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Cyberspace Security Using Adversarial Learning and Conformal Prediction

Harry Wechsler
2015 Intelligent Information Management  
This paper advances new directions for cyber security using adversarial learning and conformal prediction in order to enhance network and computing services defenses against adaptive, malicious, persistent  ...  The motivation for using conformal prediction and its immediate off-spring, those of semi-supervised learning and transduction, comes from them first and foremost supporting discriminative and non-parametric  ...  FIS ultimately deploys an integrated IDS that is scalable and responsive to attacks coming from multiple and heterogeneous channels.  ... 
doi:10.4236/iim.2015.74016 fatcat:wqiu3pkl6zeurlr3mizdahhgd4

Malware Detection Based on Graph Attention Networks for Intelligent Transportation Systems

Cagatay Catal, Hakan Gunduz, Alper Ozcan
2021 Electronics  
To detect malware attacks addressing ITS, a Graph Attention Network (GAN)-based framework is proposed in this study.  ...  A GAN-based model is combined with different types of node features during the experiments and the performance is compared against Graph Convolutional Network (GCN).  ...  While combining the outputs, the attention mechanism weights learned adaptively in the training of the network are used.  ... 
doi:10.3390/electronics10202534 fatcat:akgkn5cp6baodoqesyh4vlprlm

A Survey on Heterogeneous Graph Embedding: Methods, Techniques, Applications and Sources [article]

Xiao Wang and Deyu Bo and Chuan Shi and Shaohua Fan and Yanfang Ye and Philip S. Yu
2020 arXiv   pre-print
space while preserving the heterogeneous structures and semantics for downstream tasks (e.g., node/graph classification, node clustering, link prediction), has drawn considerable attentions in recent  ...  Heterogeneous graphs (HGs) also known as heterogeneous information networks have become ubiquitous in real-world scenarios; therefore, HG embedding, which aims to learn representations in a lower-dimension  ...  For this reason, they prefer to use attention mechanism to capture the most relevant structural and attribute information to the task. Wang et al.  ... 
arXiv:2011.14867v1 fatcat:phfoxj7qsrfshfednomeok7pau

Recommender Systems for the Internet of Things: A Survey [article]

May Altulyan, Lina Yao, Xianzhi Wang, Chaoran Huang, Salil S Kanhere, Quan Z Sheng
2020 arXiv   pre-print
Traditional recommender systems fail to exploit ever-growing, dynamic, and heterogeneous IoT data.  ...  We discuss several limitations of applying recommendation systems to IoT and propose a reference framework for comparing existing studies to guide future research and practices.  ...  Recommendations with Reinforcement Learning With the recent tremendous approaches to RS, reinforcement learning (RL) has received increasing attention.  ... 
arXiv:2007.06758v1 fatcat:dt36whkh2jb4bi3r4pjc7ty2um

Internet of Things 2.0: Concepts, Applications, and Future Directions

Ian Zhou, Imran Makhdoom, Negin Shariati, Muhammad Ahmad Raza, Rasool Keshavarz, Justin Lipman, Mehran Abolhasan, Abbas Jamalipour
2021 IEEE Access  
With the aid of machine learning and AI, managing these network connections and autonomous devices should not require much user attention and labor [351] .  ...  Thus, AI could decrease the usability for users with special requirements and preferences.  ... 
doi:10.1109/access.2021.3078549 fatcat:g5jkc5p6tngpfonbhtsbcjipai

Role of Device Identification and Manufacturer Usage Description in IoT security: A Survey

Noman Mazhar, Rosli Salleh, Muhammad Zeeshan, M. Muzaffar Hameed
2021 IEEE Access  
There are many ways to fingerprint the device, mostly using device network flows or device local attributes.  ...  INDEX TERMS Manufacturer usage description (MUD), Internet of Things (IoT), device identification (DI), software defined network (SDN), machine learning (ML), deep learning (DL).  ...  ACKNOWLEDGMENT The authors of this research would like to thank the anonymous reviewers for the valuable comments and constructive suggestions, and their insights to improve the quality of the manuscript  ... 
doi:10.1109/access.2021.3065123 fatcat:5gofmkoawbccvhum5zuo3i7vya

Applications in Security and Evasions in Machine Learning: A Survey

Ramani Sagar, Rutvij Jhaveri, Carlos Borrego
2020 Electronics  
learning, cost-efficiency and error-free processing.  ...  Even with the use of current sophisticated technology and tools, attackers can evade the ML models by committing adversarial attacks.  ...  All authors have read and agreed to the published version of the manuscript. Funding: This research received no external funding. Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/electronics9010097 fatcat:ttmpehdctjhbdk7arxgczl6224

HAWK: Rapid Android Malware Detection through Heterogeneous Graph Attention Networks [article]

