BDA4CID 2024
A Workshop at 2024 IEEE International Conference on Big Data (IEEE Big Data 2024)
December 15th - 18th, 2024, Online (Washington DC, USA)
Online this year
Dear All, due to personal circumstances we are making this workshop Online this year. We hope this doesn’t discourage you from submitting your work.
Outline
We’d like to continue the success of the International Workshops on Big Data Analytics for Cyber Intelligence and Defense (BDA4CID 2017) at the IEEE Big Data 2017 Conference in Boston, USA, Big Data Analytics for Cyber Intelligence and Defense (BDA4CID 2018) at the IEEE Big Data 2018 Conference in Seattle, USA, Big Data Analytics for Cyber Intelligence and Defense (BDA4CID 2019) at the IEEE Big Data 2019 Conference in Los Angeles, USA, the Big Data Analytics for Cyber Intellegence and Defence (BDA4CID 2020) held virtually and the Big Data Analytics for Cyber Intellegence and Defence (BDA4CID 2021) held virtually, and the Big Data Analytics for Cyber Intellegence and Defence (BDA4CID 2022) Osaka, Japan.
Cyber-attacks have posed real and wide-ranging threats for the information society. Detecting cyber-attacks becomes a challenge, not only because of the sophistication of attacks, but also because of the large scale and complex nature of today’s IT infrastructures.
When significant amounts of data is collected from computer systems operations and monitoring, data science and intelligent advanced analytics are necessary to correlate, learn and mine, interpret and visualize such data. To mitigate existing cyber threats, it is important that cyber-attack detection and security analysis take advantage of data science and advanced analytics. Big data provides a systemic approach, from capturing of IT operation data, through data processing and event correlation, to anomaly detection and response decision.
This Workshop will focus on the cutting-edge developments from both academia and industry, with a particular emphasis on novel techniques to capture, store and process the big-data from a wide range of sources in monitoring IT infrastructures, and in particular on the methodologies and technologies which can be applied to correlate, learn and mine, interpret and visualize the cyber security data.
This workshop is timely and interesting for researchers, academics and practitioners in big data processing and analytics, cyber security, cyber defense, security analytics, data mining and machine learning of security data, security information and event management, along with anomaly detection. The workshop is very relevant to the big data community, especially data mining, machine learning, cyber physical systems, computational intelligence, and will bring forth a lively forum on this exciting and challenging area at the conference.
Research Topics
The workshop only considers well-written manuscripts that describe original, unpublished, state-of-the-art research and practical work. Indicative topics for the workshop are as follows:
Cyber security analytics
- Big data analytics for cyber intelligence and anomaly detection
- Big data intelligence for combating advanced persistent threats (APT)
- Big data for cyber intelligence and cyber situational awareness
- Big data processing platforms for cyber security and defense
- Cyber security analytics for cloud computing
- Cyber security visualization
- Cyber threat intelligence and modeling
- Cyber defense/security operations centers
- Data mining and machine learning for cyber threat and security
- Log management for cyber security analytics
- Next-generation Security Information and Event Management (SIEM)
- Next-generation intrusion detection/prevention systems (IDS/IPS)
- Real-time event correlation for cyber security analytics
- Real-time monitoring of computer and network systems
- Security incident management for cyber security analytics
- Stream mining for cyber intelligence and anomaly detection
- Stream analytics for cyber intelligence and anomaly detection
- Vulnerability analysis and modelling
Social media analytics
- Social media data mining
- Sentiment analysis in social media networks
- Opinion mining in social media networks
- Natural language processing and text mining for social media data analysis
- Security and privacy issues in social media networks
- Fake news detection in social media networks
This year we are seeking papers which address the cybersecurity ‘data sharing paradox’ where organisations (including businesses, NGOs and government bodies) who possess datasets that could aid the development of better cyber-security are either unwilling, feel unable or are unable to share their data with others to solve the common problem. Papers could cover (but not limited to):
- Best practices in sharing data between companies and researchers
- Data schemas and structures to better enable sharing and multi-purpose usability
- New datasets for cyber-intelligence and defense
- Anonymization of datasets to remove company information
- Synthetic datasets which match the characteristics of real data
To contribute towards advances of knowledge, the workshop will solicit submissions of manuscripts from researchers and practitioners who are actively working in Big Data Analytics for Cyber Intelligence and Defense.
Paper Format
Papers should be formatted using the two column IEEE CS template and can be up to 10 pages (including references) in length using page size of 8.5” x 11”.
Formatting templates:
Submission webpage
Please submit your papers through the conference submission system here.
Review Process
Each submission will be peer reviewed by at least 2 peers.
Please note that the authors of each submitted paper will be expected to review one other paper.
Important Dates (All dates now firm)
| Oct 28, 2024 | Due date for full workshop papers submission |
| rolling | Notification of paper acceptance to authors |
| Nov 20,2024 | Camera-ready of accepted papers |
| Dec 15-18 2024 | Workshop (one day of) |
Workshop Program Co-Chairs
Dr Stephen McGough
Reader in Machine Learning
School of Computing Science
Newcastle University
United Kingdom
E-mail : stephen.mcgough@newcastle.ac.uk
Dr Amir Atapour-Abarghouei
Assistant Professor
Department of Computing Science
Durham University
Durham, DH1 3LE
United Kingdom
Email: Amir.Atapour-Abarghouei@durham.ac.uk
Prof David Wall
Professor
School of Law
University of Leeds
Leeds
United Kingdom
E-mail: d.s.wall@leeds.ac.uk
International Technical Committee
To be confirmed
| William Blanc | Florida Polytechnic University, USA |
| Johan Fernquist | Swedish Defence Research Agency, Sweden |
| Matthew Forshaw | Newcastle University, UK |
| Phil Jackson | Newcastle University, UK |
| Amirreza Niakanlahiji | University of Illinois at Springfield, USA |
| Nik Khadijah Nik Aznan | Newcastle University, UK |