Journal of Parallel and Distributed Computing

Security & Privacy in Social Big Data

SCOPE of the SI

The rapid development of social networks dramatically changes the way
people think, work, and interact. As more and more individual users
proactively generate, share, and exchange digital contents through
social media, social networks have become a key source of big
data. However, with such vast interconnectivity, convergence of
relationships, and shared user information comes increased security
and privacy concerns in social big data. On one hand, users carelessly
posting their personal information on social media which can easily
have their privacy breached. On the other hand, malicious attackers
may manipulate such information to make a profit.

There are two important security and privacy issues in social
networks. The first is how to effectively utilize social data while
protecting user privacy. The second is how to guarantee the
authenticity of social data for an in-depth data analysis. Traditional
security mechanisms and models tailored to small-scale or isomorphic
data are inadequate to securing social big data which exhibit enormous
volume and diverse formats. Therefore, how to develop scalable
cryptographic algorithms/protocols and lightweight data
mining/organization/optimization models to solve the security and
privacy challenges becomes crucial for the successful application of
social big data.

About the Topics of Interest 

Any topic related to security and privacy aspects, e.g., access
control, authorization, authorization, and anonymization, for big data
and social networks, 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) Fundamentals and Technologies in Social Networks and Big Data 
    Social network models and platforms
    Social network architectures and data models
    Searching and discovery
    Architectures for big data 
    Machine learning and deep learning
    Scalable computing models, theories, and algorithms
    Content analysis and data mining 
    Novel and incentive applications of social big data in various fields 
    Big data transformation, and presentation
    Big data acquisition, integration, cleaning, and best practices
    Large-scale data collection and filtering problem
    Sparse data modeling, compressing, and sensing

 (ii) Security and Privacy in Social Networks 
    Accountability and audit in social networks
    Authentication and authorization in cloud services; 
    Secure access to social networks; 
    Big data privacy model in social networks
    New trust mechanism in social networks
    Privacy and security preserving protocol for social networks
    Applications of cryptography in social networks 
    Secure data management in social networks;
    Privacy modeling in social networks
    Privacy-preserving social data publishing
    Private information retrieval in social networks 
    Measurement studies of security & privacy issues in social networks
    Combating cyber-crime: anti-phishing, anti-spam, anti-fraud techniques

 (iii) Security and Privacy in Big Data 
    Access control models and anonymization algorithms in big data
    Cryptography in big data and cloud computing 
    Data protection and integrity in big data
    Secure searching in big data
    Secure outsourcing computing in big data
    System designs for secure data storage in big data
    Security model and architecture for big data; 
    Software and system security for big data; 
    Scalability and auditing for big data; 
    Security and privacy in big data sharing and visualization; 
    Security and privacy in big data mining and analytics; 
    Data-centric security and data classification; 
    Privacy in big data applications and services; 
    Privacy in big data integration and transformation;
    Privacy in big data storage management; 
    Threat detection using big data analytics; 
    Big data privacy policies and standards

 (iv) System, Information and Network Security 
    High performance security systems
    Secure system implementation
    Database and system security
    Secure operating systems
    Cryptographic primitives and security protocols 
    Disaster recovery
    Provable security
    Key distribution and management
    Intrusion detection and prevention
    Privacy, anonymity and traceability
    Identity management
    Access controls and security mechanisms
    Web & applications security
    Secure routing and network management
    Security in content delivery networks
    Security in high speed network
    Security in optical systems and networks
    Network monitoring
    Network security policies

Important Dates 

        Submission deadline: December 31, 2018
        First-roundpass notification (for a rejected paper): January 31, 2019
        Acceptance/rejection notification: September 1, 2019 
        Publication materials due: December 31, 201

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 25 pages (one-column, at least 10pt fonts) including
figures, tables, and references. A detailed submission guideline is
available as "Guide to Authors" at:

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

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'C , Corresponding Guest Editor
College of Computer Science and Electronic Engineering, Hunan University, China 

Dr. Md Zakirul Alam Bhuiyan 
Department of Computer and Information Sciences, Fordham University, USA 

Dr. Jiankun Hu 
School of Engineering and IT, University of New South Wales, Australia 

Dr. Jie Wu 
Department of Computer and Information Sciences, Temple University, USA