[Apologies for multiple postings] https://www.journals.elsevier.com/journal-of-parallel-and-distributed-comput... ******************************************************************************************************************** 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: January 20, 2019 First-roundpass notification (for a rejected paper): February 20, 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 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/journal-of-parallel-and-distributed-comput... 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: http://evise.com/evise/jrnl/jpd 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.cn; gracelq628@126.com Dr. Md Zakirul Alam Bhuiyan Department of Computer and Information Sciences, Fordham University, USA Email: mbhuiyan3@fordham.edu; zakirulalam@gmail.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 -- Dr. Qin Liu College of Computer Science and Electronic Engineering Hunan University Changsha, Hunan Province,P.R. China, 410082 Mobile: +86-13548577157 Email: gracelq628@hnu.edu.cn; gracelq628@126.com Homepage: http://res.hnu.edu.cn/hbs/lq/