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Detection and Ignoring of Blackhole Attack in Vanets Networks
International Journal of Cloud Applications and Computing, 2016Vehicular networks or VANET announce as the communication networks of the future, where the mobility is the main idea. These networks should be able to interconnect vehicles. The optimal goal is that these networks will contribute to safer roads and more effective in the future by providing timely information to drivers and concerned authorities.
Chaima Bensaid +2 more
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MART: Targeted attack detection on a compromised network
MILCOM 2016 - 2016 IEEE Military Communications Conference, 2016Targeted attacks are a significant problem for governmental agencies and corporations. We propose a MinHash-based, targeted attack detection system which analyzes aggregated process creation events typically generated by human keyboard input. We start with a set of malicious process creation events, and their parameters, which are typically generated ...
Jack W. Stokes +3 more
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Research on Attacks Detection in CSMA Wireless Networks
2019 11th International Conference on Wireless Communications and Signal Processing (WCSP), 2019Based on the in-depth analysis of the jamming attack principle of the communication system using the CSMA protocol, this paper proposes a detection algorithm based on the statistical information fluctuation range of control frames such as RTS (Request to Send) frames and CTS (Clear to Send) frames. With Bootstrap technique of non-parametric statistics,
Fang Fang +4 more
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Detecting amplification attacks with Software Defined Networking
2017 IEEE Conference on Dependable and Secure Computing, 2017Distributed denial of service (DDoS) is an attack that attempts to disrupt network service for various malicious purposes. It makes use of public services as reflectors to amplify the traffic, and thus called distributed reflection denial of service attacks.
Chih-Chieh Chen +4 more
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Multivariate statistical analysis for network attacks detection
The 3rd ACS/IEEE International Conference onComputer Systems and Applications, 2005., 2005Summary form only given. Detection and self-protection against viruses, worms, and network attacks is urgently needed to protect network systems and their applications from catastrophic failures. Once a network component is infected by viruses, worms, or became a target of network attacks, its operational state shifts from normal to abnormal state ...
Guangzhi Qu +2 more
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Detecting network attacks using behavioural models
Proceedings of the 6th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems, 2011In this paper we're dealing with the problem of detecting malware using behaviour model. For better malware description we have divided this model into two parts — malware spreading model and malware statistical behavioural model. Spreading models are typical epidemiological models like SI model, advanced SIR and SEIR models and empiric file spreading ...
Jiri Schafer, Michal Drozd
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On the Limits of Payload-Oblivious Network Attack Detection
2008We introduce a methodology for evaluating network intrusion detection systems using an observable attack space, which is a parameterized representation of a type of attack that can be observed in a particular type of log data. Using the observable attack space for log data that does not include payload (e.g., NetFlow data), we evaluate the ...
M. Patrick Collins, Michael K. Reiter
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Approximate autoregressive modeling for network attack detection
Journal of Computer Security, 2006This paper presents a technique for creating an ARX model of network signals and using it for detecting network anomalies caused by intrusions. Network signals are non-stationary, highly volatile and hard to model using traditional methods. We present our own modeling technique using a combination of system identification theory and wavelet ...
Harshit Nayyar, Ali A. Ghorbani 0001
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Impersonation Attack Detection in IoT Networks
GLOBECOM 2022 - 2022 IEEE Global Communications Conference, 2022Dinh Duc Nha Nguyen +4 more
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On the Detection of DDoS Attackers for Large-Scale Networks
2009 IEEE International Conference on e-Business Engineering, 2009The Distributed Denial of Service attacks (DDoS) is one of the major threats to network security that exhausts network bandwidth and resources. The current detection schemes are sensitive to the number of attackers and may lead to a high false positive probability especially for largescale networks with huge number of attackers. It is notable, however,
Dalia Nashat +2 more
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