We invite submissions for our upcoming Special Session on Data Mining for Privacy and Information Security at The 20th International Conference on Advanced Data Mining and Applications 2024 (ADMA 2024). ADMA is in the list of CCF (China Computer Federation) recommended Conferences (C series, Databases/Data Mining).

Special Session: Data Mining for Privacy and Information Security

The fusion of scalable computing infrastructure, big data, and artificial intelligence has boosted the development and application of data science and advanced data analytics. However, the recently emerging threats on the privacy, security, and trust (PST) of the data and analytics models have shown a dramatically increasing trend with the wide deployment of data analytics applications.

This special session mainly focuses on the discussions of privacy, security, and trust in data analytics, which generally covers (but not limited to) the topics in privacy-preserving technology, privacy attacks, federated learning, machine unlearning, data poisoning attacks, model evasion attacks, adversarial learning, model robustness, secure machine learning integrating cryptographic techniques, blockchain techniques protection PST of data and models, etc. This special session invites authors to submit original research work that demonstrates and explores current advances in all related areas mentioned above. High-quality accepted papers will be recommended to the associated journal special issues.

Topics of Interest

We welcome contributions spanning a wide spectrum of topics, including but not limited to:

  • Privacy-preserving techniques
  • Privacy attacks and defences
  • Federated learning
  • Machine unlearning
  • Data poisoning attacks and countermeasures
  • Model evasion attacks and robustness
  • Adversarial learning and security
  • Secure machine learning with cryptography
  • Blockchain for data and model protection
  • Trustworthy and explainable AI
  • Domain-specific privacy and security challenges
  • Post-quantum cryptography

Formatting Guidelines

We welcome English-language papers containing original and unpublished contributions to the fields of data mining and related areas. Manuscripts should adhere to the LNAI (Lecture Notes in Artificial Intelligence) format. For the template and detailed instructions on LNCS style, please refer to Springer's Author Instructions. Papers should adhere to the main conference guidelines, ensuring they do not exceed 15 pages in LNAI format. Submissions undergo a double-blind review process for ADMA2024. This means:

  • Author identities and affiliations remain undisclosed to reviewers throughout the review process.
  • Authors must prepare and submit blinded manuscripts that conceal author and affiliation information. Specific guidelines are outlined below.
  • Both authors and reviewers are expected to make sincere efforts to prevent accidental de-blinding of any submission.
  • All submitted papers must adhere to the following rules. Non-compliance may result in automatic rejection.

Submission Guidelines

Authors are invited to submit original research papers, case studies, and technical reports aligned with the theme of AI in Healthcare and Medicine. Submissions should adhere to the conference's formatting guidelines and be submitted through the CMT online submission system. All submissions will undergo a rigorous peer-review process to ensure quality and relevance. When submitting your manuscript, please choose the "Special Session Track" option and select the area of "Special Session: Data mining for privacy and information security".

Important Dates

  • Paper Submission Deadline: 15th June 2024 (AoE)
  • Notification of Acceptance: 1st August, 2024 (AoE)
  • Camera-Ready Paper Due: 15th August, 2024 (AoE)
  • Conference Dates: 3rd~5th December, 2024 (AEST)

Track Chairs

Prof. Aswani Kumar Cherukuri, Vellore Institute of Technology, India, aswani@vit.ac.in

A/Prof. Qingyi Zhu, Chongqing University of Posts and Telecommunications, China, zhuqy@cqupt.edu.cn

Program Committee

Yushu Zhang, Nanjing University of Aeronautics and Astronautics, China

Chenquan Gan, Chongqing University of Posts and Telecommunications, China

Lu-Xing Yang, Deakin University, Australia

Ming Li, Henan Normal University, China

Leo Yu ZHANG, Griffith University, Australia

Xianyong Li，Xihua University, China

Jichao Bi, Zhejiang Institute of Industry and Information Technology, China

Sindhuja Rao, CISCO, Bengaluru, India

Raghavendra Kumar Chunduri, Concetrix, USA

Firuz Kamalov, Canadian University of Dubai, UAE

Arghya Kusum Das, University of Alaska, USA

Debasis Ganguly, University of Glasgow, UK

Praveen Kumar Donta, Vienna University of Technology, Austria

Amit Kumar Singh, Siksha O Anusandhan University, India

Naresh Kshetri, Emporia State University, USA

Ali Ismail Awad, UAE University, UAE

Muhammad Naveed Aman, University of Nebraska Lincoln, USA

Yassine Maleh, Sultan Moulay Slimane University, Morocco