Social Media Analytics and Cloud Security (SMACS'24) 

A plethora of social networking applications and the wide availability of cloud resources, provide powerful and easy mechanisms for criminals to confer, plan, and execute with absolute timely precision. Threat and risk assessments for prevention of crime, and timely aid to victims of criminal acts are crucial but complex tasks for the police and administrative bodies. The complexity is augmented by the fact that advancements in technology make the task easier, but often perpetrators of crimes possess comparable or more advanced technology.  Fast advancements in technological innovations to proactively predict and prevent crime, and to provide timely aid to victims have become a problem to be addressed with the highest priority for a peaceful society. Cloud-based storage, cloud computing, and big data analytics are crucial technologies for crime prediction and prevention.

The International Workshop on Social Media Analytics and Cloud Security (SMACS) welcomes research efforts in this area of importance and solicits research papers on ideas, models, surveys, and applications in the area.

The following list includes (but not limited to)  some of the major topics that we plan to focus in this international workshop. 

· Security for Big Data Storage

· Cloud Service models for Crime Detection and Prevention

· Big data Models for potential crime-related analysis

· Predictive Analytics for crime prevention

· Inter cloud operability for secure crime-related data handling

· Security, privacy, and trust models for IoT for crime detection and Prevention

· Multi-cloud/hybrid-cloud support for IoT applications

· Collaboration models for IoT applications for collaborative crime detection

· Social Computing and Crime Detection, Prevention, and Mitigation of Impact

· Collaborative Big Data Analytics for crime detection and prevention and challenges

· Fake news generation, propagation, and early detection in Social Media

· AI based systems for deep fake video detection on Online Social Networks

·  AI based models for detecting fake profiles in Online social Media

·  Vulnerabilities in virtualization and cloud platforms

·  Network and cloud security

· Using Geo Technology and Big Data Analytics for checking infiltration

This workshop welcomes theoretical models, algorithms, practical results, description and analysis of experiments and demonstrations of working prototypes.

Submission Guidelines

We invite original research papers that have not been previously published and are not currently under review for publication elsewhere. Submitted papers should be no longer than 8 pages in two-column IEEE template format. All accepted papers will be published as part of the CCGRIDW proceedings (CCGrid Workshops proceedings). All previous CCGrid proceedings have been published by the IEEE and available online through IEEE Digital Library (EI indexing). Each accepted paper will be included and indexed in the IEEE digital libraries (Xplore) and in Scopus Database. Submission Link: https://easychair.org/conferences/?conf=smac24

Important Dates

  Paper Submission Deadline:

Dec 22nd, 2023  (24 th January 2024)

Notification of Acceptance:

Feb 23rd, 2024

Camera-ready Submissions Deadline:

March 4th, 2024

Track Program Chairs

Madhu Kumar S.D, NIT Calicut, India(madhu@nitc.ac.in)

Priya Chandran, NIT Calicut,  India (priya@nitc.ac.in)

Programme Committee

Rajeev R. Raje, IUPUI, USA

Arun Ravindran, University of North Carolina, Charlotte, USA

      Umesh Bellur, IIT Bombay, India

     Sunil Chandra, IISc, Bangalore, India

     Feras Mahmoud Naji Awaysheh, University Of Tartu, Estonia

      Hiran V Nath, NIT Calicut, India

      Annappa, NIT Karnataka, India

      Prawaal Sharma, Infosys, India

         Shruti Kunde, TCS Research Lab, India