10th International Workshop on Security, Privacy, Trust, and Machine Learning for IoT

15 March 2020 all-day

General Information

The 10th International Workshop on Security, Privacy, Trust, and Machine Learning for Internet of Things (IoTSPT-ML 2020) will be held in conjunction with the The 29th International Conference on Computer Communications and Networks (ICCCN 2020), in Honolulu, Hawaii, USA. All papers presented in IoTSPT-ML 2020 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 are 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We plan to seek previously unpublished work in theoretical or experimental research, or work in-progress on topics including, but not limited to, the following: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 and privacy frameworks for IoT
  • Cryptographic approaches for security and privacy in IoT
  • Trust frameworks and management models for IoT
  • Wireless security protocols for IoT
  • Threat and attack models in IoT
  • Intrusion and malware detection for IoT
  • End-to-end system security models for IoT
  • Machine Learning for security and privacy in IoT
  • Deep Learning for security in IoT
  • Machine learning for deep packet inspection for IoT
  • Machine learning to analyze cryptographic protocols for IoT
  • Privacy-preserving, machine-learning-based data analytics in IoT
  • Privacy enhancing and anonymization techniques in IoT

Important Dates

  • Papers submission: March 15, 2020
  • Notification of acceptance: April 27, 2020 (Hard Deadline)
  • Camera-ready paper due: May 11, 2020 (Hard Deadline)
  • Workshop date: August 6, 2020

Submission Instructions for authors

Authors are invited to submit manuscripts reporting original unpublished research and recent developments in the topics related to the workshop. 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=icccn2020) under “10th 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 pages are 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 exceeds 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).


Submitted papers will be reviewed by the workshop Program Committee and judged on originality, technical correctness, relevance, and quality of presentation. An accepted paper must be presented at the ICCCN 2020 venue by one of the authors registered at the full registration rate. Each workshop registration covers up to two workshop papers by an author. Accepted and presented papers will be published in the ICCCN proceedings and submitted to IEEE Xplore as well as other Abstracting and Indexing (A&I) databases. IEEE reserves the right to exclude a paper from distribution after the conference, including IEEE Xplore® Digital Library if the paper is not presented by the author at the conference.

ICCCN 2020 Paper Submission Terms and Conditions:

1. Authors declare that the submission is original and has not been submitted to other venue or under consideration by other venues.

2. Paper titles and/or author names cannot be changed and/or added to the papers once papers are submitted to ICCCN 2020 for review and in the final camera-ready manuscript.

3. If the paper is accepted, at least one of the authors must register at full rate and present it in person at the conference. Accepted and paid paper(s) but not presented onsite by the registered author(s) (for any reason, including visa issues, travel problems, etc.) will be published in the conference proceedings only. We strongly encourage that all authors of accepted papers apply for an entry visa to Hawaii in case one author cannot get the entry visa.


Workshop Co-Chairs
  • Geethapriya Thamilarasu, University of Washington Bothell
  • Abhishek Parakh, University of Nebraska at Omaha
Technical Program Committee
  • Nabil Benamar
  • Schahram Dustdar
  • Zeljko Zilic
  • Paolo Bellavista
  • Carlos Kamienski
  • Marin Litoiu
  • Francesco Longo
  • Klaus Moessner
  • Alexandros Fragkiadakis
  • Xinxin Fan
  • Song Fang
  • Sebastian Echeverria