Big Data in Distributed Analytics, Cybersecurity, Cyber Warfare and Digital Forensics

Big Data can reduce the processing time of large volumes of data in the distributed computing environment using Hadoop. It also can predict potential cybersecurity breaches, help stop cyber attacks, and facilitate post-breach digital forensic analysis. This paper introduces Big Data applications in distributed analytics, general cybersecurity (general cyber threats, cyber attacks, and cyber security in cloud computing, etc.), cyber warfare, cyber defense, and digital forensics. Some methods and technology progress in these cyberareas are presented. Some challenges of Big Data applications in the areas and solutions to part of the challenges are also discussed.

[1]  Jung ho Eom.  Roles and Responsibilities of Cyber Intelligence for Cyber Operations in Cyberspace , 2014 .

[2]  Josiah Dykstra,et al.  Forensic Collection of Electronic Evidence from Infrastructure-As-a-Service Cloud Computing , 2012 .

[3]  Erin Smith Crabb.  "Time for Some Traffic Problems": Enhancing E-Discovery and Big Data Processing Tools with Linguistic Methods for Deception Detection , 2014, J. Digit. Forensics Secur. Law.

[4]  Dursun Delen,et al.  Leveraging the capabilities of service-oriented decision support systems: Putting analytics and big data in cloud , 2013, Decis. Support Syst..

[5]  Juha Heinanen,et al.  OF DATA INTENSIVE APPLICATIONS , 1986 .

[6]  Su-Hyun Kim,et al.  Block Access Token Renewal Scheme Based on Secret Sharing in Apache Hadoop , 2014, Entropy.

[7]  C. L. Philip Chen,et al.  Data-intensive applications, challenges, techniques and technologies: A survey on Big Data , 2014, Inf. Sci..

[8]  Madjid Merabti,et al.  Secure Cloud Computing for Critical Infrastructure: A Survey , 2012 .

[9]  Kapil Govil,et al.  An Effective Reliability Efficient Algorithm for Enhancing the Overall Performance of Distributed Computing System , 2013 .

[10]  Sherali Zeadally,et al.  US Policy on Active Cyber Defense , 2014 .

[11]  E. Châtelet,et al.  The Impact of Natural Disasters on Critical Infrastructures: A Domino Effect-based Study , 2014 .

[12]  Alvaro A. Cárdenas,et al.  Big Data Analytics for Security , 2013, IEEE Security & Privacy.

[13]  Hanku Lee,et al.  DIVE-C: Distributed-parallel Virtual Environment on Cloud Computing Platform , 2013, MUE 2013.

[14]  Zaigham Mahmood,et al.  Data Location and Security Issues in Cloud Computing , 2011, 2011 International Conference on Emerging Intelligent Data and Web Technologies.

[15]  Helge Janicke,et al.  Cyber warfare: Issues and challenges , 2015, Comput. Secur..

[16]  U. S. Representative,et al.  Cyberspace and the Changing Nature of Warfare , 2008 .

[17]  Umesh Kumar,et al.  A Comprehensive Review of Straggler Handling Algorithms for MapReduce Framework , 2014 .

[18]  Simson L. Garfinkel,et al.  Lessons learned writing digital forensics tools and managing a 30TB digital evidence corpus , 2012, Digit. Investig..

[19]  Catalin Boja,et al.  Distributed Parallel Architecture for "Big Data" , 2012 .

[20]  Douglas Schweitzer.  Incident Response: Computer Forensics Toolkit , 2003 .

[21]  Bimal Kumar Mishra,et al.  Cyber Warfare: Worms’ Transmission Model , 2014 .

[22]  Ivan Barać.  INTEGRATED PROACTIVE FORENSICS MODEL IN NETWORK INFORMATION SECURITY , 2014 .

[23]  Junho Choi,et al.  Ontology-based access control model for security policy reasoning in cloud computing , 2013, The Journal of Supercomputing.

[24]  Marlena J. Gaul.  Big Data at Work: Dispelling the Myths, Uncovering the Opportunities , 2014 .

[25]  Žaklina Spalević.  CYBER SECURITY AS A GLOBAL CHALLENGE TODAY , 2014 .