Digital forensics has emerged as an emerging field of study for IT-related academics, professionals, and researchers over the last decade. To move forward with the investigation into how to gather and examine digital evidence in a current software framework, researchers are also concerned with and challenged by the "built-in" questions of how to develop and build forensic awareness in software applications, so that a cooperative environment for digital forensic purposes is created. By providing an incentive for hackers to conduct confidential attacks, the Internet has made it easier to access open source software. The rapid expansion of global communication and networking networks and devices makes investigating cyber-attacks difficult. There are also indications of illegal activity in massive amounts of data that must be examined for digital forensics and evidence. Digital forensics and cybercrime investigations have become extremely important for law enforcement, national security, and information security. Cybercriminals are developing crime forks in tandem with new technologies including the Internet of Things (IoT), Block-chain, Autonomous Driving, and Fog / Edge computing. Spam attacks, malware, cyberwarfare, carding, phishing scams, and data breaches are only a few of the types of malware that have been affected. As a result, academicians, experts, and scholars are increasingly interested in digital forensics, which is an emerging area of study.
FAIReScience 2021 - Making eScience FAIR (findable, accessible, interoperable, and reusable) for diverse research objects
This discussion-focused workshop examines how the FAIR (Findable, Accessible, Interoperable, Reusable) principles are and can be applied to eScience research objects beyond data. Invited speakers will present the idea of FAIR and its application to objects such as software, workflows, machine learning models, and executable notebooks, and where FAIR is going. Invited talks will be followed by a panel discussion guided by questions suggested by the attendees. From the talks, questions and discussions, we plan a white paper to be written after the workshop, with workshop speakers and attendees as authors.
This workshop explores innovations and experiences around developing portable, general, reproducible workflows while paying attention to providing open data with verifiable authenticity while protecting privacy, where needed. We are looking for community discussion and participation on the above topics plus the following. First, component packaging via containers and virtual machines, automation scripting, deployment, portability builds, and system support for these and other relevant activities. Second, provenance collection, exploration, and tracking are key for a well-documented scientific output. Third, issues with managing large data sets and workflow intermediate data, particularly those intended to manage publicly accessed data for use and reuse are encouraged. Finally, new techniques and technologies that address portability and reproducibility requirements, such as those required for peer reviewed publication, are also requested.