High-Quality in Data Authentication Dodging Massive Attack in VANETS

VANET plays an important role in the Security terms. VANET network is due to their unique features like as a high dynamic network (topology) and Mobility prediction. It attracts so much attention to the industry. VANET wireless networks are rapidly increased commercial and academic interests. Mobile connectivity, Traffic congestion management and road safety are some applications that have arisen within this network model. The routing protocol is a reactive type which means if there is data to be sent then the way will create. On-demand Distance Vector routing protocol is a generally used network topology based on rules for VANET. In surveyed of the routing protocol implemented a balance AODV method used for identifying the malicious nodes in the network. A balanced AODV routing method is defined with following characteristics:- (i) Use of threshold adaptive according to the network situations and balance index i.e node nature. (ii) Detect the malicious node in the network. (iii) Detection and prevention methods in real-time and independent on each vehicle node. In research paper, implement a B-AODV routing protocol and RSA method for detection and prevention the malicious node in the vehicular network. In this proposed algorithm, each vehicle node is employing balance index for acceptable and reject able REQ information’s (Bits). The consequences of the simulation tool in MATLAB (Matrix Laboratory) indicates BAODV and RSA method is used to detect and prevent the flood attach and loss of network bandwidth. Comparison between AODV, BAODV, RSA in normal phase defines B-AODV is exactly matched with AODV in the vehicular network and performance analysis overhead, an end to end delay and packet delivery rate

An Insight into Sybil Attacks – A Bibliometric Assessment

Sybil attack poses a significant security concern in both centralized and distributed network environments, wherein malicious adversary sabotage the network by impersonating itself as several nodes, called Sybil nodes. A Sybil attacker creates different identities for a single physical device to deceive other benign nodes, as well as uses these fake identities to hide from the detection process, thereby introducing a lack of accountability in the network. In this paper, we have thoroughly discussed the Sybil attack including its types, attack mechanisms, mitigation techniques that are in use today for the detection and prevention of such attacks. Subsequently, we have discussed the impact of the Sybil attack in various application domains and performed a bibliometric assessment in the top four scholarly databases. This will help the research community to quantitatively analyze the recent trends to determine the future research direction for the detection and prevention of such attacks

A multi-tier trust-based security mechanism for vehicular ad-hoc network communications

Securing communications in vehicle ad hoc networks is crucial for operations. Messages exchanged in vehicle ad hoc network communications hold critical information such as road safety information, or road accident information and it is essential these packets reach their intended destination without any modification. A significant concern for vehicle ad hoc network communications is that malicious vehicles can intercept or modify messages before reaching their intended destination. This can hamper vehicle ad hoc network operations and create safety concerns. The multi-tier trust management system proposed in this paper addresses the concern of malicious vehicles in the vehicle ad hoc network using three security tiers. The first tier of the proposed system assigns vehicles in the vehicle ad hoc network a trust value based on behaviour such as processing delay, packet loss and prior vehicle behavioural history. This will be done by selecting vehicles as watchdogs to observe the behaviour of neighbouring vehicles and evaluate the trust value. The second tier is to protect the watchdogs, which is done by watchdogs’ behaviour history. The third security tier is to protect the integrity of data used for trust value calculation. Results show that the proposed system is successful in identifying malicious vehicles in the VANET. It also improves the packet delivery ratio and end-to-end delay of the vehicle ad hoc network in the presence of malicious vehicles

An intelligent intrusion detection system for external communications in autonomous vehicles

Advancements in computing, electronics and mechanical systems have resulted in the creation of a new class of vehicles called autonomous vehicles. These vehicles function using sensory input with an on-board computation system. Self-driving vehicles use an ad hoc vehicular network called VANET. The network has ad hoc infrastructure with mobile vehicles that communicate through open wireless channels. This thesis studies the design and implementation of a novel intelligent intrusion detection system which secures the external communication of self-driving vehicles. This thesis makes the following four contributions: It proposes a hybrid intrusion detection system to protect the external communication in self-driving vehicles from potential attacks. This has been achieved using fuzzification and artificial intelligence. The second contribution is the incorporation of the Integrated Circuit Metrics (ICMetrics) for improved security and privacy. By using the ICMetrics, specific device features have been used to create a unique identity for vehicles. Our work is based on using the bias in on board sensory systems to create ICMetrics for self-driving vehicles. The incorporation of fuzzy petri net in autonomous vehicles is the third contribution of the thesis. Simulation results show that the scheme can successfully detect denial-of-service attacks. The design of a clustering based hierarchical detection system has also been presented to detect worm hole and Sybil attacks. The final contribution of this research is an integrated intrusion detection system which detects various attacks by using a central database in BusNet. The proposed schemes have been simulated using the data extracted from trace files. Simulation results have been compared and studied for high levels of detection capability and performance. Analysis shows that the proposed schemes provide high detection rate with a low rate of false alarm. The system can detect various attacks in an optimised way owing to a reduction in the number of features, fuzzification