Detecting malicious behavior in a vehicular DTN for public transportation

Guo, Yinghui; Schildt, Sebastian; Pögel, Tobias; Wolf, Lars

doi:10.1109/giis.2013.6684378

Cited by 14 publications

(10 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For instance, Pham and Fdida [16] suggested that DTNs could aid in the distribution of news within cities through the use of fixed nodes. For another instance, the detection of malicious behavior through the use of a Misbehavior Detection System (MDS) was proposed to improve network performance, and it had been discussed in vehicular DTNs of metropolitan areas by Guo et al [17]. There are some common traits between these described applications, such as node movement trajectory and regular moving.…”

Section: Mobile Nodes and Fixed Sink Stations In City Environmentsmentioning

confidence: 99%

GTDM: A DTN Routing on Noncooperative Game Theory in a City Environment

Lin

Zhou

et al. 2015

Journal of Sensors

View full text Add to dashboard Cite

The performance of delay tolerant networks (DTNs) can be influenced by movement model in different application environments. The existing routing algorithms of DTNs do not meet the current city environments due to the large differences in node densities, social characteristics, and limited energy. The key indicators of DTNs such as success delivery ratio, average delivery latency, network lifetime, and network overhead ratio can influence the performances of civil DTNs applications. Aiming to improve the key indicators of DTNs in city environments, this paper presents a fixed sink station based structure and a more proper routing algorithm named Game Theory Based Decision Making (GTDM). GTDM shows decision-making process for neighborhood selection and packet delivering strategy which is based on the noncooperative game theory method and city environment characteristics. GTDM performance is evaluated using numerical simulations under Working Day Movement (WDM) model and the results suggested that GTDM outperforms other traditional DTNs routing approaches, such as Epidemic and Prophet algorithms.

show abstract

Section: Mobile Nodes and Fixed Sink Stations In City Environmentsmentioning

confidence: 99%

GTDM: A DTN Routing on Noncooperative Game Theory in a City Environment

Lin

Zhou

et al. 2015

Journal of Sensors

View full text Add to dashboard Cite

show abstract

“…Delay Tolerant Networks (DTNs) are infrastructure-less networks, where no end-to-end route exists and disconnection of network occurs frequently [1]- [7]. DTNs are primarily developed for Interplanetary Networks (IPNs) [8], however, also applicable in emerging networks such as Vehicular Ad-hoc Networks (VANETs) [9], Underwater Wireless Sensor Networks (UWSNs) [10] and disaster applications [11]. For example, some of these specific applications of DTNs are KioskNet [12], DakNet [13], ZebraNet [14] and WiderNet [15].…”

Section: Introductionmentioning

confidence: 99%

A taxonomy on misbehaving nodes in delay tolerant networks

Khalid

Ullah

Ahmed

et al. 2018

Computers & Security

View full text Add to dashboard Cite

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.

show abstract

“…They first submit their tickets and then reveal their contact history to one another. Similarly, Guo et al [24,25] proposed Misbehavior Detection System (MDS) that helps in finding malicious nodes in vehicular DTNs. They also used the concept of encounter tickets similar to [23].…”

Section: Related Workmentioning

confidence: 98%

“…They also used the concept of encounter tickets similar to [23]. The schemes [23][24][25] detect the presence of malicious nodes in the network. However, these schemes would not be able to detect the isolator from the network because isolator neither drops nor forwards other nodes messages.…”

Section: Related Workmentioning

confidence: 99%