1,130 research outputs found
Secure Group Communication in Delay Tolerant Mobile Ad-Hoc Network
Delay-tolerant networks (DTNs) are well-known for delivering various types of information from different senders in a multicast manner, both in centralised and decentralised networks. Wireless mobile nodes form small networks in which one or more senders transmit data to one or more destinations through intermediate nodes. DTN routing protocols differ from traditional wireless routing protocols. There are security threats in DTNs, such as blackhole attackers dropping data, jamming attacks consuming bandwidth, and Vampire attacks depleting battery power and available bandwidth. This paper proposes a prevention scheme to detect and mitigate all three types of attackers in multicast communication. These attackers can impact performance by generating false replies, flooding with redundant information, and wasting communication power. The primary focus of this paper is on security issues related to DTN routing protocols. In order to counter malicious nodes, a blacklist is maintained, and if a neighbour identifies a node as malicious, it excludes packets from that node. Meanwhile, the neighbour continues sending packets to the malicious node, except for broadcast packets, which are dropped. If a node is found to forward no packets or only some packets by all its neighbours, any reply it gives to route requests is disregarded, and any request it initiates is ignored. Successful data reception at the destination indicates that hop-based data delivery maintains a record of successful transmissions. The proposed security scheme demonstrates improved performance
Survey and Review on Various Topology and Geographical based Routing Protocol Parameters to Ensure the QOS Parameters of VANET
Vehicular Ad Hoc Network (VANET) is a type of wireless network that allows communication between vehicles and infrastructure. One of the critical considerations in VANET is Quality of Service (QoS) parameters, which determine the network's performance. The effective management of QoS parameters is essential for VANET's reliable and efficient operation. In this research paper, we aim to explore topology-based and geographical-based routing protocol parameters to ensure QoS parameters in VANET. The former uses the network topology to make routing decisions, while the latter uses the location information of vehicles. We will first provide an overview of VANET and QoS parameters. Then, we will delve into the key parameters of topology-based and geographical-based routing protocols and how they affect QoS. We will also survey and review the existing routing protocols and parameter values used in these protocols. The findings of this research paper will provide insights into the effective management of QoS parameters in VANET and contribute to the development of more efficient routing protocols
Stable dynamic feedback-based predictive clustering protocol for vehicular ad hoc networks
Scalability presents a significant challenge in vehicular communication, particularly when there is no hierarchical structure in place to manage the increasing number of vehicles. As the number of vehicles increases, they may encounter the broadcast storm problem, which can cause network congestion and reduce communication efficiency. Clustering can solve these issues, but due to high vehicle mobility, clustering in vehicular ad hoc networks (VANET) suffers from stability issues. Existing clustering algorithms are optimized for either cluster head or member, and for highways or intersections. The lack of intelligent use of mobility parameters like velocity, acceleration, direction, position, distance, degree of vehicles, and movement at intersections, also contributes to cluster stability problems. A dynamic clustering algorithm that efficiently utilizes all mobility parameters can resolve these issues in VANETs.
To provide higher stability in VANET clustering, a novel robust and dynamic mobility-based clustering algorithm called junction-based clustering protocol for VANET (JCV) is proposed in this dissertation. Unlike previous studies, JCV takes into account position, distance, movement at the junction, degree of a vehicle, and time spent on the road to select the cluster head (CH). JCV considers transmission range, the moving direction of the vehicle at the next junction, and vehicle density in the creation of a cluster. JCV's performance is compared with two existing VANET clustering protocols in terms of the average cluster head duration, the average cluster member (CM) duration, the average number of cluster head changes, and the percentage of vehicles participating in the clustering process, etc. To evaluate the performance of JCV, we developed a new cloud-based VANET simulator (CVANETSIM). The simulation results show that JCV outperforms the existing algorithms and achieves better stability in terms of the average CH duration (4%), the average CM duration (8%), the number of CM (6%), the ratio of CM (22%), the average CH change rate (14%), the number of CH (10%), the number of non-cluster vehicles (7%), and clustering overhead (35%).
