ICDM 2021

Data Mining and Machine Learning for Cybersecurity Workshop


Jointly held with the DL-CTI Workshop

December 7, 2021




Workshop


Data Mining and Machine Learning for Cybersecurity (DMC) workshop will be held in conjunction with The 2021 IEEE International Conference on Data Mining (ICDM2021, https://icdm2021.auckland.ac.nz/) on December 7-10, 2021.

DMC is jointly held with the DL-CTI workshop (https://www.dl-cti.org/). DMC workshop is a full-day event that includes three speakers. The workshop will be held on December 7, 2021.

Scope


In the past decades, cybersecurity threats have been among the greatest challenges for social development resulting in financial loss, violation of privacy, damages to infrastructures, etc. Organizations, governments, and cyber practitioners tend to leverage state-of-the-art Artificial Intelligence technologies to analyse, prevent, and protect their data and services against cyber threats and attacks. Due to the complexity and heterogeneity of security systems, cybersecurity researchers and practitioners have shown increasing interest in applying data mining methods to mitigate cyber risks in a wide range of security areas, such as malware detection and key player identification in an underground forum. To protect the cyber world, we need more effective and efficient algorithms and tools that are capable of automatically and intelligently analysing and classifying the massive amount of data in cybersecurity complex scenarios. This workshop will focus on empirical findings, methodological papers, and theoretical and conceptual insights related to data mining in the field of cybersecurity.

Topics


The workshop aims to bring together researchers from cybersecurity, data mining, and machine learning domains. We encourage a lively exchange of ideas and perceptions through the workshop, focused on cybersecurity and data mining. Topics of interest include, but are not limited to:

1. Data mining and AI applications for cybersecurity

2. Data-driven cybersecurity innovation

3. Modelling and simulation of cyber systems and system components

4. Data mining approaches to make cyber systems secure and resilient

5. Human behaviour models with application to cybersecurity

6. AI tools and techniques, mental resilience, and cybersecurity

7. Data mining for cybersecurity software verification and validation

8. Automation of heterogeneous security tools

9. Decision making with uncertainty in cyber systems

10. Security and privacy


We are interested in the new applications of data mining and AI for cybersecurity. Submitted papers will be evaluated based on criteria such as technical originality, creativity, and applicability.


Methodological topics of interest include, but are not limited to:

1. Graph convolution networks and graph attention networks
2. Interpretable deep learning
3. Real-time and/or streaming deep learning
4. Multi-view deep learning paradigms
5. Deep adversarial learning (e.g., generative adversarial networks)
6. Deep transfer learning
7. Deep Bayesian learning
8. Deep reinforcement learning

Application areas of interest include, but are not limited to:

1. Malware evasion and detection
2. IP reputation services
3. Event correlation and anomaly detection
4. Internet of Things (IoT) analysis (e.g., fingerprinting, network telescopes, etc.)
5. Threat modeling (e.g., mapping exploits to MITRE ATT&CK)
6. Security data fusion (e.g., event correlation) across multiple data sources
7. Cybersecurity information sharing and automation
8. Smart and large-scale vulnerability assessment and management systems
9. Security Intelligence Augmentation (e.g., human-in-the-loop systems)
10. Dark Web Analytics for CTI applications

Guest Speakers


Giovanni Russello, The University of Auckland, New Zealand

Ryan Ko, The University of Queensland, Australia

Xuyun Zhang, Macquarie University, Australia

Submission & Publication


Paper submissions should be limited to max 8 pages plus 2 extra pages and follow the IEEE ICDM format. More detailed information is available in the IEEE ICDM 2021 Submission Guidelines (https://www.ieee.org/conferences/publishing/templates.html).

Please submit your manuscript through the DMC 2021 submission site.

All accepted workshop papers will be published in the dedicated ICDMW proceedings published by the IEEE Computer Society Press. Therefore, papers must not have been accepted for publication elsewhere or be under review for another workshop, conferences, or journals.

Important Date


Submissions due: September 3, 2021

Notifications of Acceptance: September 24, 2021

Camera-ready paper due: October 1, 2021

Workshop day: December 7, 2021

All dates are 11:59PM Pacific Daylight Time (PDT).

Workshop Organisation


Workshop Organiser

Muhammad Ali Babar, The University of Adelaide, Australia

Gillian Dobbie, The University of Auckland, New Zealand

Hsinchun Chen, University of Arizona

Sagar Samtani, Indiana University

Zahid Islam, Charles Sturt University, Australia

Reza Shahamiri, The University of Auckland, New Zealand

Ranran Bian, The University of Adelaide, Australia

Victor Benjamin, Arizona State University

Weifeng Li, University of Georgia


Program Committee

Muhammad Ali Babar, The University of Adelaide, Australia

Gillian Dobbie, The University of Auckland, New Zealand

Ankit Shah, University of South Florida

Hongyi Zhu, University of Texas, San Antonio

Nasir Ghani, University of South Florida

Hyrum Anderson, Microsoft

Zahid Islam, Charles Sturt University, Australia

Reza Shahamiri, The University of Auckland, New Zealand

Ranran Bian, The University of Adelaide, Australia

Ethan Rudd, FireEye

Balaji Padmanabhan, University of South Florida

Elias Bou-Harb, University of Texas, San Antonio

Yunji Liang, Northwestern Polytechnical University

Yidong Chai, Tsinghua University

Shuo Yu, Texas Tech University

Reza Ebrahimi, University of Arizona

Michael Bewong, Charles Sturt University, Australia

Rafiqul Islam, Charles Sturt University, Australia

Contact Us


Ranran Bian

School of Computer Science, Faculty of Engineering, Computer and Mathematical Sciences, The University of Adelaide

Floor/Room 5 48D, Ingkarni Wardli, North Terrace, Adelaide 5000, Australia

Email: monica.bian@adelaide.edu.au


Muhammad Ali Babar

School of Computer Science, Faculty of Engineering, Computer and Mathematical Sciences, The University of Adelaide

Floor/Room 4 54, Ingkarni Wardli, North Terrace, Adelaide 5000, Australia

Email: ali.babar@adelaide.edu.au