Yiming Hei, Renyu Yang, Hao Peng, Lihong Wang, Xiaolin Xu, Jianwei Liu, Hong Liu, Jie Xu, Lichao Sun
2021 arXiv   pre-print
We model Android entities and behavioural relationships as a heterogeneous information network (HIN), exploiting its rich semantic metastructures for specifying implicit higher-order relationships.  ...  An incremental learning model is created to handle the applications that manifest dynamically, without the need for re-constructing the whole HIN and the subsequent embedding model.  ...  Heterogeneous information network (HIN) [15] , [16] , as a special case of graph neural network, has been widely adopted in many areas such as operating systems, Internet of Things and cyber-security  ... 
arXiv:2108.07548v1 fatcat:wizwynfcmfhi5fkkll5c4kaof4

LIPIcs : an Open-Access Series for International Conference Proceedings

Marc Herbstritt, Wolfgang Thomas
2016 ERCIM News  
Pavlovian learning is modelled to detect and learn to predict biologically-significant aversive and appetitive (emotional) stimuli which are key targets for attentional processing and for the organisation  ...  Random forest and deep neural networks show the best performance with a prediction accuracy of up to 92%.  ...  model of the application, i.e. the specification of the multi-cloud application requirements with respect to component interfaces, cloud deployment needs, etc.  ... 
doi:10.18154/rwth-2018-223393 fatcat:ddo7qz65l5b7peuksw2amaoxai

A comprehensive survey on machine learning for networking: evolution, applications and research opportunities

Raouf Boutaba, Mohammad A. Salahuddin, Noura Limam, Sara Ayoubi, Nashid Shahriar, Felipe Estrada-Solano, Oscar M. Caicedo
2018 Journal of Internet Services and Applications  
In this way, readers will benefit from a comprehensive discussion on the different learning paradigms and ML techniques applied to fundamental problems in networking, including traffic prediction, routing  ...  Machine Learning (ML) has been enjoying an unprecedented surge in applications that solve problems and enable automation in diverse domains.  ...  Acknowledgments We thank the anonymous reviewers for their insightful comments and suggestions that helped us improve the quality of the paper.  ... 
doi:10.1186/s13174-018-0087-2 fatcat:jvwpewceevev3n4keoswqlcacu

Survey of Generative Methods for Social Media Analysis [article]

Stan Matwin, Aristides Milios, Paweł Prałat, Amilcar Soares, François Théberge
2021 arXiv   pre-print
We included two important aspects that currently gain importance in mining and modeling social media: dynamics and networks.  ...  Networks, on the other hand, may capture various complex relationships providing additional insight and identifying important patterns that would otherwise go unnoticed.  ...  The work shown in [198] tries to quantify image sharing preferences and to build models that automatically predict users' personality in a cross-modal and cross-platform setting using Twitter and Flickr  ... 
arXiv:2112.07041v1 fatcat:xgmduwctpbddfo67y6ack5s2um

Enabling Integrity for the Compressed Files in Cloud Server

S.K Prashanth
2013 IOSR Journal of Computer Engineering  
This proof can be done by both the cloud and the customer and can be incorporated in the Service level agreement (SLA). Here we are encrypting the hash values and providing the more security.  ...  Cloud storage moves the users data to large data centers, which are remotely located and on which user does not have any control.  ...  Acknowledgment The work has been supported by the grants from the US Department of Energy (DEO) (DESC0004308) and the US National Science Foundation (NSF-IIS-0900970 and NSF-CNS-0831360).  ... 
doi:10.9790/0661-1240105 fatcat:suxx6aa5kneybiskk2z4n6guce

Social physics [article]

Marko Jusup, Petter Holme, Kiyoshi Kanazawa, Misako Takayasu, Ivan Romic, Zhen Wang, Suncana Gecek, Tomislav Lipic, Boris Podobnik, Lin Wang, Wei Luo, Tin Klanjscek (+3 others)
2021 arXiv   pre-print
, cooperation as a basis for civilised life, the structure of (social) networks, and the integration of intelligent machines in such networks.  ...  with social scientists, environmental scientists, philosophers, and more.  ...  Further vulnerabilities include the spread of disinformation or cyber-attacks.  ... 
arXiv:2110.01866v1 fatcat:ccfxyezl6zgddd6uvrxubmaxua

Program Book

2020 2020 5th International Conference on Universal Village (UV)  
It was found that the prediction accuracy of the models with 85% and 90% training sets could reach 84.62% and 88.89%, indicating the potential of applying machine learning algorithm to the prediction of  ...  To achieve the balance between computational cost efficiency and accuracy at the same time this study proposes to apply Attention-based Graph Neural Network (AGNN) to shortterm metro passenger flow prediction  ... 
doi:10.1109/uv50937.2020.9426196 fatcat:bikzcbilgbfp5jzssihjmswpua

Network resilience [article]

Xueming Liu, Daqing Li, Manqing Ma, Boleslaw K. Szymanski, H Eugene Stanley, Jianxi Gao
2022 arXiv   pre-print
Only in recent years, taking advantages of the network theory and lavish real data sets, network scientists have directed their interest to the real-world complex networked multidimensional systems and  ...  failures in infrastructure systems, and social convention changes in human and animal networks.  ...  An ecosystem may automatically restore itself from the species invasion or environmental changes, and a cellular network can automatically recover by changing the expression level of some specific genes  ... 
arXiv:2007.14464v2 fatcat:vyas2dqb4ngkpazcfvwkth7maa
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