The dissertation also introduced a stable dynamic feedback-based predictive clustering (SDPC) protocol for VANET, which ensures cluster stability in both highway and intersection scenarios, irrespective of the road topology. SDPC considers vehicle relative velocity, acceleration, position, distance, transmission range, moving direction at the intersection, and vehicle density to create a cluster. The cluster head is selected based on the future construction of the road, considering relative distance, movement at the intersection, degree of vehicles, majority-vehicle, and probable cluster head duration. The performance of SDPC is compared with four existing VANET clustering algorithms in various road topologies, in terms of the average cluster head change rate, duration of the cluster head, duration of the cluster member, and the clustering overhead. The simulation results show that SDPC outperforms existing algorithms, achieving better clustering stability in terms of the average CH change rate (50%), the average CH duration (15%), the average CM duration (6%), and the clustering overhead (35%)
A Novel Method of Enhancing Security Solutions and Energy Efficiency of IoT Protocols
Mobile Ad-hoc Networks (MANETβs) are wireless networks that are capable of operating without any fixed infrastructure. MANET routing protocols must adhere to strict secrecy, integrity, availability and non-repudiation criteria. In MANETs, attacks are roughly categorised into two types: active and passive. An active attack attempts to modify or remove data being transferred across a network. On the other hand, passive attack does not modify or erase the data being sent over the network. The majority of routing protocols for MANETs were built with little regard for security and are therefore susceptible to a variety of assaults. Routing technologies such as AODV and dynamic source routing are quite common. Both however are susceptible to a variety of network layer attacks, including black holes, wormholes, rushing, byzantine, information disclosure. The mobility of the nodes and the open architecture in which the nodes are free to join or leave the network keep changing the topology of the network. The routing in such scenarios becomes a challenging task since it has to take into account the constraints of resources of mobile devices. In this an analysis of these protocols indicates that, though proactive routing protocols maintain a route to every destination and have low latency, they suffer from high routing overheads and inability to keep up with the dynamic topology in a large sized network. The reactive routing protocols in contrast have low routing overheads, better throughput and higher packet delivery ratio. AODVACO-PSO-DHKE Methodology boosts throughput by 10% while reducing routing overhead by 7%, latency by 8% and energy consumption by 5%. To avoid nodes always being on, a duty cycle procedure that's also paired with the hybrid method is used ACO-FDR PSO is applied to a 100-node network and NS-3 is used to measure various metrics such as throughput, latency, overhead, energy consumption and packet delivery ratio
Analysis of Behavioral Characteristics of Jammers to Detect Malicious Nodes in Mobile ADHOC Networks
Wireless ADHOC Networks are used to establish a wireless connection between two computing devices without the need for a Wi-Fi access point or router. This network is decentralized and uses omnidirectional communication media, which makes it more vulnerable to certain types of attacks compared to wired networks. Jamming attacks, a subset of denial-of-service (DoS) attacks, involve malicious nodes that intentionally interfere with the network, blocking legitimate communication. To address this issue, the proposed method analyzes various characteristics of nodes, such as packets sent, received, and dropped, at each node. Using the packet delivery ratio and packet drop ratio, the method detects jamming nodes from normal nodes, improving network performance. The network is simulated in NS2 environment
Technologies of information transmission and processing
Π‘Π±ΠΎΡΠ½ΠΈΠΊ ΡΠΎΠ΄Π΅ΡΠΆΠΈΡ ΡΡΠ°ΡΡΠΈ, ΡΠ΅ΠΌΠ°ΡΠΈΠΊΠ° ΠΊΠΎΡΠΎΡΡΡ
ΠΏΠΎΡΠ²ΡΡΠ΅Π½Π° Π½Π°ΡΡΠ½ΠΎ-ΡΠ΅ΠΎΡΠ΅ΡΠΈΡΠ΅ΡΠΊΠΈΠΌ ΡΠ°Π·ΡΠ°Π±ΠΎΡΠΊΠ°ΠΌ Π² ΠΎΠ±Π»Π°ΡΡΠΈ ΡΠ΅ΡΠ΅ΠΉ ΡΠ΅Π»Π΅ΠΊΠΎΠΌΠΌΡΠ½ΠΈΠΊΠ°ΡΠΈΠΉ, ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΎΠ½Π½ΠΎΠΉ Π±Π΅Π·ΠΎΠΏΠ°ΡΠ½ΠΎΡΡΠΈ, ΡΠ΅Ρ
Π½ΠΎΠ»ΠΎΠ³ΠΈΠΉ ΠΏΠ΅ΡΠ΅Π΄Π°ΡΠΈ ΠΈ ΠΎΠ±ΡΠ°Π±ΠΎΡΠΊΠΈ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΈ. ΠΡΠ΅Π΄Π½Π°Π·Π½Π°ΡΠ΅Π½ Π΄Π»Ρ Π½Π°ΡΡΠ½ΡΡ
ΡΠΎΡΡΡΠ΄Π½ΠΈΠΊΠΎΠ² Π² ΠΎΠ±Π»Π°ΡΡΠΈ ΠΈΠ½ΡΠΎΠΊΠΎΠΌΠΌΡΠ½ΠΈΠΊΠ°ΡΠΈΠΉ, ΠΏΡΠ΅ΠΏΠΎΠ΄Π°Π²Π°ΡΠ΅Π»Π΅ΠΉ, Π°ΡΠΏΠΈΡΠ°Π½ΡΠΎΠ², ΠΌΠ°Π³ΠΈΡΡΡΠ°Π½ΡΠΎΠ² ΠΈ ΡΡΡΠ΄Π΅Π½ΡΠΎΠ² ΡΠ΅Ρ
Π½ΠΈΡΠ΅ΡΠΊΠΈΡ
Π²ΡΠ·ΠΎΠ²
Towards Reliable Multi-Path Routing : An Integrated Cooperation Model for Drones
Ad-hoc networks have evolved into a vital wireless communication component by offering an adaptable infrastructure suitable for various scenarios in our increasingly interconnected and mobile world. However, this adaptability also exposes these networks to security challenges, given their dynamic nature, where nodes frequently join and leave. This dynamism is advantageous but presents resource constraints and vulnerability to malicious nodes, impacting data transmission reliability and security.
In this context, this article explores the development of a secure routing protocol for Ad-hoc networks based on a cooperation reinforcement model to reduce the degradation of routing performance. We leverage the reputation of nodes as an additional security layer to monitor their behavior and evaluate their level of reliability. To exemplify our solution, we focus on drone fleets (UAVs) as a pertinent case study. Drones frequently operate in dynamic, challenging environments, relying on Ad-hoc networks for communication. They serve as an apt illustration, highlighting the complexities of the issue and the efficacy of our proposed remedy. The simulation results show the effectiveness of our proposed solution compared to stae-of-the-artsolutions
Applications
Volume 3 describes how resource-aware machine learning methods and techniques are used to successfully solve real-world problems. The book provides numerous specific application examples: in health and medicine for risk modelling, diagnosis, and treatment selection for diseases in electronics, steel production and milling for quality control during manufacturing processes in traffic, logistics for smart cities and for mobile communications
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