scholarly journals Mitigating Network Denial-of-Service Through Diversity-Based Traffic Management

2005 ◽  
pp. 104-121 ◽  
Author(s):  
Ashraf Matrawy ◽  
Paul C. van Oorschot ◽  
Anil Somayaji
Keyword(s):  
Traffic Management ◽  
Denial Of Service

scholarly journals Decision Tree and Neural Network Based Hybrid Algorithm for Detecting and Preventing Ddos Attacks in VANETS

2020 ◽  
Vol 9 (5) ◽  
pp. 669-675
Keyword(s):  
Neural Network ◽  
Decision Tree ◽  
Traffic Management ◽  
Hybrid Algorithm ◽  
Denial Of Service ◽  
Attack Detection ◽  
Ddos Attacks ◽  
Dos Attacks ◽  
Ddos Attack ◽  
Different Types

The demand of Vehicular Adhoc Networks (VANETs) has been increasing in the area of vehicular and infrastructure communications. It has been felt that there is requirement of sharing of critical information related to safety and traffic management among different types of vehicles in a secure way. To ensure the smooth operation of the network, the availability of network resources is needed. The presence of either malicious vehicles or inaccessibility of network services makes VANET easy target for denial of service (DoS) attacks. The sole purpose of DoS attacks is to prevent the intended users from accessing the available resources and services. When the DoS attack is carried out by multiple vehicles distributed throughout the network, it is referred as Distributed DoS (DDoS) attack. The DDoS attacks are very dangerous and hard to be addressed in real time. The machine learning based DDoS attack detection algorithms have been proposed and presented by the research community in literature. In this paper, a hybrid algorithm of Decision Tree and Neural Network is presented for detecting and preventing different types of DDoS attacks in VANETs with highly efficient results. The simulation based experiments are carried out in order to evaluate and compare the performance of proposed hybrid algorithm with respect to different performance parameters. Based on experiments results, it has been found that the performance of hybrid algorithm has been increased significantly.

scholarly journals MSOM: Efficient Mechanism for Defense against DDoS Attacks in VANET

2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Mohammed Al-Mehdhara ◽  
Na Ruan
Keyword(s):  
Traffic Management ◽  
Ad Hoc ◽  
Network Reliability ◽  
Denial Of Service ◽  
Detection Accuracy ◽  
Ddos Attacks ◽  
Self Organizing Maps ◽  
Clustering And Classification ◽  
Network Communications ◽  
And Performance

The wireless nature of the Vehicular Ad Hoc Network (VANET), a technology that offers facilities such as traffic management and safety services, makes it vulnerable to distributed denial-of-service (DDoS) attacks that exploit network communications and reduce network reliability and performance. This paper proposes a design of a secure VANET architecture using a Software-Defined Networking (SDN) controller and Neural Network Self-Organizing Maps (SOMs). In the proposed design, we adopt the SDN architecture by using its separation of the control plane from the data plane and adding intelligent capabilities to the VANET. To resolve the drawbacks of standard SOMs and to enhance the SOM’s efficiency, a Multilayer Distributed SOM (MSOM) model based on two levels of clustering and classification is used. Experimental results show that our solution can efficiently detect malicious traffic, prevent and mitigate DDoS attacks, and increase system security and recovery speed from the attacking traffic. Moreover, the proposed scheme achieves a high accuracy rate (99.67%). Simulation results demonstrate the effectiveness and efficiency of the MSOM regarding detection accuracy and other studied metrics.

Safety Culture and Safety-Relevant Behavior in Air Traffic Management

2015 ◽  
Vol 5 (1) ◽  
pp. 3-17 ◽  
Author(s):  
Michaela Schwarz ◽  
K. Wolfgang Kallus
Keyword(s):  
Safety Culture ◽  
Traffic Management ◽  
Service Providers ◽  
Five Factor Model ◽  
Principal Component ◽  
Air Traffic Management ◽  
Air Traffic ◽  
Psychometric Validation ◽  
Safety Attitudes ◽  
Culture Development

Since 2010, air navigation service providers have been mandated to implement a positive and proactive safety culture based on shared beliefs, assumptions, and values regarding safety. This mandate raised the need to develop and validate a concept and tools to assess the level of safety culture in organizations. An initial set of 40 safety culture questions based on eight themes underwent psychometric validation. Principal component analysis was applied to data from 282 air traffic management staff, producing a five-factor model of informed culture, reporting and learning culture, just culture, and flexible culture, as well as management’s safety attitudes. This five-factor solution was validated across two different occupational groups and assessment dates (construct validity). Criterion validity was partly achieved by predicting safety-relevant behavior on the job through three out of five safety culture scores. Results indicated a nonlinear relationship with safety culture scales. Overall the proposed concept proved reliable and valid with respect to safety culture development, providing a robust foundation for managers, safety experts, and operational and safety researchers to measure and further improve the level of safety culture within the air traffic management context.

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