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The vehicular ad hoc network (VANET) is a method through which Intelligent Transportation Systems (ITS) have become important for the benefit of daily life. Real-time detection of all forms of attacks, including hybrid DoS attacks in IEEE 802.11p, has become an urgent issue for VANET. This is due to sporadic real-time exchange of safety and road em...
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The purpose of this study was to review synchronous and asynchronous e-learning at Light International School. The study found out that the school as a hybrid or blended model e-learning model. The school used both synchronous e-learning which was done through Zoom Cloud meetings and asynchronous e-learning using Firefly Learning Management System...
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... Gateways acting as Fog devices in this attack could be compromised or taken out and replaced with fraudulent ones. 13 Customers of Star Bar or KFC, for instance, connecting to attacker access points that display false SSIDs as public real ones. Once the attackers take over the gateways, the victims' private communications will be intercepted. ...
In fog computing, the management, measurement, configuration, control, communication, and storage tasks are carried out collaboratively by one or more near‐user or end users. Fog computing is widely utilized in major application domains like centralized fog utilized in a shopping complex (UXFog), agriculture domain (FoAgro), health‐care domain (MediFog), vehicle parking system, and energy Lattices. The execution of fog computing at the system's edge provides the elevated quality of service (QoS), promotes area mindfulness, and minimal dormancy for the continuous and online streaming application areas. Fog networking is extremely concerned about wireless system security due to the prevalence of wireless communication in fog computing. Sniffer attacks, Jamming assaults, and several other intrusions are considered examples of security issues. While considering network storage issues, factors like interaction management, dynamic workload, and low dormancy are the most challenging aspects of designing the network model. Thus, privacy and security issues are crucial while designing the network model, accomplished through intrusion detection, access control and authentication methods. Therefore, the security analysis of fog computing based on authentication, access control and intrusion detection mechanisms are analyzed in this research to design a novel technique with enhanced security and privacy features for sharing and accessing information.
... where PS i (Predicated Share) is is provided by : Pseudocode communicates [Ers20] via the interpolation order n nodes [Nob+19] .In order to determine whether or not the nodes will be selected for data transfer, the final key result, which is established using E-Lagrange's technique, must be determined. One essential generating strategy involves the use of both a numerator and a denominator in order to function properly.In the numerator [RHS18], the network IDs of the vehicles that are still present during the iteration are used to calculate the number of iterations. ...
... WMANet routing protocols are uncomplicated, which makes them more vulnerable to such attacks compared with the routing protocols of framework-based networks. A type of common routing attacks on WMANets is the packet drop attack (PDA) [2]. A PDA functions as the base for launching different attacks, such as a distributed denial of service attack and a sinkhole attack, which result in numerous hubs attempting to route their traffic to the malicious hub. ...
Network security and energy consumption are deemed to be two important components of wireless and mobile ad hoc networks (WMANets). There are various routing attacks which harm Ad Hoc networks. This is because of the unse-cure wireless communication, resource constrained capabilities and dynamic topology. In order to cope with these issues, Ad Hoc On-Demand Distance Vector (AODV) routing protocol can be used to remain the normal networks functional-ity and to adjust data transmission by defending the networks against black hole attacks. The proposed system, in this work, identifies the optimal route from sender to collector, prioritizing the number of jumps, the battery life, and security, which are fundamental prerequisites. Researches have proposed various plans for detecting the shortest route, as well as ensuring energy conversions and defense against threats and attacks. In this regard, the packet drop attack is one of the most destructive attack against WMANet communication and hence merits special attention. This type of attack may allow the attacker to take control of the attacked hubs, which may lost packets or transmitted information via a wrong route during the packets journey from a source hub to a target one. Hence, a new routing protocol method has been proposed in this study. It applies the concept of energy saving systems to conserve energy that is not required by the system. The proposed method for energy aware detection and prevention of packet drop attacks in mobile ad hoc networks is termed the Ad Hoc On-Demand and Distance Vector-Packet Drop Battling Mechanism (AODV-PDBM). Keywords: Wireless and mobile ad hoc networks (WMANet); packet drop attack (PDA); ad hoc on-demand distance vector (AODV); dynamic source routing (DSR); packet drop battling mechanism (PDBM)
... e GL10 object with relevant drawing parameters is configured for drawing. Finally, in the onDrawFrame method of the renderer class inherited from GLSurfaceView.Renderer, all virtual objects are traversed and drawn one by one at the designated position in the frustum, so as to be superimposed and displayed on the real picture of the mobile phone camera to realize virtual and real fusion [23]. ...
