Wireless Communications and Mobile Computing

Computational Intelligence Techniques for Information Security and Forensics in IoT Environments


Publishing date
01 May 2021
Status
Closed
Submission deadline
18 Dec 2020

Lead Editor

1Nanjing University of Information Science & Technology, Nanjing, China

2Lakehead University, Thunder Bay, Canada

3National Dong Hwa University, Hualien, Taiwan

4Sejong University, Seoul, Republic of Korea

5University of Milano, Crema, Italy

6Indian Institute of Technology, Jodhpur, India

This issue is now closed for submissions.

Computational Intelligence Techniques for Information Security and Forensics in IoT Environments

This issue is now closed for submissions.

Description

As a popular paradigm, the Internet-of-Things (IoT) usually consists of numerous smart devices interconnected with other devices, application services, and systems by wireless networks and protocols. These smart devices often collect a massive amount of data from real-world objects via sensors and process, transmit and manage these data to networks for a variety of practical applications such as smart cities, smart homes, autonomous transportation, and health supervision. This raises two problems that must be addressed urgently; how to ensure the security of these IoT data, and how to implement the forensics of these data if they suffer illegal copying, tampering, and forgery attacks in IoT environments.

Computational intelligence techniques have shown the desirable efficiency and effectiveness in data processing and mining, and they have attracted a lot of attention. Recently, a typical example is deep convolutional neural networks (CNN) and its derivates, such as Faster Region-based CNN (Faster R-CNN) and Generative Adversarial Networks (GAN). These examples have gained great success in many basic computer vision tasks including automatic image representation generation, semantic segmentation and classification, object detection and tracking, and data restoration. They have outperformed traditional methods significantly. Due to the promising performances of computational intelligence techniques in data processing and mining tasks of computer vision, it might be reasonable and effective to explore these computational intelligence techniques to address the problems of information security and forensics in IoT environments.

The aim of this Special Issue is to solicit original research articles and review articles that focus on the challenges and issues of information security and forensics in IoT environments by computational intelligence techniques and models.

Potential topics include but are not limited to the following:

  • Computational intelligence theories and methodologies for IoT data security
  • Deep learning feature-based IoT data search
  • Perceptual visual content representation, modelling, and understanding in IoT
  • Privacy data control and management in IoT
  • Steganography and steganalysis by Generative Adversarial Networks (GAN) or other deep learning networks in IoT
  • Secret image sharing/visual cryptography by computational intelligence techniques in IoT
  • Digital watermarking schemes by deep learning techniques in IoT
  • Digital forensics by deep learning techniques in IoT
  • Forensics of deep fake faces generated by GAN
  • Fingerprint liveness forensics in IoT
  • IoT copy data/tamper data detection by computational intelligence techniques
  • Identity authentication in IoT
  • Blockchain techniques for tamper-proofing of IoT data or other security applications

Articles

  • Special Issue
  • - Volume 2021
  • - Article ID 6640106
  • - Research Article

Antiforensics of Speech Resampling Using Dual-Path Strategy

Diqun Yan | Yongkang Gong | Tianyun Liu
  • Special Issue
  • - Volume 2021
  • - Article ID 6631585
  • - Research Article

Fingerprinting Indoor Positioning Method Based on Kernel Ridge Regression with Feature Reduction

Yanfen Le | Shijialuo Jin | ... | Heng Yao
  • Special Issue
  • - Volume 2021
  • - Article ID 8859088
  • - Research Article

Deep Camera-Aware Metric Learning for Person Reidentification

Wei Liu | Ping Liang | ... | Xin Xu
  • Special Issue
  • - Volume 2020
  • - Article ID 8847651
  • - Research Article

SK-FMYOLOV3: A Novel Detection Method for Urine Test Strips

Rui Yang | Yonglin Zhang | ... | Xiaonan Luo
  • Special Issue
  • - Volume 2020
  • - Article ID 8823300
  • - Research Article

An Empirical Study on GAN-Based Traffic Congestion Attack Analysis: A Visualized Method

Yike Li | Yingxiao Xiang | ... | Zhen Han
  • Special Issue
  • - Volume 2020
  • - Article ID 8892349
  • - Research Article

Blind Photograph Watermarking with Robust Defocus-Based JND Model

Chunxing Wang | Xiaoxiao Li | ... | Wenbo Wan
  • Special Issue
  • - Volume 2020
  • - Article ID 8882655
  • - Research Article

Using the Same PayWord Chains Associated with a Single Account from Multiple Mobile Devices

Tao-Ku Chang | Fu-Hao Yeh
  • Special Issue
  • - Volume 2020
  • - Article ID 8849536
  • - Research Article

Trust-Based Missing Link Prediction in Signed Social Networks with Privacy Preservation

Huaizhen Kou | Fan Wang | ... | Yuwen Liu
  • Special Issue
  • - Volume 2020
  • - Article ID 8870467
  • - Research Article

Robust Image Hashing with Low-Rank Representation and Ring Partition

Zhenjun Tang | Zixuan Yu | ... | Xianquan Zhang
  • Special Issue
  • - Volume 2020
  • - Article ID 8812087
  • - Research Article

A New Steganography Method for Dynamic GIF Images Based on Palette Sort

Jingzhi Lin | Zhenxing Qian | ... | Guorui Feng
Wireless Communications and Mobile Computing
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Acceptance rate11%
Submission to final decision151 days
Acceptance to publication66 days
CiteScore2.300
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