English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Zendy Plus

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Zendy Tools

Zendy Open

It is challenging for digital forensic practitioners to maintain skillset currency, for example knowing where and how to extract digital artifacts relevant to investigations from newer, emerging devices (e.g., due to the increased variety of data storage schemas across manufacturers and constantly changing models). This paper presents a knowledge sharing platform, developed and validated using an Internet of Things dataset released in the DFRWS 2017–2018 forensic challenge. Specifically, we present an automated knowledge-sharing forensic platform that automatically suggests forensic artifact schemas, derived from case data, but does not include any sensitive data in the final (shared) schema. Such artifact schemas are then stored in a schema pool and the platform presents candidate schemas for use in new cases based on the data presented. In this way, investigators need not learn the forensic profile of a new device from scratch, nor do they have to manually anonymize and share forensic knowledge obtained during the course of an investigation.

How Do I Share My IoT Forensic Experience With the Broader Community? An Automated Knowledge Sharing IoT Forensic Platform