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Protecting Neural Networks with Hierarchical Random Switching: Towards Better Robustness-Accuracy Trade-off for Stochastic Defenses [article]

Xiao Wang, Siyue Wang, Pin-Yu Chen, Yanzhi Wang, Brian Kulis, Xue Lin, Peter Chin
2019 arXiv   pre-print
This paper is motivated by pursuing for a better trade-off between adversarial robustness and test accuracy for stochastic network defenses.  ...  To achieve a better DES, we propose hierarchical random switching (HRS), which protects neural networks through a novel randomization scheme.  ...  In addition, towards achieving a better trade-off, we propose hierarchical random switching (HRS) for defense, which can be easily compatible with typical network training procedures.  ... 
arXiv:1908.07116v1 fatcat:2hoia3hwznbjhntrfunh5ja6fy

An Exhaustive Survey on P4 Programmable Data Plane Switches: Taxonomy, Applications, Challenges, and Future Trends [article]

Elie F. Kfoury, Jorge Crichigno, Elias Bou-Harb
2021 arXiv   pre-print
Despite the impressive advantages of programmable data plane switches and their importance in modern networks, the literature has been missing a comprehensive survey.  ...  approach to develop network applications; providing granular visibility of packet events defined by the programmer; reducing complexity and enhancing resource utilization of the programmable switches;  ...  A commonly used training technique for deep neural networks is synchronous stochastic gradient descent [299] . In this technique, each worker has a copy of the model that is being trained.  ... 
arXiv:2102.00643v2 fatcat:izxi645kozdc5ibfsqp2y2foau

An Exhaustive Survey on P4 Programmable Data Plane Switches: Taxonomy, Applications, Challenges, and Future Trends

Elie F. Kfoury, Jorge Crichigno, Elias Bou-Harb
2021 IEEE Access  
INDEX TERMS Programmable switches, P4 language, Software-defined Networking, data plane, custom packet processing, taxonomy.  ...  Despite the impressive advantages of programmable data plane switches and their importance in modern networks, the literature has been missing a comprehensive survey.  ...  A commonly used training technique for deep neural networks is synchronous stochastic gradient descent [299] . In this technique, each worker has a copy of the model that is being trained.  ... 
doi:10.1109/access.2021.3086704 fatcat:2jgbxj2cbfbp7fawkxwrztbbia

Var-CNN: A Data-Efficient Website Fingerprinting Attack Based on Deep Learning

Sanjit Bhat, David Lu, Albert Kwon, Srinivas Devadas
2019 Proceedings on Privacy Enhancing Technologies  
While the current state-of-the-art attack, which uses deep learning, outperforms prior art with medium to large amounts of data, it attains marginal to no accuracy improvements when both use small amounts  ...  This shortens the time needed for data collection and lowers the likelihood of having data staleness issues.  ...  The authors would like to thank Dimitris Tsipras and the Mądry Lab at MIT for providing some of the compute resources used to run these experiments.  ... 
doi:10.2478/popets-2019-0070 dblp:journals/popets/BhatLKD19 fatcat:hjgdmdykkfbpfoldank4hi2sqi

Mitigating Black-Box Adversarial Attacks via Output Noise Perturbation [article]

Manjushree B. Aithal, Xiaohua Li
2021 arXiv   pre-print
In this paper, we study the method of adding white noise to the DNN output to mitigate such attacks, with a unique focus on the trade-off analysis of noise level and query cost.  ...  We also show that this method outperforms many other defense methods and is robust to the attacker's countermeasures.  ...  Protecting neural networks with hierarchical random switching: Towards better robustness-accuracy trade-off for stochastic defenses. arXiv preprint arXiv:1908.07116, 2019. [24] Carlini, N., D.  ... 
arXiv:2109.15160v1 fatcat:i57rydy7vje6noobropaezygxe

Artificial intelligence enabled software-defined networking: a comprehensive overview

Majd Latah, Levent Toker
2019 IET Networks  
Software defined networking (SDN) represents a promising networking architecture that combines central management and network programmability.  ...  Recently, the research community has showed an increased tendency to benefit from the recent advancements in the artificial intelligence (AI) field to provide learning abilities and better decision making  ...  There is a trade-off between exploration and exploitation.  ... 
doi:10.1049/iet-net.2018.5082 fatcat:celiaiit7jhrfnufpoltuecf5y

2020 Index IEEE Systems Journal Vol. 14

2020 IEEE Systems Journal  
., +, JSYST Sept. 2020 3343-3350 On the Secrecy Performance of Random VLC Networks With Imperfect CSI and Protected Zone.  ...  ., +, JSYST June 2020 2713-2724 On the Secrecy Performance of Random VLC Networks With Imperfect CSI and Protected Zone.  ...  ., +, 2585 -2588 Energy-Efficient IoT-Fog-Cloud Architectural Paradigm for Real-Time Wildfire Prediction and Forecasting. 2003 -2011 Agent Pseudonymous Authentication-Based Conditional Privacy Preservation  ... 
doi:10.1109/jsyst.2021.3054547 fatcat:zf2aafvnfzbeje32qei5563myu

Toward Proactive, Adaptive Defense: A Survey on Moving Target Defense [article]

Jin-Hee Cho, Dilli P. Sharma, Hooman Alavizadeh, Seunghyun Yoon, Noam Ben-Asher, Terrence J. Moore, Dong Seong Kim, Hyuk Lim, Frederica F. Nelson
2019 arXiv   pre-print
Reactive defense mechanisms, such as intrusion detection systems, have made significant efforts to secure a system or network for the last several decades.  ...  The aim of this paper is to provide the overall trends of MTD research in terms of critical aspects of defense systems for researchers who seek for developing proactive, adaptive MTD mechanisms.  ...  Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation here on.  ... 
arXiv:1909.08092v1 fatcat:wsycpvaqgzdcvboagxlbg5x6uu

