Mitigating Blackhole and Greyhole Routing Attacks in Vehicular Ad Hoc Networks Using Blockchain Based Smart Contracts

The rapid increase in vehicle traffic volume in modern societies has raised the need to develop innovative solutions to reduce traffic congestion and enhance traffic management efficiency.Revolutionary advanced technology,such as Intelligent Transportation Systems(ITS),enables improved traffic management,helps eliminate congestion,and supports a safer environment.ITS provides real-time information on vehicle traffic and transportation systems that can improve decision-making for road users.However,ITS suffers from routing issues at the network layer when utilising Vehicular Ad Hoc Networks(VANETs).This is because each vehicle plays the role of a router in this network,which leads to a complex vehicle communication network,causing issues such as repeated link breakages between vehicles resulting from the mobility of the network and rapid topological variation.This may lead to loss or delay in packet transmissions;this weakness can be exploited in routing attacks,such as black-hole and gray-hole attacks,that threaten the availability of ITS services.In this paper,a Blockchain-based smart contracts model is proposed to offer convenient and comprehensive security mechanisms,enhancing the trustworthiness between vehicles.Self-Classification Blockchain-Based Contracts(SCBC)and Voting-Classification Blockchain-Based Contracts(VCBC)are utilised in the proposed protocol.The results show that VCBC succeeds in attaining better results in PDR and TP performance even in the presence of Blackhole and Grayhole attacks.

An Intelligent Hybrid Mutual Authentication Scheme for Industrial Internet of Thing Networks

Internet of Things(IoT)network used for industrial management is vulnerable to different security threats due to its unstructured deployment,and dynamic communication behavior.In literature various mechanisms addressed the security issue of Industrial IoT networks,but proper maintenance of the performance reliability is among the common challenges.In this paper,we proposed an intelligent mutual authentication scheme leveraging authentication aware node(AAN)and base station(BS)to identify routing attacks in Industrial IoT networks.The AAN and BS uses the communication parameter such as a route request(RREQ),node-ID,received signal strength(RSS),and round-trip time(RTT)information to identify malicious devices and routes in the deployed network.The feasibility of the proposed model is validated in the simulation environment,where OMNeT++was used as a simulation tool.We compare the results of the proposed model with existing field-proven schemes in terms of routing attacks detection,communication cost,latency,computational cost,and throughput.The results show that our proposed scheme surpasses the previous schemes regarding these performance parameters with the attack detection rate of 97.7%.

Dual Authentication Hashing for Security Enhancement in MANET

Mobile Ad hoc Network (MANET) is a collection of mobile hosts with wireless interfaces that form a temporary network without the aid of any fixed infrastructure or centralized administration. A MANET is a type of ad hoc network that can change locations and configure itself on the fly. The dynamic and cooperative behaviour of ad hoc networking without any centralized or unified controlling authority for authentication and monitoring is sensitive to attacks that damage or exploit the cooperative behaviour of ad hoc routing. Routing attacks lead to the most disastrous damage in MANET. The main objective of this paper is to enhance the security against routing attacks in MANETs. Intrusion detection based on DAHT (Dual Authentication Hash Technique) entirely depends on the end to end communication between the source and destination is employed here. The proposed technique identifies the misbehaving nature of current node and the previous node where it receives the information. DAHT is simulated with various parameters in NS2. The results obtained are compared with existing mechanism. The results show that malicious detection, overhead reduction and delay are better when compared to the existing system that is employed in protecting the routing information.

Experiment and simulation study of emergency evacuation during violent attack in classrooms

In recent years,as a disaster,terrorist attacks have occurred throughout the world.However,emergency evac-uation behaviors during these incidents were not clear,and the traditional emergency plans were not suitable for such incidents.In this paper,evacuation behaviors under armed assault attack in a classroom were studied based on evacuation experiments.A total of 103 participants took part in three experiments.In each experiment,the attacker’s attacking route was set differently to study the impact of the attacking route on evacuation be-haviors.Pre-evacuation delay,panic of the evacuees,exit choices,evacuation time,and evacuees’trajectories in the experiments were all analyzed.The results of the experiments showed that when a terrorist attack occurs,there is a long delay before evacuation,and most of the evacuees were in the state of“observation”before they moved.When one of the participants started to evacuate or shout,other participants would begin to recognize the danger and escape quickly.These three experiments showed that the route of the attacker had a significant impact on the routes and exit choices of the evacuees.Rather than searching for the nearest exit,the primary purpose of evacuees was to keep a safe distance from the attacker.The average speed of the evacuees in these three experiments was 1.07 m/s,0.81 m/s,and 0.84 m/s,respectively.The density distribution during the crowd evacuation process was uneven,with the highest density occurring at the area from the seats to the aisles.The research can provide data support for the design of emergency plans and the computer simulation of the armed assault attack.

Heuristics of node selection criteria to assess robustness of world airport network

The world airport network（WAN） is one of the networked infrastructures that shape today＇s economic and social activity, so its resilience against incidents affecting the WAN is an important problem. In this paper, the robustness of air route networks is extended by defining and testing several heuristics to define selection criteria to detect the critical nodes of the WAN.In addition to heuristics based on genetic algorithms and simulated annealing, custom heuristics based on node damage and node betweenness are defined. The most effective heuristic is a multiattack heuristic combining both custom heuristics. Results obtained are of importance not only for advance in the understanding of the structure of complex networks, but also for critical node detection.