Artificial Intelligence: The Security & Privacy Opportunities and Challenges for Emerging Applications

  in Special Issue   Posted on March 28, 2020

Information for the Special Issue

Submission Deadline: Mon 30 Nov 2020
Journal Impact Factor : 3.997
Journal Name : Future Generation Computer Systems
Journal Publisher:
Website for the Special Issue: https://www.journals.elsevier.com/future-generation-computer-systems/call-for-papers/the-security-privacy-opportunities
Journal & Submission Website: https://www.sciencedirect.com/journal/future-generation-computer-systems

Special Issue Call for Papers:

Introduction

In recent years, the collection, processing, and analysis of personal data have become greatly convenient and widespread, as the continuous advancement of emerging applications such as social networks, Internet of Things (IoT), and cloud computing. This also make sensitive information more vulnerable to abuses, and thus secure mechanisms and technologies tailored for emerging applications need to be explored urgently.

Artificial Intelligence (AI) with the benefits of enhancing efficiency and improving accuracy has been widely used in academia and industry. From a privacy and security angle, AI brings about both opportunities and challenges for emerging applications. On the one hand, AI can help interested parties to better protect privacy in challenging situations, improving the state-of-the-art of security solutions. On the other hand, AI also presents risks of opaque decision making, biased algorithms, and safety vulnerabilities, challenging traditional notions of privacy protection.

About the Topics of Interest

Any topic related to security and privacy aspects in AI and AI-enabled emerging applications with security and privacy will be considered. All aspects of design, theory and realization are of interest. The scope and interests for the special issue include but are not limited to the following list:

(i) Security & Privacy in AI

● Security AI modeling and architecture

● Secure multi-party computation techniques for AI

●Secure experiments, test-beds and prototyping systems for AI

● Novel cryptographic mechanism for AI

● Accelerated Machine Learning (ML) in a security environment

● Adversarial example (AE) research

● Generate Adversarial Network (GAN) research

● Attack and defense methods with AE

●Privacy-preserving ML

●Normative approaches to privacy in AI

●Security & privacy in robust statistics

● Security & privacy in online learning

●Adaptive side-channel attacks

● Security protocols for AI

●Security and privacy in data mining and analytics

(ii) AI-Enabled Secure Emerging Applications

● AI for IoT security

● Privacy persevering ML in social network

●AI for spam detection

●AI for phishing detection and prevention

●AI for botnet detection

●AI for intrusion detection and response

●AI for malware identification

●AI for authorship identification

●AI for multimedia data security

● AI for enhance Privacy-Enhancing Technologies (PETs)

● AI-driven personalization of privacy assistance

● Vulnerability testing through intelligent probing

● AI -driven simplification or summarization of privacy policies

● AI analysis of privacy regulations

●AI systems defending against multiple attack vectors

●Biometrics security

 

Important Dates

● Submission deadline: November 30, 2020

● First-round-pass notification (for a rejected paper): December 31, 2020

● Acceptance/rejection notification: July 31, 2021

● Publication materials due: December 31, 2021

Submission Format and Guideline

All submitted papers must be clearly written in excellent English and contain only original work, which has not been published by or is currently under review for any other journal or conference. Papers must not exceed 35 pages (one-column, at least 10pt fonts) including figures, tables, and references. A detailed submission guideline is available as “Guide to Authors” at:

https://www.elsevier.com/journals/future-generation-computer-systems/0167-739x/guide-for-authors

All manuscripts and any supplementary material should be submitted through Elsevier Editorial System (EES). The authors must select as “VSI: AISP” when they reach the “Article Type” step in the submission process. The EES website is located at:

https://www.evise.com/profile/#/FGCS/login

All papers will be peer-reviewed by at least three independent reviewers. Requests for additional information should be addressed to the guest editors.

 

Guest Editors

Dr. Qin Liu– Corresponding Guest Editor

College of Computer Science and Electronic Engineering, Hunan University, China

Email: gracelq628@.hnu.edu.cngracelq628@126.com

Dr. Guojun Wang

School of Computer Science and Cyber Engineering, Guangzhou University, China

Email: csgjwang@gzhu.edu.cncsgjwang@163.com

Dr. Jiankun Hu

School of Engineering and IT, University of New South Wales, Australia

Email: J.Hu@adfa.edu.au

Dr. Jie Wu

Department of Computer and Information Sciences, Temple University, USA

Email: jiewu@temple.edu

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