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Special Session 1: Formal Methods and Intelligent Tools for Cybersecurity
This special session delves into the realm of formal methods and intelligent tools for cybersecurity and cyber defense.
As the intricacy of communication networks continues to escalate, the imperative for robust security measures becomes increasingly
paramount and formidable. Traditional security technologies may prove inadequate to meet the demands of users operating within open,
heterogeneous, dynamic, mobile, distributed, and wireless computing environments. Consequently, there arises an incessant demand to
cultivate environments that facilitate diverse applications to collaborate while upholding elevated levels of security. The primary aim
of this session is to convene researchers and practitioners actively engaged in the realms of security, cybersecurity, and cyber defense.
The emphasis lies in deliberating emerging methodologies and strategies for crafting and fortifying secure systems and networks. Submissions
focusing on formal methodologies are especially encouraged, as well as papers proposing approaches integrating AI, ML, DL, XAI, and NLP techniques.
Session Organizers
▪
Prof. Jaouhar Fattahi, Laval University, Québec, Canada
▪
Prof. Mohamed Mejri, Laval University, Québec, Canada
▪
Prof. Ridha Ghayoula, Moncton University, New Brunswick, Canada
▪
Prof. Emil Pricop, Petroleum-Gas University of Ploiesti, Romania
The topics of interest include, but are
not limited to:
• Cryptographic protocols
• Cryptography and Cryptanalysis
• Network security
• Hardware security
• Software security
• Formal Methods for security
• Biometrics
• Web applications security
• Security policies, model and architecture
• Privacy, trust and anonymity
• Security in parallel and distributed systems
• Cloud security
• Incident response and management
• Identity and access management
• Governance, risk management, and compliance
• Physical security
• Security architecture and design
• Wireless and mobile security
• Intrusion detection
• Anomaly detection
• Detecting toxic content on social networks
Submission method
Submit your Full Paper (no less than 8 pages) or your paper
abstract-without publication (200-400 words) via
Online Submission System, then choose
Track: ICCCM 2024-Special Session 1 (Formal Methods and
Intelligent Tools for Cybersecurity)
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Special Session 2: Interdisciplinary Aspects of AI, IoT for Industrial and Medical Applications, and Social Deployment
Artificial Intelligence (AI) and the Internet of Things (IoT)
are empowering and widely used in society, industry, and the
medical field. In particular, many achievements have been made
in the industrial and medical fields. We aim to be at the
forefront of their dissemination to academics and the general
public as a social infrastructure worldwide. In a broad sense,
AI is a series of processes that use various methods to find
meaning and value in the data collected by the IoT. These have
the potential to solve various problems that exist in human
society.
In this particular track, we welcome submissions to present new
research issues and examples of social implementations related
to AI and IoT technologies for the practical application of AI
and IoT across disciplines. Submissions to this track should
report actual and significant unpublished results on any aspect
of society or the medical and industrial communities.
Session Organizers
▪ Assoc. Prof. Takanobu Otsuka, Nagoya Institute of Technology,
Japan
▪ Assoc. Prof. Shintaro Oyama, Nagoya University, Japan
Assoc. Prof. Takanobu
Otsuka
Nagoya Institute of Technology, Japan
Dr. Takanobu Otsuka is an Associate Professor at the Nagoya
Institute of Technology. He received an M.E and Doctor of
Engineering from the Nagoya Institute of Technology in 2011 and
2016, respectively. From 2012 to 2015, he was an Assistant
Professor at the Nagoya Institute of Technology. From 2015 and
2016, he was a visiting researcher at UCI (the University of
California Irvine).
His main research interests include IoT, multi-agent systems,
intelligent agents, distributed systems, and software
engineering on offshoring.
Assoc. Prof. Shintaro
Oyama
Nagoya University, Japan
Dr. Shintaro Oyama is an Associate Professor at the Innovative
Research Center for Preventive Medical Engineering (PME),
Institute for the Innovation for Future Society, Nagoya
University, Tokai National University Organization, and is
currently involved in industry-academia collaborative research
in a wide range of areas.
He graduated from Nagoya University School of Medicine in 2007,
and obtained his medical license. While working as a orthopedic
and hand surgeon, he has been engaged in research in the areas
of machine learning and photonics as a junior research associate
in the Image Information Processing Research Team at RIKEN since
2013. He has also been involved in the development of medical AI
and medical xR technologies at the Medical IT Center and xR
Center in Nagoya University Hospital (NUH).
His research themes are; Medical AI, Software as a Medical
Devices, Medical IoTs, Social Healthcare Systems, Medical
Informatics.
We plan to provide a unified platform for innovative research in
the core and applied areas by sharing demonstrations and the
latest research in AI and IoT.
The topics of interest include, but are
not limited to:
• Image recognition
• Machine Learning
• Knowledge representation, reasoning, and planning
• IoT and medical and Industrial practice
• Learning and adaptation
• AI and IoT for Human Learning and Behavior Change
• AI and IoT in Business
• Pattern Recognition
• Big Data and AI
• semi-supervised and unsupervised learning
• Reinforcement learning
• Innovative applications
Co-organized by
▪ New Energy and Industrial Technology Development Organization
(NEDO) (Public-Private Young Researcher Discovery Support
Program), Japan
▪ AIMAILs, National University Organization Nagoya University,
Japan
▪ Co-Creation IoT Infrastructure Research Center, Nagoya
Institute of Technology, Japan
Submission method
Submit your Full Paper (no less than 8 pages) or your paper
abstract-without publication (200-400 words) via
Online Submission System, then choose
Track: ICCCM 2024-Special Session 2 (Interdisciplinary
Aspects of AI, IoT for Industrial and Medical Applications, and
Social Deployment)
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Special Session 3: Time-Series
Data Processing and Real Data Analysis
This special
session addresses the analysis and utilization of time-series
data collected in various contexts, from our daily lives to
manufacturing, economics, and medical care. Time-series data is
collected for a broad range of purposes, such as elderly care,
preventive maintenance of industrial equipment, self-evaluation
of investment products, and business strategy formulation.
Furthermore, the recent proliferation of IoT (Internet of
Things) and ID-PoS (Point of Sales with ID) systems has led to
an increase in the volume of data acquired. As the costs of
collecting and retaining data rise, there is a growing need for
its effective utilization. On the other hand, since time-series
data varies in periodicity, presence or absence of trends, and
pattern characteristics depending on the target, it is necessary
to understand the data specific to each target and develop
appropriate processing and analysis methods. Therefore, this
session aims to share time-series data analysis methods,
examples of their application, and the knowledge gained in
various fields to accelerate the development of methods for
effective utilization of the increasing volumes of data.
Session Organizer
▪ Asst. Prof. Kosuke Shima, Nagoya Institute of Technology,
Japan
The topics of interest include, but are
not limited to:
•
Pattern Recognition
•
Machine Learning
•
Unsupervised Learning
•
Data Preparation
•
Anomaly Detection
•
Skill Transfer
•
Implicit Knowledge
•
Motion Analysis
Submission method
Submit your Full Paper (no less than 8 pages) or your paper
abstract-without publication (200-400 words) via
Online Submission System, then choose
Track: ICCCM 2024-Special Session 3 (Time-Series Data
Processing and Real Data Analysis)
Template Download