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Comparative Evaluation of Spoofing Defenses
2011
IEEE Transactions on Dependable and Secure Computing
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Our results offer a valuable insight into advantages and limitations of the proposed defenses, and uncover the relationship between any spoofing defense's performance and the Internet's topology. ...
This paper answers the above questions by: (1) Formalizing the problem of spoofed traffic filtering and defining novel effectiveness measures, (2) Observing each defense as selfish (it helps its participants ...
Related Work For space reasons, we only survey work related to evaluation of spoofing defense effectiveness. ...
doi:10.1109/tdsc.2009.44
fatcat:x3kgnwyp3raflidkvwgoeyb23a
Detection and defense mechanisms against DDoS attacks: A review
2015
2015 International Conference on Innovations in Information, Embedded and Communication Systems (ICIIECS)
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The efficiency of algorithm in identifying spoof attack packets is evaluated by simulation experiments in NS3. ...
It is most challenging to defense against such attacks because most of the attacker use source IP address spoofing in order to hide their identity and such attack packets appear to the target server as ...
They evaluated the defenses individually and comparatively in common network settings and their results indicate that three defenses, namely hop count filtering, route based packet filtering and PiIp can ...
doi:10.1109/iciiecs.2015.7193118
fatcat:35aawztearef7f2ecxlybff46e
Toward Blockchain-Based Spoofing Defense for Controlled Optimization of Phases in Traffic Signal System
2022
IEICE transactions on information and systems
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Meanwhile, experiments on the simulation platform VISSIM and Hyperledger Fabric show the efficiency and practicality of the blockchain-based defense mechanism. ...
Unfortunately, I-SIG suffers data spoofing from any hacked vehicle; in particular, the spoofing of the last vehicle can break the system and cause severe traffic congestion. ...
Acknowledgments The work was supported by the National Natural Science Foundation of China under Grant Nos. 61972025, 61802389, 61672092, U1811264, and 61966009, the National Key R&D Program of China under ...
doi:10.1587/transinf.2021bcp0014
fatcat:acyl43rcnrgj5eozehgkrfzu34
On the deployability of inter-AS spoofing defenses
2015
IEEE Network
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Evaluation results reveal the technical features of highly deployable defenses, which can help improve existing defenses and the design of future defenses. ...
In this article we investigate the deployability of the defenses by evaluating their deployment benefit, deployment cost, and operational risk. ...
In this article we survey existing inter-AS spoofing defenses and evaluate them against these metrics. ...
doi:10.1109/mnet.2015.7113230
fatcat:vzdngvvoc5hudlrt7ppuis5bcu
GANBA: Generative Adversarial Network for Biometric Anti-Spoofing
2022
Applied Sciences
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Then, the resulting PAD discriminators of the proposed GANBA can be used as a defense technique for detecting both original and adversarial spoofing attacks. ...
Moreover, the robustness of the whole biometric system (ASV + PAD) against this new type of attack is completely unexplored. ...
Furthermore, we acknowledge the support of Nvidia with the donation of a Titan X GPU.
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/app12031454
fatcat:w6ne562hsrfg5f6gzphhk3d5wm
Deep Learning based Detection of DNS Spoofing Attack
2019
Zenodo
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The methodology of the research is to evaluate the deep learning model trained on the artificially synthesized dataset. The numerical results from simulations are used to evaluate the performance. ...
Using of IP header data, particularly, such feature as hop count is well known and widely used for IP spoofing. The main challenge is to apply these approaches to DNS spoofing detection. ...
In the [9] the comparative evaluation of spoofing defenses is presented.2019 Scientific Seminar on Innovative Solutions in Software Engineering, Ivano-Frankivsk, Ukraine, December 10, 2019 ...
doi:10.5281/zenodo.4091018
fatcat:jyv5xjxqsfcaxjlxh7ani7hz5y
Defense technique against spoofing attacks using reliable ARP table in cloud computing environment
2015
2015 17th Asia-Pacific Network Operations and Management Symposium (APNOMS)
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In this paper, we propose a defense technique for loss of VM resources against the network attacks called spoofing of poison on OpenStack environment. ...
However spoofing or poison attacks on VM inside the cloud cause the deterioration of cloud system and those attacks can make the huddle for spreading the cloud services. ...
On the top of it, we propose a defense technique against Spoofing attacks using reliable ARP table. ...
doi:10.1109/apnoms.2015.7275401
dblp:conf/apnoms/KangSH15
fatcat:3wxhe2ijlrfcnd67qp6ttwiamm
Towards Robust LiDAR-based Perception in Autonomous Driving: General Black-box Adversarial Sensor Attack and Countermeasures
[article]
2020
arXiv
pre-print
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We perform the first defense study, proposing CARLO to mitigate LiDAR spoofing attacks. ...
Recent studies have demonstrated that LiDAR-based perception is vulnerable to spoofing attacks, in which adversaries spoof a fake vehicle in front of a victim self-driving car by strategically transmitting ...
The entire algorithm of CARLO is detailed in Appendix C.
