[Call for Papers] 8th IEEE Conference on Communications and Network Security (CNS 2020) Avignon, France -- 29 June-1 July 2020 http://cns2020.ieee-cns.org/
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후세인 라쉬드[RASHEED HUSSAIN]
** Deadline Extended: February 9, 2020 (11:59 p.m. American Samoa time) **
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8th IEEE Conference on Communications and Network Security (CNS 2020) Avignon, France -- 29 June-1 July 2020 http://cns2020.ieee-cns.org/
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The IEEE Conference on Communications and Network Security (CNS) is a premier forum for cyber security researchers, practitioners, policy makers, and users to exchange ideas, techniques and tools, raise awareness, and share experiences related to all practical and theoretical aspects of communications and network security.
The conference seeks submissions from academia, government, and industry presenting novel research results in communications and network security.
Particular topics of interest include, but are not limited to:
* Anonymity and privacy technologies
* Biometric authentication and identity management
* Censorship countermeasures and privacy
* Combating cyber-crime (anti-spam, anti-phishing, anti-fraud
techniques, etc.)
* Computer and network forensics
* Cyber deterrence strategies
* Data and application security
* Data protection and integrity
* Game-theoretic security technologies
* Implementation and evaluation of networked security systems
* Information-theoretic security
* Intrusion detection, prevention, and response
* Key management, public key infrastructures, certification,
revocation, and authentication
* Malware detection and mitigation
* Security metrics and models
* Physical-layer and cross-layer security technologies
* Security and privacy for big data
* Security and privacy for data and network outsourcing services
* Security and privacy for mobile and wearable devices
* Security and privacy in cellular networks
* Security and privacy in cloud and edge computing
* Internet Security: Protocols, standards, measurements
* Security and privacy in crowdsourcing
* Security and privacy in cyber-physical systems
* Security and privacy in emerging wireless technologies and
applications (dynamic spectrum sharing, cognitive radio networks,
millimeter wave communications, MIMO systems, smart/connected
vehicles, UAS, etc.)
* Security and privacy in peer-to-peer and overlay networks
* Security and privacy in WiFi, ad hoc, mesh, sensor, vehicular,
body-area, disruption/delay tolerant, and social networks
* Security and privacy in smart cities, smart and connected health,
IoT, and RFID systems
* Security for critical infrastructures (smart grids,
transportation systems, etc.)
* Security for future Internet architectures and designs
* Security for software-defined and data center networks
* Security in machine learning
* Social, economic, and policy issues of trust, security, and privacy
* Traffic analysis
* Usable security and privacy
* Web, e-commerce, m-commerce, and e-mail security
Accepted and presented technical papers will be published in the
2020 IEEE CNS Proceedings and submitted to IEEE Xplore(R) as well as other Abstracting and Indexing (A&I) databases. See the website for detailed instructions and submission rules and regulations and for author requirements for accepted papers.
IMPORTANT DATES
Paper submission deadline: February 9, 2020 [extended]
Notification: March 23, 2020
Final paper submission: March 30, 2020
SUBMISSION
GENERAL CHAIR
Abderrahim BENSLIMANE, University of Avignon, France GENERAL CO-CHAIR Patrizio Campisi, Roma TRE University, Italy
PROGRAM CHAIRS
Sara Foresti, Università degli Studi di Milano, Italy Yong Guan, Iowa State University, USA
PUBLICATION CHAIRS
Rasheed Hussain, Innopolis University, Russia Aziz Mohaisen, University of Central Florida, USA Sun Wen, Northwestern Polytechnical University, China Francesco De Pellegrini, Avignon University, France
Rasheed Hussain, PhD
Muhammad Ahmad
"Interactive Deep Learning for Hyperspectral Images"
Special Issue Information
Deep models have achieved remarkable results in many real-world applications based on quality-labeled training samples. However, accruing reliable training samples is expensive in many real-world applications, particularly in the remote sensing domain. Therefore, there is a need to develop interactive deep schemes that can help to attain reliable, informative, and heterogeneous samples for learning. For this Special Issue of Remote Sensing, we aim to present a collection of articles related to “Interactive Deep Learning for Hyperspectral Images” including, but not limited to, the following topics:
1. Investigation of the behavior and performance of deep models in terms of the computational cost and generalized performance for both on-shelf and novel classification methods under different experimental conditions.
2. Development of several novel strategies to limit the Hughes phenomenon for hyperspectral image classification by exploiting several on-shelf and novel sample selection methods. This includes the generation of a good spectral library, the development of suitable models to upscale the ground spectra to air and space-borne measurements, evolving application methodologies, and device algorithms for pre and post-processing hyperspectral cubes.
Guest Editors
Dr. Muhammad Ahmad
Dr. Adil Mehmood Khan
Dr. Diego Oliva
Dr. Omar Nibouche