Social good and healthcare are increasingly dependent on products and services whose security and integration should be attended. These systems are becoming larger and more complex, due to the increasingly involved processes and amount of the available heterogeneous data generated by a growing number of interconnected control and monitoring devices. Moreover, those devices are also heavily dependent on systems whose security, management, and compliance must also be considered. This evolving scenario requires new strategies to improve the security and the performance of integration of services of their associated frameworks. Compliance management and cyber-security forensic analysis are rapidly emerging in Information Technologies (IT) as important requirements to be attended, mainly due to the exponential growth of available raw data produced by sensors, which demands the development of new approaches for data analytics to gather new insights in terms of security. Such evolving scenario requires scalable frameworks able to collect and consume a massive quantity of heterogeneous structured and unstructured data, foreseeing the tracking and tracing of eventual anomalies supported by new machine learning models or data analytics approaches. Moreover, innovative frameworks can contribute to improve their protection by considering forensic techniques (for supporting, for instance, criminal law enforcement); and to improve continuous auditing (e.g. on subcontractors, IT systems, supply chain, and personnel activity) for compliance management and service quality assessment processes. Additionally, it is required a higher degree of flexibility in terms of security management, monitoring, and configuration to prevent possible risks arising, for instance, from operational errors or cyber-attacks. The authors from all fields working on these subjects are encouraged to submit a paper presenting their recent work, or a scientific discussion on the topic.
Authors are solicited to submit original, previously unpublished papers in the following, but not limited to, topic areas:
- Integration Services;
- Auditing Compliance;
- Machine Learning;
- Data Analytics;
- Parallel Computing;
- Machine learning;
- Intelligent systems;
- Sensor Data Acquisition, Analysis and Processing.
All registered papers will be submitted for publishing by Springer and made available through SpringerLink Digital Library.
Proceedings will be submitted for inclusion in leading indexing services, such as Web of Science, EI Engineering Index (Compendex and Inspec databases), DBLP, EU Digital Library, Google Scholar, IO-Port, MathSciNet, Scopus, Zentralblatt MATH.
The registered papers must follow the guidelines below:
• Papers should be in English.
• Submitted papers can be short (6-11 p.) or regular (12-15+ p.).
• Previously published work may not be submitted, nor may the work be
concurrently submitted to any other conference or journal. Such papers will be rejected without review.
GOODTECHS proceedings are indexed in leading indexing services, including Ei Compendex, ISI Web of Science, Scopus, CrossRef, Google Scholar, DBLP, as well as EAI’s own EU Digital Library (EUDL).
Community Review is a service offered to Program Committees and submitting Authors of all EAI conferences designed to improve the speed and the quality of the review process.
Abstracts of all authors who opt-in to Community Review during submission will be published and available for Bidding here.
Learn more about the Community Review process
Papers should be submitted through EAI ‘Confy+’ system, and have to comply with the Springer format (see Author’s kit section).
Full Paper Submission deadline
14 June 2021
1 July 2021
1 August 2021
Start of Conference
15 September 2021
End of Conference
17 September 2021