CALL FOR PAPERS | TOPICS - CFP Flyer

Prospective authors are invited to submit high-quality original technical papers for presentation at the conference and publication in the conference proceedings. The topics are not limited to those as below:
Easychair Submission System: http://www.easychair.org/conferences/?conf=icccbda2025

 

Track 1: Cloud Computing Fundamentals and Architecture

Track Chair:


Emerging cloud models (public, private, hybrid clouds)
Cloud service architectures (IaaS, PaaS, SaaS)
Cloud deployment strategies
Cloud computing and semantic web technologies
Cloud Computing Architecture and Systems
Cloud Computing Models, Simulations, Designs, and Paradigms
Cloud Computing Technologies, Services and Applications
Cloud Economics
Cloud Management and Operations
Cloud Middleware Frameworks
Cloud Optimization and Automation
Cloud Quality and Performance
Cloud Solution Design Patterns

  Track 2: Security and Privacy in Cloud and Big Data

Track Chair:

 

Security and privacy in cloud computing
Security challenges in cloud-based IoT applications
Data governance and compliance in the cloud
Security and privacy for big data
Privacy Preserving Big Data Analytics
Blockchain based lightweight data structures for IoT data
Collaborative Threat Detection using Big Data Analysis Analytics

     
Track 3: Big Data Technologies and Frameworks

Track Chair:

 

Big data frameworks and tools (Hadoop, Spark, etc.)
Algorithms and Systems for Big Data Analysis Search
Big Data Storage, Indexing, Searching and Querying
Techniques, models and algorithms for big data
Tools and systems for big data
Intelligent Data Processing
Hardware/software infrastructure for big data
Big Data Open Platforms
Experience with Big Data Project Deployments
Big Data Toolkits

  Track 4: Data Analytics and Machine Learning

Track Chair:

 

Machine learning and artificial intelligence in big data
Data mining techniques and applications
Big Data Analysis Analytics and Metrics
Machine learning and AI for big data
City-scale Data Mining and Machine Learning
Visualization Analytics for Big Data
Data mining, graph mining and data science
Foundational Models for Big Data
Issues, problems and opportunities in Big Data

     
Track 5: IoT, Edge Computing, and Cloud Integration

Track Chair:

 

IoT architecture and cloud integration
Data management and analytics in IoT environments
Edge vs. cloud computing paradigms
Data processing and analytics at the edge
Applications and case studies of edge computing
Challenges and solutions in edge computing deployment
Social impact and sustainability in cloud and big data applications
Innovative use cases leveraging cloud and big data technologies

 

Track 6: Application of Cloud and Big Data in Various Industries
Track Chair:

 

Industry-specific applications (healthcare, finance, smart cities, etc.)
Big Data for Vertical Industries (including Government, Healthcare, and Environment)
Big Data Analysis for Business Model Innovation
Big Data in Government Management Models and Practices
Real-life Case Studies of Value Creation through Big Data Analytics

     
Track 7: Future Trends and Challenges in Cloud and Big Data

Track Chair:

 

Emerging trends in cloud computing and big data
Ethical considerations and societal impacts
Regulatory changes affecting cloud and big data
Research challenges and future directions
Big Data Analysis Economics
Big Data for Business Model Innovation
SME-centric Big Data Analytics

  Track 8: Cloud Storage and Data Management

Track Chair:

 

Data storage and retrieval in cloud environments
Data integration and interoperability
Cloud-based database management systems
Data Quality and Provenance Control
Framework for Data Understanding and Quality
New Data Standards and Programming Models
Representation Formats for Multimedia Big Data

Policies

Review:
The Committees of ICCCBDA 2025 invest great efforts in reviewing the papers submitted to the conference and organising the sessions to enable the participants to gain maximum benefit.

By submitting a paper to ICCCBDA, the authors agree to the review process and understand that papers undergo a peer-review process. Manuscripts will be reviewed by appropriately qualified experts in the field selected by the Conference Committee, who will give detailed comments and — if the submission gets accepted — the authors submit a revised ("camera-ready") version that takes into account this feedback.

All papers are reviewed using a single-blind review process: authors declare their names and affiliations in the manuscript for the reviewers to see, but reviewers do not know each other's identities, nor do the authors receive information about who has reviewed their manuscript.

 

 

Dual/Double Submissions:
By submitting a manuscript to ICCCBDA, authors acknowledge that it has not been previously published or accepted for publication in substantially similar form in any peer-reviewed venue with publicly accessible papers, including journals, conferences, workshops, or other peer-reviewed, archival forums. Furthermore, no paper substantially similar in content has been or will be submitted to another peer-reviewed conference or workshop with publicly accessible papers during the review period. The authors also attest that they did not submit a substantially similar submission to ICCCBDA 2025. As a rule of thumb, the ICCCBDA submission should contain no more than 20 percent of material from previous publications. Violation of any of these conditions will lead to rejection.

 

 

Plagiarism:
ICCCBDA is utterly intolerant of plagiarism. Submitted papers are expected to contain original work executed by the authors with adequate, proper and scholarly citations to the work of others. It is the job of the authors to clearly identify both their own contribution(s) and also published results / techniques on which they depend or build. Reviewers are charged to ensure these standards are met.
If the author is found to commit an act of plagiarism, the following acts of sanction will be taken:
1. Reject the article submitted or delete the article from the final publications.
2. Report the authors violation to his/her supervisor(s) and affiliated institution(s)
3. Report the authors violation to the appropriate overseeing office of academic ethics and research funding agency.
4. Reserve the right to publish the authors name(s), the title of the article, the name(s) of the affiliated institution and the details of misconduct, etc. of the plagiarist”.