work focuses on providing an analysis of cyber risk and associated concentration of research (ACR2). The introduction of ACR2 approach can be used to consider research challenges in VEC and open up further investigation into those threats that are important but under-researched. That is, the approach can identify very high or high risk areas that have a low research concentration. In this way, this research can lay the foundations for the development of further work in securing the future of ITS

    A Taxonomy on Misbehaving Nodes in Delay Tolerant Networks

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    Delay Tolerant Networks (DTNs) are type of Intermittently Connected Networks (ICNs) featured by long delay, intermittent connectivity, asymmetric data rates and high error rates. DTNs have been primarily developed for InterPlanetary Networks (IPNs), however, have shown promising potential in challenged networks i.e. DakNet, ZebraNet, KioskNet and WiderNet. Due to unique nature of intermittent connectivity and long delay, DTNs face challenges in routing, key management, privacy, fragmentation and misbehaving nodes. Here, misbehaving nodes i.e. malicious and selfish nodes launch various attacks including flood, packet drop and fake packets attack, inevitably overuse scarce resources (e.g., buffer and bandwidth) in DTNs. The focus of this survey is on a review of misbehaving node attacks, and detection algorithms. We firstly classify various of attacks depending on the type of misbehaving nodes. Then, detection algorithms for these misbehaving nodes are categorized depending on preventive and detective based features. The panoramic view on misbehaving nodes and detection algorithms are further analyzed, evaluated mathematically through a number of performance metrics. Future directions guiding this topic are also presented

    A Security and Efficient Routing Scheme with Misbehavior Detection in Delay-Tolerant Networks

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    Due to the unique network characteristics, the security and efficient routing in DTNs are considered as two great challenges. In this paper, we design a security and efficient routing scheme, called SER, which integrates the routing decision and the attacks detection mechanisms. In SER scheme, each DTNs node locally maintains a one-dimensional vector table to record the summary information about the contact with other nodes and the trust degree of other nodes. To obtain the global status and the contact relationship among all nodes, the trusted routing table consisting of vectors of all nodes is built in each DTNs node. The method for detecting malicious nodes and selfish nodes is proposed, which exploits the global summary information to analyze the history forwarding behavior of node and judge whether it is a malicious node or selfish node. The routing decision method is proposed based on trust degree of forwarding messages between nodes, which adopts trust degree as relay node selection strategy. Simulation results show that compared with existing schemes SER scheme could detect the attacks behavior of malicious nodes and selfish nodes, at the same time, with higher delivery rate and lower average delivery delay

    Modelling of the Electric Vehicle Charging Infrastructure as Cyber Physical Power Systems: A Review on Components, Standards, Vulnerabilities and Attacks

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    The increasing number of electric vehicles (EVs) has led to the growing need to establish EV charging infrastructures (EVCIs) with fast charging capabilities to reduce congestion at the EV charging stations (EVCS) and also provide alternative solutions for EV owners without residential charging facilities. The EV charging stations are broadly classified based on i) where the charging equipment is located - on-board and off-board charging stations, and ii) the type of current and power levels - AC and DC charging stations. The DC charging stations are further classified into fast and extreme fast charging stations. This article focuses mainly on several components that model the EVCI as a cyberphysical system (CPS)
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