Secu_AgeBigData 2019 : Combating Security Challenges in the Age of Big Data
Call For Papers
******** CALL FOR BOOK CHAPTER ********
BOOK TITLE: Combating Security Challenges in the Age of Big Data
To be Published by SPRINGER
The incentive for joining the big data and advanced analytics is no longer in doubt for businesses and ordinary users alike. Technology giants like Google, Microsoft, Amazon, Facebook, Apple, and companies like Uber, Airbnb, NVIDIA, Expedia, and so forth are continuing to explore new ways to collect and analyze big data to provide their customers with interactive services and new experiences. With any discussion of big data, security is not, however, far behind. Large scale data breaches and privacy leaks at governmental and financial institutions, social platforms, power grids, and so forth, are on the rise that cost billions of dollars. This book addresses the key security challenges in the big data centric computing and network systems, and discusses how to tackle them using a mix of conventional and state-of-the-art techniques. The book explains how the security needs and implementations are inherently different at different stages of the big data centric system, namely at the point of big data sensing and collection, delivery over existing networks, and analytics at the data centers. Thus, the book sheds light on how conventional security provisioning techniques like authentication and encryption need to scale well with all the stages of the big data centric system to effectively combat security threats and vulnerabilities. The book also uncovers the state of the art technologies like deep learning and blockchain which can dramatically change the security landscape in the big data era.
Tentative Table of Contents:
Part I: Cyber Security Challenges in the Big Data Era
1. Security Risk Modeling: Definitions, Methodologies, Metrics and Tools
2. Conventional Cyber Defense Techniques: Cryptography and its applications
3. Model-Based Threat/Vulnerability Assessment and Penetration Testing
4. Security Challenges in Next Generation Cyber Physical Systems, Internet-of-Things, and Cloud Computing in the Age of Big Data
5. Social, Political, and Business Impact: cryptocurrency and smart healthcare as case studies
Part II: Threat Counteraction in Next Generation Computing and Networking Systems
6. Big Data Analytics for Cyber Defense
7. Securing Big Data Gathering and Analytics in the Internet-of-Things: State of the Art
8. Smart/Intelligent Firewalls, Intrusion Prevention and Detection Systems Powered by Deep Machine Learning
9. Procedures, Methods and Technologies for Designing Secure and Resilient Heterogeneous Cloud Computing Platforms at centralized data centers and network edge
10. Blockchain Beyond Cryptocurrency: a public ledger framework for secure communication in next generation cyber physical systems such as the IoT
The emergence of big data, at the moment of capturing and gathering from the Internet-of-Things (IoT) sensing plane to delivery over existing networks to the cloud computing data centers for analytics has opened up countless opportunities as well as security challenges. To combat the security challenges of the next generation heterogeneous computing/network systems in the age of big data has an increasing impact on the users’ privacy in terms of leaking sensitive data with or without their knowledge. Examples of such leakage can comprise personal information collected from smart homes or even crowdsourcing to highly critical information of smart power grids. It is, indeed, a highly cross-discipline topic with many challenges and open issues, including how to intelligently identify and thwart the cyber-physical threats using the state-of-the-art techniques including Artificial Intelligence (AI) such as deep learning methodologies.
In such a very current field of research and engineering, the list of “hot-topics” include:
- Convergence between Cyber and Physical Security
- Emerging Cloud Computing and Internet-of-Things (IoT) security issues
- Sensor networks and smart devices for security
- Cyber-security of Industrial Control System (ICS)
- Interdependency analysis of real-time gathering/analytics of big data and security
- Socio-political and business impact of big data security
- Attack/Penetration testing and other simulation techniques for next generation computing/networking security evaluation
- Intelligent intrusion detection and prevention systems power by AI
- Blockchain for security beyond cryptocurrencies
- Applications, case-studies and industrial experience reports in cyber-physical systems that include smart homes, smart cities, smart healthcare, and smart industry (i.e., industry 4.0).
Because of the wide dimensions of security challenges listed above, a comprehensive/exhaustive list is difficult to sketch, particularly given that the new technologies coupled with new/zero-day threats are continuing to emerge. The volume, variety, velocity, and veracity of the big data add to a tremendous complexity to the existing methods to model security provisioning to users. The big data, therefore, stimulates research and engineering initiatives in the cyber security domain. From a theoretical perspective, various areas related to design-for-security need to be explored in addition to the existing computing/networking frameworks that include next generation cloud computing platforms in the edge (exploiting Mobile Edge Computing (MEC), Unmanned Aerial Vehicle (UAV) based computing platforms, and so forth). From a cross-discipline point of view, rapidly evolving AI algorithms pave the way to new scenarios to incorporate intelligence into the MECs, UAVs, and so forth. Furthermore, blockchain based technologies are pushing the security paradigms beyond the realm of cryptocurrencies like bitcoin. Researchers are exploring means to exploit blockchains to design new security and privacy frameworks that may be fused with cyber physical systems like the IoT in the near future. Therefore, it is critical to evaluate how these emerging paradigms and the most current research developments such as deep learning, big data analytics, information fusion, early warning systems, and blockchains could help improve the security and resilience of the next generation computing and networking systems.
Proposal Submission: August 15, 2018
First Submission: November 15, 2018
Return Reviewed Chapters: February 25, 2019
Final Chapters Submission: April 15, 2019
Tentative Publications: Last quarter of 2019
Each manuscript should preferably be written in a tutorial manner with enough details so that it can be easily accessible to the readers outside the specialty of the area. Expected manuscript length is between 7,000 to 12,000 words. Longer manuscripts may be allowed based on the topic and need. Manuscripts submitted for the book must be original, must not be previously published or currently under review anywhere. The manuscript must be prepared with MS-Office (doc or docx). Kindly do not use any special formatting or macro for the submission version, doc or docx file. General guideline is: Use A4 page with 1 inch (or, 2.54 cm) margin on all sides, single column format, 1.5 line spacing with 11 point sized font, Times New Roman. References should be cited within the text with numbers in sequence like , , , …. An all-in-one PDF file may be submitted for the initial version however, if the chapter is accepted, this formatting style must be followed and MS-Office file (doc, docx) must be supplied.
Please email to both editors at email@example.com and firstname.lastname@example.org (COPY the exact email addresses from here)
Al-Sakib Khan Pathan (Southeast University, Dhaka, Bangladesh. Email: email@example.com)
Zubair Md Fadlullah (Tohoku University, Japan. Email: firstname.lastname@example.org)