Journal ArticleDOI
Artificial intelligence in cyber security: research advances, challenges, and opportunities
Zhimin Zhang,Huansheng Ning,Feifei Shi,Fadi Farha,Yang Xu,Jiabo Xu,Fan Zhang,Kim-Kwang Raymond Choo +7 more
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TLDR
A conceptual human-in-the-loop intelligence cyber security model is presented based on the existing literature on the applications of AI in user access authentication, network situation awareness, dangerous behavior monitoring, and abnormal traffic identification.Abstract:
In recent times, there have been attempts to leverage artificial intelligence (AI) techniques in a broad range of cyber security applications. Therefore, this paper surveys the existing literature (comprising 54 papers mainly published between 2016 and 2020) on the applications of AI in user access authentication, network situation awareness, dangerous behavior monitoring, and abnormal traffic identification. This paper also identifies a number of limitations and challenges, and based on the findings, a conceptual human-in-the-loop intelligence cyber security model is presented.read more
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Metaverse beyond the hype: Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy
Yogesh K. Dwivedi,Laurie Hughes,Abdullah M. Baabdullah,Samuel Ribeiro-Navarrete,Mihalis Giannakis,Mutaz M. Al-Debei,Denis Dennehy,Bhimaraya A. Metri,Dimitrios Buhalis,Christy M. K. Cheung,Kieran Conboy,Ronan Doyle,Ram Janam Dubey,Vincent Dutot,Reto Felix,Dinesh Goyal,Anders Gustafsson,Chris Hinsch,Ikram Jebabli,Marijn Janssen,Young-Gab Kim,Jooyoung Kim,Stefan Koos,David Kreps,Nir Kshetri,Vikram Kumar,Keng-Boon Ooi,Savvas Papagiannidis,Ilias O. Pappas,Ariana Polyviou,Sang-Min Park,Neeraj Pandey,Maciel M. Queiroz,Ramakrishnan Raman,Philipp A. Rauschnabel,A Ranade Shirish,Marianna Sigala,Konstantina Spanaki,Garry Wei-Han Tan,M. K. Tiwari,Giampaolo Viglia,Samuel Fosso Wamba +41 more
TL;DR: The potential socio-economic impact of a fully functional persistent cross-platform metaverse has been examined in detail by combining the informed narrative and multi-perspective approach from experts with varied disciplinary backgrounds as discussed by the authors .
Journal ArticleDOI
The role of artificial intelligence and machine learning in wireless networks security: principle, practice and challenges
Journal ArticleDOI
A deeper look into cybersecurity issues in the wake of Covid-19: A survey
TL;DR: In this paper , the authors analyzed the Coronavirus (COVID-19) crisis from the angle of cyber-crime, highlighting the wide spectrum of cyberattacks that occurred around the world.
Journal ArticleDOI
XAI for Cybersecurity: State of the Art, Challenges, Open Issues and Future Directions
Gautam Srivastava,Rutvij H. Jhaveri,Sweta Bhattacharya,Sharnil Pandya,Rajeswari,Praveen Kumar Reddy Maddikunta,Gokul Yenduri,Jon G. Hall,Mamoun Alazab,Thippa Reddy Gadekallu +9 more
TL;DR: This dissertation aims to provide a history of information technology in India and investigates its role in the development and implementation of e-commerce.
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Multi-Controller Deployment in SDN-Enabled 6G Space-Air-Ground Integrated Network
TL;DR: A hierarchical multi-controller deployment strategy of an SDN-based 6G SAGIN, and a switch migration strategy oriented toward load balancing is proposed to improve the network performance.
References
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Journal ArticleDOI
One Pixel Attack for Fooling Deep Neural Networks
TL;DR: This paper proposes a novel method for generating one-pixel adversarial perturbations based on differential evolution (DE), which requires less adversarial information (a black-box attack) and can fool more types of networks due to the inherent features of DE.
Posted Content
BadNets: Identifying Vulnerabilities in the Machine Learning Model Supply Chain.
TL;DR: It is shown that outsourced training introduces new security risks: an adversary can create a maliciously trained network (a backdoored neural network, or a BadNet) that has state-of-the-art performance on the user's training and validation samples, but behaves badly on specific attacker-chosen inputs.
Journal ArticleDOI
A survey of network anomaly detection techniques
TL;DR: This paper presents an in-depth analysis of four major categories of anomaly detection techniques which include classification, statistical, information theory and clustering and evaluates effectiveness of different categories of techniques.
Journal ArticleDOI
One pixel attack for fooling deep neural networks
TL;DR: In this paper, a method for generating one-pixel adversarial perturbations based on differential evolution (DE) is proposed, which requires less adversarial information (a black-box attack) and can fool more types of networks due to the inherent features of DE.
Posted Content
Generating Adversarial Malware Examples for Black-Box Attacks Based on GAN
Weiwei Hu,Ying Tan +1 more
TL;DR: The superiority of MalGAN over traditional gradient based adversarial example generation algorithms is that MalGAN is able to decrease the detection rate to nearly zero and make the retraining based defensive method against adversarial examples hard to work.