9th International Workshop on Security, Privacy, Trust, and Machine Learning for IoT

General Information

The 9th International Workshop on Security, Privacy, Trust, and Machine Learning for Internet of Things (IoTSPT-ML 2019) will be held in conjunction with the The 28th International Conference on Computer Communications and Networks (ICCCN 2019), in Valencia, Spain. All papers presented in IoTSPT-ML 2019 will be published in the workshop proceedings.

Outstanding papers will be invited to extend to full version for a SCI(E)-indexed journal, which is currently under contact.

Motivation for the Workshop

Experts predict that there will be 3-4 billions of connected devices in use by consumers by the end of this year. Although these devices in smart TVs, microwave ovens, thermostats, etc., will probably make our lives more energy and cost efficient, they can also threaten the security of our homes. This is because the manufacturers of these devices are primarily interested in functionality and do not focus on securing the device against cyber-attacks, protecting the privacy of consumer information on the device, securing the communications from/to the device, etc. The massive scale and the variety of these devices also make it difficult for the manufacturers to design and implement manageable security and privacy solutions.

Another challenge in the IoT world is the continuous collection of data from the devices which is analyzed to make conclusions about the environment being monitored by the IoT devices. The data analyses is also crucial to maintaining the security and privacy of the data being collected from the devices. The massive scale of next-generation IoT systems makes the data collection, analyses, transport, and fusion of the results at the system level seem daunting.

This workshop aims to promote discussions of research and relevant activities in the models and design of secure, privacy-preserving, or trust architectures, data analyses and fusion platforms, protocols, algorithms, services, and applications for next generation IoT systems. We especially encourage security and privacy solutions that employ innovative machine learning techniques to tackle the issues of data volume and variety problems that are systemic in IoT platforms.

We plan to seek previously unpublished work in theoretical or experimental research, or work in-progress on topics including, but not limited to, the following:

  • Architectures and protocols for scalable, secure, robust and privacy enhancing IoT
  • Security, privacy, and trust issues in IoT
  • Security and privacy frameworks for IoT at home
  • Threat and attack models in IoT
  • Machine Learning for IoT
  • Intrusion and malware detection for IoT
  • System and data integrity
  • End-to-end system security models for IoT
  • Deep Learning for IoT
  • Cryptographic approaches for security and privacy in IoT
  • Machine learning for deep packet inspection for IoT
  • Machine learning to analyze cryptographic protocols for IoT
  • Wireless security protocols for IoT

The organizers of the workshop will invite authors of outstanding papers to submit extended versions of their papers for publication in a Special issue being organized in the journal Internet of Things, Elsevier, with a publication date of early 2020.

Important Dates

Papers submission: March 15, 2019

Notification of acceptance: April 28, 2019 (Hard Deadline)

Camera-ready paper due: May 10, 2019 (Hard Deadline)

Submission and Publication

Authors are invited to submit manuscripts reporting original unpublished research and recent developments in the topics related to the workshop. Submissions should include a title, abstract, keywords, author(s) and affiliation(s) with postal and e-mail address(es) of the corresponding author. Submitted manuscripts must be formatted in standard IEEE camera-ready format (double-column, 10-pt font) and must be submitted via EasyChair (https://easychair.org/conferences/?conf=icccn2019) under “9th International Workshop on Security, Privacy, Trust, and Machine Learning for IoT” as PDF files (formatted for 8.5×11-inch paper). The manuscripts should be no longer than 6 pages. Two additional page is permitted if the authors are willing to pay an over-length charge at the time of publication (manuscripts should not exceed 8 pages).

Submitted papers cannot have been previously published in or be under consideration for publication in another journal or conference. The workshop Program Committee reserves the right to not review papers that either exceed the length specification or have been submitted or published elsewhere. Submissions must include a title, abstract, keywords, author(s) and affiliation(s) with postal and e-mail address(es). All authors of a paper must be registered in the RIGHT order via EasyChair at the SUBMISSION TIME and cannot be changed after the submission due time at EasyChair. The paper title and author name list/order cannot be changed during the final camera-ready submission.

Outstanding papers will be invited to extend to full version for a prestigious journal, Internet of Things, Elsevier, targeting publication in early 2020. When uploading a camera-ready at IEEE, note that the paper title, author names/affiliation and order must be IDENTICAL to the original submission for peer reviewing. No title change, author addition or removal is allowed.

A paper must be registered by an author in the full rate. It must be presented by one of registered authors in the venue. Camera-ready and registration due date is FIRM. Check ICCCN homepage to find detailed instructions. Please try to complete the process as early as possible in order to avoid the rush hour, giving you time to deal with unexpected but possible issues/delay.

Organizing Committee

Workshop Co-Chairs

Parvathi Chundi, University of Nebraska at Omaha

Abhishek Parakh, University of Nebraska at Omaha

Technical Program Committee

Carol Lushbough, University of South Dakota

Pei-Chi Huang, University of Nebraska at Omaha

Wilson Rivera-Gallego, University of Puerto Rico at Mayaguez

Zhiwei Wang, Nanjing University of Posts and Telecommunications

Jian Shi, University of Houston

Giancarlo Fortino, University of Calabria

Schahram Dustdar, Vienna University of Technology

Nabil Benamar, Moulay Ismail University

Nik Besis, Edge Hill University

Dominique Genoud, Hesso//Wallis - IIG

Paolo Bellavista, University of Bologna

Shankarachary Ragi, South Dakota School of Mines and Tech

Myoungkyu Song, University of Nebraska at Omaha

Eyhab Al-Masri, University of Washington

Xinxin Fan, IoTeX

Alexandros Fragkiadakis, Foundation for Research and Technology - Hellas, Institute of Computer Science

Constantinos Marios Angelopoulos, Bournemouth University

Jitender Grover, International Institute of Information Technology - Hyderabad (IIIT - Hyderabad)

Salvatore Distefano, University of Messina

Razvan Stanica, Institut National des Sciences Appliquées de Lyon (INSA Lyon)

Dimosthenis Ioannidis, The Centre for Research and Technology, Hellas Information Technologies Institute

Gyu Myoung Lee, Liverpool John Moores University

Yunsheng Wang, Kettering University

Mengchu Zhou, New Jersey Institute of Technology

Jorge Sá Silva, University of Coimbra

Grace Lewis, Carnegie Mellon Software Engineering Institute

Carlos Kamienski, Federal University of the ABC

Sergio Saponara, University of Pisa

Isam Ishaq, Al-Quds University

Mihai Lazarescu, Politecnico di Torino

Kumar Yelamarthi, Central Michigan University

Klaus Moessner, University of Surrey

Ahmed Khattab, Cairo University

Zeljko Zilic, McGill University

Francesco Palmieri, University of Salerno, Italy

Shashikant Shantilal Patil, SVKMs Narsee Monjee Institute of Management Studies, Mumbai

Juan Antonio Martinez Navarro, University of Murcia

Rahul Kher, G H Patel College of Engineering & Technology

Rogério de Lemos, University of Kent

Song Houbling, Embry-Riddle Aeronautical University

Martin Serrano, National University of Ireland Galway(NUIG - DERI)

Etieene Gnimpieba, University of South Dakota

Francesco Longo, University of Messina - Department of Mathematics