Security and Communication Networks

Multimodality Data Analysis in Information Security


Publishing date
01 Aug 2021
Status
Closed
Submission deadline
26 Mar 2021

Lead Editor
Guest Editors

1Harbin Engineering University, Harbin, China

2Carnegie Mellon University, Pittsburgh, USA

3Nanjing University of Science and Technology, Nanjing, China

This issue is now closed for submissions.
More articles will be published in the near future.

Multimodality Data Analysis in Information Security

This issue is now closed for submissions.
More articles will be published in the near future.

Description

As modern embedded devices, communication manufacture, and Internet technology have been significantly developed in the last decade, massive amounts of multimodality data can be easily acquired from electronic sensors, computers, mobile terminals, and various networks made up by them (e.g. the Internet, IoT, etc). Correspondingly, issues of information security in data exploitation and analysis inevitably arise.

Generally, multimodality data contains much more potential information available and is capable of providing an enhanced analytical result compared to mono-source data. The way to combine the data acquired from diverse sources suitably plays a crucial role in multimodality data analysis and is worth investigating. In addition, considering that multimodality data usually belongs to big data in practice, researchers have developed some technologies based on multimodal learning to enhance human analysis effectively and quickly at a low cost. The study of multimodal learning in information security has been attracting increasing numbers of researchers and practitioners in both academia and industry.

Original research contributions and review articles on multimodality data analysis and derivative issues of information security are solicited for the Special Issue. Research devoted to the improvement and optimization of the existing multimodality data analysis methods in information security, as well as work on new models, theories, and approaches for multimodality data, are encouraged.

Potential topics include but are not limited to the following:

  • Multimodal source or sensor data fusion theory and application in information security
  • Multimodal learning in cyber security, e.g. threat detection, malicious attack detection and identification, malware detection and classification, network analysis, endpoint protection, and vulnerability assessment, etc.
  • Multimodality data representation, alignment, fusion, and co-learning
  • Multimodality machine learning and data analysis
  • Multimodal adversarial training for attacks and defence

Articles

  • Special Issue
  • - Volume 2021
  • - Article ID 9975912
  • - Research Article

A Data Aggregation Privacy Protection Algorithm Based on Fat Tree in Wireless Sensor Networks

Cheng Li | Guoyin Zhang | ... | Xin Zhao
  • Special Issue
  • - Volume 2021
  • - Article ID 5599962
  • - Research Article

Information Security Field Event Detection Technology Based on SAtt-LSTM

Wentao Yu | Xiaohui Huang | ... | Xiang Li
  • Special Issue
  • - Volume 2021
  • - Article ID 9968905
  • - Research Article

Differentially Private Web Browsing Trajectory over Infinite Streams

Xiang Liu | Yuchun Guo | ... | Yishuai Chen
  • Special Issue
  • - Volume 2021
  • - Article ID 9997641
  • - Research Article

A Vulnerability Detection System Based on Fusion of Assembly Code and Source Code

Xingzheng Li | Bingwen Feng | ... | Mingjin He
  • Special Issue
  • - Volume 2021
  • - Article ID 6689486
  • - Research Article

Permission Sensitivity-Based Malicious Application Detection for Android

Yubo Song | Yijin Geng | ... | Wei Shi
  • Special Issue
  • - Volume 2021
  • - Article ID 9916461
  • - Research Article

Meteorological Satellite Operation Prediction Using a BiLSTM Deep Learning Model

Yi Peng | Qi Han | ... | Xiaohu Feng
  • Special Issue
  • - Volume 2021
  • - Article ID 6658066
  • - Research Article

Cache Pollution Detection Method Based on GBDT in Information-Centric Network

Dapeng Man | Yongjia Mu | ... | Wei Wang
  • Special Issue
  • - Volume 2021
  • - Article ID 9941464
  • - Research Article

Explainable Fraud Detection for Few Labeled Time Series Data

Zhiwen Xiao | Jianbin Jiao
  • Special Issue
  • - Volume 2021
  • - Article ID 6663028
  • - Research Article

Project Gradient Descent Adversarial Attack against Multisource Remote Sensing Image Scene Classification

Yan Jiang | Guisheng Yin | ... | Qingan Da
  • Special Issue
  • - Volume 2021
  • - Article ID 9954957
  • - Research Article

EOM-NPOSESs: Emergency Ontology Model Based on Network Public Opinion Spread Elements

Guozhong Dong | Weizhe Zhang | ... | Shuaishuai Tan
Security and Communication Networks
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Acceptance rate53%
Submission to final decision52 days
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CiteScore3.300
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Impact Factor1.968
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Article of the Year Award: Outstanding research contributions of 2021, as selected by our Chief Editors. Read the winning articles.