CARLO Evaluation Experimental setup. We evaluate the defense performance of CARLO on the KITTI trainval and test sets. ...
arXiv:2006.16974v1
fatcat:wcer2du5gvegdivzusi5j22rbm
Defense against adversarial attacks on spoofing countermeasures of ASV
[article]
2020
arXiv
pre-print
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This paper is among the first to use defense methods to improve the robustness of ASV spoofing countermeasure models under adversarial attacks. ...
In this work, we introduce a passive defense method, spatial smoothing, and a proactive defense method, adversarial training, to mitigate the vulnerability of ASV spoofing countermeasure models against ...
DEFENSE METHODS There are two kinds of defense methods against adversarial attacks: passive defense and proactive defense. ...
arXiv:2003.03065v1
fatcat:4hgar5vfxndofpuxu4ylvncrau
Privacy-Preserving and Efficient Data Collection Scheme for AMI Networks Using Deep Learning
[article]
2020
arXiv
pre-print
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Finally, we train a deep-learning-based defense model to send spoofing transmissions efficiently to thwart the PPA. ...
Then, we train an attacker model using deep-learning, and our evaluations indicate that the success rate of the attacker is about 91%. ...
ACKNOWLEDGEMENT This project was funded by the Deanship of Scientific Research (DSR) at King Abdulaziz University, Jeddah, under grant no. DF-745-611-1441. ...
arXiv:2011.03814v1
fatcat:qcwgib6jqng3thyr4plwwovsgm
Security Analysis of Camera-LiDAR Fusion Against Black-Box Attacks on Autonomous Vehicles
[article]
2022
arXiv
pre-print
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2021 pre-print arXiv:2106.07098v2 fatcat:73bijfhp5ba5xd7bxhs7u7hz5uOther Versions
In addition, we demonstrate that the frustum attack is stealthy to existing defenses against LiDAR spoofing as it preserves consistencies between camera and LiDAR semantics. ...
Thus, in this work, we perform an analysis of camera-LiDAR fusion, in the AV context, under LiDAR spoofing attacks. ...
B Reproducing Black Box Attack To fully evaluate the existing state of the art, we reproduce the attack on LiDAR-based perception from [40] -we achieved comparable results to the original work. ...
arXiv:2106.07098v4
fatcat:onalm73kcjdunoeqbzv4sscj7m
The Attacker's Perspective on Automatic Speaker Verification: An Overview
[article]
2020
arXiv
pre-print
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Security of automatic speaker verification (ASV) systems is compromised by various spoofing attacks. ...
We present an overview on this emerging research area by focusing on potential threats of adversarial attacks on ASV, spoofing countermeasures, or both. ...
A1687b0033 from the Singapore Government's Research, Innovation and Enterprise 2020 plan (Advanced Manufacturing and Engineering domain) and in part by the Academy of Finland (Proj. ...
arXiv:2004.08849v1
fatcat:ywgbjq5oafbw3pu5mtad7fatru
The Attacker's Perspective on Automatic Speaker Verification: An Overview
2020
Interspeech 2020
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Security of automatic speaker verification (ASV) systems is compromised by various spoofing attacks. ...
We present an overview on this emerging research area by focusing on potential threats of adversarial attacks on ASV, spoofing countermeasures, or both. ...
A1687b0033 from the Singapore Government's Research, Innovation and Enterprise 2020 plan (Advanced Manufacturing and Engineering domain) and in part by the Academy of Finland (Proj. ...
doi:10.21437/interspeech.2020-1052
dblp:conf/interspeech/DasTK020
fatcat:sstxijrgp5ckjidr2isvct3foe
Novel Promising Algorithm to suppress Spoof Attack by Cryptography Firewall2014
2018
International Journal of Trend in Scientific Research and Development
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Spoof attack suppression by the biometric information incorporation is the new and modern method of and as well suppression the attack online as well off line. ...
How do the various defense mechan compare? This article first looks into the current state of IP spoofing, then thoroughly surveys the current state of IP spoofing defense. ...
How do the various defense mechanisms compare? This article first looks into the current state of IP spoofing, then thoroughly surveys the current state of IP spoofing defense. ...
doi:10.31142/ijtsrd15801
fatcat:p2qz2htdcjc6ndmiifxx3ak7yy
Multifractal Characterization of Distribution Synchrophasors for Cybersecurity Defense of Smart Grids
2021
IEEE Transactions on Smart Grid
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Source ID Mix" spoofing emerged as a new type of cyber-attack on Distribution Synchrophasors (DS) where adversaries have the capability to swap the source information of DS without changing the measurement ...
Accurate detection of such a highly-deceptive attack is a challenging task especially when the spoofing attack happens on short fragments of DS recorded within a relatively small geographical scale. ...
Performance Evaluation In this section, the performance of the proposed cybersecurity defense method is compared with other five recently reported algorithms in identifying the source information of DS ...
doi:10.1109/tsg.2021.3132536
fatcat:tjriioht7jfpdag7hs2ki3llky
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