It aims to improve the degree of visualization of building data, ensure the ability of intelligent detection, and effectively solve the problems encountered in building data processing. Convolutional neural network and augmented reality technology are adopted, and a building visualization model based on convolutional neural network and augmented reality is proposed. The performance of the proposed algorithm is further confirmed by performance verification on public datasets. It is found that the building target detection model based on convolutional neural network and augmented reality has obvious advantages in algorithm complexity and recognition accuracy. It is 25 percent more accurate than the latest model. The model can make full use of mobile computing resources, avoid network delay and dependence, and guarantee the real-time requirement of data processing. Moreover, the model can also well realize the augmented reality navigation and interaction effect of buildings in outdoor scenes. To sum up, this study provides a research idea for the identification, data processing, and intelligent detection of urban buildings.
... Specificity is the ratio between how many vehicles were exactly detected as misbehaving vehicles on how many vehicles are misbehaving. F-measure is to combine the two scores of recall and precision into a single score [32]. The false-positive rate is the probability of a false rate, when the true value is negative, the positive result will be given. ...
Vehicular Ad-Hoc Network is an emerging technology, mainly developed for road safety applications, entertainment applications, and effective traffic conditions. VANET applications work based on the accurate mobility information shared among the vehicles. Sometimes attackers manipulate the mobility information shared by the adjacent vehicle or neighboring vehicle, which results in terrible consequences. To deal with the illusion-based type of attacks, researchers have proposed enormous solutions. Unfortunately, those solutions could not deal with the dynamic vehicle conditions and variable cyber malfunctions, which reduces the misbehavior detection accurateness and increases the false-positive rate. In this paper, the dynamic vehicle context is taken into account to propose a two solutions such as Miscellaneous VANET Classifiers based Misbehavior Detection Model (MVC-MDM) and Ensemble Miscellaneous VANET Classifiers based Misbehavior Detection Model (EMVC-MDM). This model is constructed based on the Mobility Data Gathering phase, Mobility Context Feature Extraction phase, Mobility Context Feature Level Fixing phase, Hampel Filter based Context Reference Building phase, Constructing Miscellaneous VANET Classifiers based Misbehavior Detection model and Ensemble Miscellaneous VANET Classifiers based Misbehavior Detection phase. Vehicle context is prepared using the data-centric features and the behavior-based features of the vehicles. The Nonparametric Hampel filter and Kalman filter are used to building the context reference model. These filters discover the temporal and spatial correlation of the uniformity in the current mobility information. Vehicle features are extracted locally according to the stability, likelihood, and performance of the vehicles' mobility information. A random forest based learning algorithm is used to train and test the classifiers. The proposed MVC-MDM and EMVC-MDM has been simulated in various context scenarios and the presence of misbehaving vehicles. NGSIM dataset has been used for extensive simulation. The results prove that the effectiveness and the reliability of the proposed MVC-MDM and EMVC-MDM are higher than the existing misbehavior detection systems.
... ACM 44 10 03 05 01 01 IEEE Xplore 488 255 153 167 98 80 Science direct 159 55 51 56 39 26 Springer 145 72 47 54 23 15 Taylor & Francis 70 38 29 32 27 05 MDPI 38 31 21 23 15 07 Total 944 461 304 337 203 Various security issues and challenges in the deployment of fog computing have been highlighted in different surveys and reviews [4, 5, 17, 19, 25, 26, 28, 31-33, 53, 109, 112, 114, 126, 130, 133]. On the other hand, some of the researchers are deploying fog computing technology for enhancing security in different latency sensitive areas such as [8,9,14,15,34,99,100,102,104,109,127,134]; fog forensics [26,29] etc.; Challenges during simulation of fog and edge environments have been discussed in [101]. It is found that most of them are emphasizing the security issues that may occur in a typical fog to cloud scenario. ...
