Big Data and Cyber Security: Emerging Approaches and Applications
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Computer Science & Engineering".
Deadline for manuscript submissions: 20 November 2024 | Viewed by 2159
Special Issue Editors
Interests: high-performance computing; big data; cybersecurity; performance; resilience
Interests: parallel and distributed processing; big data; emerging technologies
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
With accelerated digitization, the amount of data being generated from various environments is rapidly increasing. With this rapid increase in the generation of diverse data, which exceeds a quintillion bytes per day, there is an extreme need for innovative technological advances to ensure their security. Alternatively, the power and knowledge behind the emergent solutions employed to secure data generated in business and academic environments reduce the time to response, facilitating the mitigation of and defense against existing and evolving cybersecurity threats.
This Special Issue focuses on advanced cybersecurity approaches and applications that address threats to the confidentiality, integrity, and availability of big data; it also discusses pioneering and emergent solutions that utilize the power of the meteoric rise in big data to analyze and resolve unprecedented security and privacy challenges and malicious threats in diverse environments.
We encourage original submissions from academia and industry on the most recent theoretical and applied advances, with a focus on how big data research fits broader cybersecurity objectives, and vice versa.
Topics of interest may include:
- Security research and threat intelligence;
- Real-time compliance;
- Security monitoring;
- Secure data storage;
- Data privacy;
- Big data cryptography;
- Access control and auditing;
- Intrusion and anomaly detection;
- Spamming and spoofing detection;
- Malware and ransomware detection;
- Software code security;
- Frameworks and architectures for big data security;
- Cloud security;
- Artificial intelligence (AI) security, machine learning, and big data analytics for cybersecurity.
Technical Committee Member:
Name: Elizabeth Bautista
Email: ejbautista@lbl.gov
Homepage: https://www.nersc.gov/about/nersc-staff/operations-technology/elizabeth-bautista/
Affiliation: Lawrence Berkeley National Laboratory
Interests: HPC; monitoring; cybersecurity; big data
Dr. Nitin Sukhija
Prof. Dr. Kuan-Ching Li
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Electronics is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- cybersecurity
- big data
- data science
- AI
- machine learning
- data analytics
- monitoring
- privacy