Edge Learning for B5G Networks with Distributed Signal Processing: Semantic Communication, Edge Computing, and Wireless Sensing [article]

Wei Xu, Zhaohui Yang, Derrick Wing Kwan Ng, Marco Levorato, Yonina C. Eldar, M'erouane Debbah
2022 arXiv   pre-print
In particular, typical performance metrics for dual-functional learning and communication networks are discussed.  ...  Also, recent achievements of enabling techniques for the dual-functional design are surveyed with exemplifications from the mutual perspectives of "communications for learning" and "learning for communications  ...  Taking FL as an example, the trade-off between learning time and UE energy consumption and the trade-off between computation time and communication latency are of wide interest.  ... 
arXiv:2206.00422v1 fatcat:osp426emrngi3bvye6fmk7kqce

Explainable Artificial Intelligence Applications in Cyber Security: State-of-the-Art in Research [article]

Zhibo Zhang, Hussam Al Hamadi, Ernesto Damiani, Chan Yeob Yeun, Fatma Taher
2022 arXiv   pre-print
The deficiencies of transparency and interpretability of existing Artificial Intelligence techniques would decrease human users' confidence in the models utilized for the defense against cyber attacks,  ...  However, although Artificial Intelligence-based approaches for the detection and defense of cyber attacks and threats are more advanced and efficient compared to the conventional signature-based and rule-based  ...  BETWEEN INTERPRETABILITY AND ACCURACY The Explainability and performance (predictive accuracy) of a model are generally shown to be in trading-off with each other [90] .  ... 
arXiv:2208.14937v1 fatcat:qyqk2oxsbvhapjszbkwuz3aw5q

2022 Roadmap on Neuromorphic Computing and Engineering [article]

Dennis V. Christensen, Regina Dittmann, Bernabé Linares-Barranco, Abu Sebastian, Manuel Le Gallo, Andrea Redaelli, Stefan Slesazeck, Thomas Mikolajick, Sabina Spiga, Stephan Menzel, Ilia Valov, Gianluca Milano (+47 others)
2022 arXiv   pre-print
This data transfer is responsible for a large part of the power consumption. The next generation computer technology is expected to solve problems at the exascale with 1018 calculations each second.  ...  This new generation of computers has the potential to be used for the storage and processing of large amounts of digital information with much lower power consumption than conventional processors.  ...  Acknowledgements The author thanks the CNRS for support. Acknowledgements The author would like to thank E. Donati for fun and insightful discussions and brainstorming on the topic.  ... 
arXiv:2105.05956v3 fatcat:pqir5infojfpvdzdwgmwdhsdi4

Security Threats and Artificial Intelligence based Countermeasures for Internet of Things Networks: A Comprehensive Survey

Shakila Zaman, Khaled Alhazmi, Mohammed Aseeri, Muhammad Raisuddin Ahmed, Risala Tasin Khan, M. Shamim Kaiser, Mufti Mahmud
2021 IEEE Access  
EFFICIENCY AND IOT CAPABILITY TRADE OFF The IoT requires a balance between security and energy consumption.  ...  In real-time, IoT systems are typically stochastic and random, thus the existing models are not applicable for realtime applications.  ...  For more information, see https://creativecommons.org/licenses/by-nc-nd/4.0/  ... 
doi:10.1109/access.2021.3089681 fatcat:fatpywnjzzfilidakyduz6qz44

A Full Dive into Realizing the Edge-enabled Metaverse: Visions, Enabling Technologies,and Challenges [article]

Minrui Xu, Wei Chong Ng, Wei Yang Bryan Lim, Jiawen Kang, Zehui Xiong, Dusit Niyato, Qiang Yang, Xuemin Sherman Shen, Chunyan Miao
2022 arXiv   pre-print
communication systems for users to immerse as and interact with embodied avatars in the Metaverse.  ...  Finally, we discuss the future research directions towards realizing the true vision of the edge-enabled Metaverse.  ...  A trade-off is derived between the privacy protection and the model performance, i.e., a better model performance leads to a lower level of privacy protection.  ... 
arXiv:2203.05471v2 fatcat:jhl66faxw5clnopsb5rbsopzoq

Table of contents

2021 ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)  
Zoubir, Technische Universität Darmstadt, Germany SAM-10.6: FUNDAMENTAL TRADE-OFFS IN NOISY SUPER-RESOLUTION WITH ...................................... 4420 SYNTHETIC APERTURES Sina Shahsavari, Jacob  ...  TRADE-OFF OF INFERENCE AS SERVICE ................................................... 2645 Yulu Jin, Lifeng Lai, University of California, Davis, United States IFS-6.4: FEDERATED LEARNING WITH LOCAL DIFFERENTIAL  ... 
doi:10.1109/icassp39728.2021.9414617 fatcat:m5ugnnuk7nacbd6jr6gv2lsfby

Game-Theoretic and Machine Learning-based Approaches for Defensive Deception: A Survey [article]

Mu Zhu, Ahmed H. Anwar, Zelin Wan, Jin-Hee Cho, Charles Kamhoua, Munindar P. Singh
2021 arXiv   pre-print
Defensive deception is a promising approach for cyber defense. Via defensive deception, the defender can anticipate attacker actions; it can mislead or lure attacker, or hide real resources.  ...  It closes with an outline of some research directions to tackle major gaps in current defensive deception research.  ...  Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation herein.  ... 
arXiv:2101.10121v2 fatcat:ko2mzzvyerehnfxbwgeuz72ilu
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