Book title: Trust, Security, and Privacy for Big Data
Publisher: CRC Press
Editors: Alazab & Gupta (2021)

Description
The volume of data in the world is increasing exponentially, also has revolutionized the current digital ecosystem. The readily available large datasets foster AI and machine learning automated solutions. However, the data format and its collection from various sources not only introduce unprecedented challenges to different domains including IoT, manufacturing, smart cars, power grids etc, but at the same time highlights the security and privacy issues in this age of big data. One of the serious side effects of the digital age and big data is the growing risk in terms of Trust, Security and Privacy.

Many big data tools are open source and not designed with security in mind. The huge increase in big data leads to many data security concerns, as big data can enable “invasions of privacy and trust. Big Data is changing cyber security analytics by providing new tools and opportunities for leveraging large quantities of structured and unstructured data. The humongous scale of extraordinary scale, security and privacy in big data faces many challenges, such as generative adversary networks, efficient encryption and decryption algorithms, encrypted information retrieval, attribute-based encryption, attacks on availability, and reliability.

Big data provide a deeper understanding and better decision making based on largely collected and available operational data, hence, data security is cruital. The scope of this book is on how Big Data can improve cyber security best practices., i.e. safeguard confidentiality and security of sensitive personal information, as well as the integrity of data. The purpose is to offer a timely venue for researchers and industry partners in communications and networking domains to present and discuss their latest results in security and privacy-related work of big data.

Suggested Topics
Submissions are solicited on the following topics, but not limited to:



Visualization in Big Data and Data Science

Virtualization of Resources in Clouds

Deep NLP (natural language processing)

Regularization and Optimization Techniques

Forward and Backward Propagation

Effective feature embedding

Neural networks for graphs

Generative adversarial networks

Restricted Boltzmann Machine

Deep reinforcement learning

Relational modeling and prediction

Semantic knowledge-bases

Neural abstract machines and program induction

Deep learning architectures

Performance metrics

Model Selection and

Forward and Backward Propagations

Regularization and Optimization Techniques

Convolutional Networks

Recurrent Neural Networks

Fuzzy hashes and logic



Big Data Framework and Tools

Popular Frameworks

Popular Tools for quick prototyping

Deep Learning with GPUs

Deep Learning in the Cloud



Bigdata for Security

Malware identification, analysis and similarity

Representation and detection of social engineering attacks

Botnet identification and detection

Intrusion detection and response

Spam and phishing detection

Classification of sequences of system/network events

Security in social networks

Application of learning to computer forensics

Program representation

Learning in adversarial environments

Web Application

Security, Privacy, Trust and Safety

Mobile Computing, Internet of Things (IoT)

Cloud, Apps and Services, and their Security

Big Data architectures for network security

Detecting data and information leakage



Big Data and Cloud Computing

Big Data and IoT on the Cloud

IoT Services and ApplicationsSecurity, Privacy and Trust in IoT

Big Data Management

Cloud Computing Platforms, Applications and Management

Cloud Security and Privacy Management

Mobile Cloud Computing

Data Storage in Clouds


Important Dates
20 Mar 2021 — Deadline

1 Apr 2021 — Manuscript delivery to the publisher

Book Panel Advisors
Dr. Feras Awaysheh (University of Edinburg)

Dr. Smriti Bhatt (Texas A&M San Antonio)

Dr. Sudip Mittal (UNCW)

Dr. Mahmoud Abdelsalam (Manhattan College)

Dr. Yuan Cheng (CSU)

Dr. Amro Awad (North Carolina State University)

Dr. Thippa Reddy G (Vellore Institute of Technology)

Dr. Mohannad Alhanahnah (University of Wisconsin-Madison)

Dr. Izzat Ismadi (Texas A&M University-San Antonio)

Dr Ravi Vinayakumar (Prince Mohammad Bin Fahd University)

Dr. Keping Yu ( Weseda University)

Manuscript guidelines and submission:
Use A4 page with 1 inch (or, 2.54 cm) margin on all sides, single column format, 1.5 line spacing with 10 point sized font, Times New Roman.

References should be cited within the text with numbers in sequence like [1], [2], [3], ....

An all-in-one PDF file may be submitted for the initial version.

If the chapter is accepted, formatting style provided by CRC Press must be followed and Editable files for text (Tex / MS-Office file (doc, docx)) must be supplied.

The submission Web page is:

https://easychair.org/conferences/?conf=tspbigdata21

Contact Information:
Assoc/ Prof Mamoun Alazab: Charles Darwin University, Australia. alazab.m@ieee.org

Dr. Maanak Gupta: Tennessee Technological University, USA. mgupta@tntech.edu