11th International Workshop on Security, Privacy, Trust, and Machine Learning for IoT

Motivation for the Workshop

Internet of Things (IoT) has emerged as the next big technological revolution in computing in recent years with the potential to transform every sphere of human life. With an expanding network of interconnected Internet-enabled devices, IoT devices are used in a range of applications from connected cars, smart homes, healthcare, smart retail, to supply-chain management. The rise of this transformative technology is however deeply mired with security and privacy concerns.

The large influx of connected devices in the market introduces new vulnerabilities and opens new avenues for security attacks. The massive scale and variety of these devices also make it challenging for the manufacturers to design and implement manageable security and privacy solutions resulting in devices shipped without adequate security controls in place. Traditional security, privacy and trust-based solutions are also found to be inefficient against the various constraints of the IoT environment.

In the IoT ecosystem, where devices are constantly generating increased volume of big of data, machine-learning algorithms can be useful to perform intelligent processing, automated data analysis and provide meaningful interpretations and predictions to support smart and secure IoT applications. Machine learning techniques that enable the IoT devices to learn and adapt to various threats dynamically will be critical to building secure IoT systems. Use of machine learning for IoT security is especially very promising to detect any outliers to normal activity in the system.

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We plan to seek previously unpublished work in theoretical or experimental research, or work in-progress on topics including, but not limited to, the following: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

· Machine learning for anomaly detection in IoT

· Machine learning to analyze cryptographic protocols for IoT

· Deep Learning for security in IoT

· Privacy-preserving Edge Machine Learning in IoT

· Privacy enhancing and anonymization techniques in IoT

· Attack against Federated Learning in IoT Systems

Important Dates

Papers submission: March 26, 2021 (FIRM)

Notification of acceptance: April 23, 2021

Camera-ready paper due: April 30, 2021

Workshop date: July 22, 2021

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=icccn2021) as PDF files (formatted for 8.5x11-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 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).

REVIEW AND PUBLICATION OF MANUSCRIPTS

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 2021 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 2021 Paper Submission Terms and Conditions:

1. Authors declare that the submission is original and has not been submitted to other venues 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 2021 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 Athens in case one author cannot get the entry visa.

ORGANIZING COMMITTEE

Workshop Co-Chairs

Geethapriya Thamilarasu, University of Washington Bothell

Abhishek Parakh, University of Nebraska at Omaha

Technical Program Committee

Le Guan, University of Georgia

Cristina Alcaraz, University of Malaga, Spain

Pei-Chi Huang, University of Nebraska Omaha

Weizhi Meng, Technical Universtiy of Denmark

Gokhan Kul, University of Massachusetts Dartmouth

Jun Dai, California State University Sacramento

Saptarshi Debroy, The City University of New York (CUNY)

Yu Chen, State University of New York Binghamton

Qinghua Li, University of Arkansas

Smriti Bhatt, Texas A&M University-San Antonio

Antonio Celesti, University of Messina

Klaus Moessner, University of Surrey