The potent concept of fog computing is currently attracting many researchers as it brings cloud services closer to the end-user. It also roots out some of the major limitations of the cloud scenario where there exists the need for extremely low latency. Despite its compelling advantages, fog computing is still an evolving paradigm that demands further research. Among all the other issues prevalent in fog computing, security is one of the burning issues. Fog nodes, being at the edge of the network, pose several security threats. The authors have thus conducted a systematic literature review (SLR) on security issues in fog computing scenario. Initially, the prevalent security issues are identified through an in-depth survey and then the available literature per security issue is analyzed systematically. This SLR reveals that the security in/through fog scenario is being addressed by the researchers all over the globe. But, the approaches with respect to fog environment still lack methods to evaluate security aspects. Though most of the researchers are prioritizing the consideration of security aspects at fog level, there still exists a need to consider fog computing security as an area of serious concern.
... In particular, many activities have been done, such as dataset preparation, environmental noise injection, communication simulation, and misbehavior simulation. Similar to related studies [2,20,29,35,76,77], the Matlab tool [78] has been used for simulating the environmental noises, vehicle communication, and misbehaving vehicles. ...
Life-saving decisions in vehicular ad hoc networks (VANETs) depend on the availability of highly accurate, up-to-date, and reliable data exchanged by neighboring vehicles. However, spreading inaccurate, unreliable, and false data by intruders create traffic illusions that may cause loss of lives and assets. Although several solutions for misbehavior detection have been proposed to address these issues, those solutions lack adequate representation and the adaptability to vehicular context. The use of predefined static thresholds and lack of comprehensive context representation have rendered the existing solutions limited to specific scenarios and attack types, which impedes their generalizability. This paper addresses these limitations by proposing an ensemble-based hybrid context-aware misbehavior detection system (EHCA-MDS) model. EHCA-MDS has been developed in four phases, as follows. The static thresholds have been replaced by dynamic ones created on the fly by analyzing the spatial and temporal properties of the mobility information collected from neighboring vehicles. Kalman filter-based algorithms were used to collect the mobility information of neighboring vehicles. Three sets of features were then derived, each of which has a different perspective, namely data consistency, data plausibility, and vehicle behavior. These features were used to construct a dynamic context reference using the Hampel filter. The Hampel-based z-score was used to evaluate the vehicles based on their behavioral activities, data consistency, and plausibility. For comprehensive features representation, multifaceted, non-parametric-based statistical classifiers were constructed and updated online using a Hampel filter-based algorithm. For accurate representation, the output of the statistical classifiers, vehicles’ scores, context reference parameters, and the derived features were used as input to an ensemble learning-based algorithm. Such representation helps to identify the misbehaving vehicles more effectively. The proposed EHCA-MDS model was evaluated in the presence of different types of misbehaving vehicles under different context scenarios through extensive simulations, utilizing a real-world traffic dataset. The results show that the accuracy and robustness of the proposed EHCA-MDS under different vehicular dynamic context scenarios were higher than existing solutions, which confirms its feasibility and effectiveness to improve the performance of VANET critical applications.
Vehicular ad hoc network (VANET) is a modern communication design that allows the interpretation between vehicles to move at high speeds on the roads. It has started the opportunity to design various new administrations like traffic administration, distribution of emergency data to avoid dangerous conditions, traffic engineering, and other user records. VANETs are a close relation of MANETs but with recognizing features like action at high speeds, processing power, moving controlled, sufficient storage, variable node consistency, and challenging communication position with precise link existence. Various security issues are usually identified in vehicular ad hoc networks, like authentication and authorization issues, and it gets problems from frequent attacks that survive for MANET. As VANETs are extensively used in various critical applications, much investigation has been done to determine effective solutions against these DoS attacks that can work for multiple routing protocols. This paper presents a brief survey on DoS attack on network availability and its extremity stage in the VANET atmosphere. Also, the paper discusses on various existing techniques to detect and prevent the DoS attack. A detailed comparative statement is made between these techniques to understand its effectiveness in VANET.
LEACH employs a randomization strategy to uniformly spread energy and load through each and every node in the sensor network. The sensor nodes in LEACH assemble into clusters known as local clusters. A cluster-head known as a central base station would be present in the local cluster. When the cluster head has made his or her decision, all other participant nodes or non-cluster-head nodes in the cluster may submit their data to the corresponding cluster-head. Due to battery drain, the sensor node chosen as a cluster-head in traditional clustering algorithms would die easily. As a result, network loss will occur both efficiently and rapidly. As a result, LEACH employs a unique approach for preserving the lifespan of cluster heads as well as the overall network. The LEACH algorithm employs randomized rotation of the high-energy cluster-head sorting technique. This algorithm would choose the cluster-head on a regular basis depending on the sensor nodes with the highest capacity.
