Fundamental Concepts of Cyber Resilience: Introduction and Overview

Given the rapid evolution of threats to cyber systems, new management approaches are needed that address risk across all interdependent domains (i.e., physical, information, cognitive, and social) of cyber systems. Further, the traditional approach of hardening of cyber systems against identified threats has proven to be impossible. Therefore, in the same way that biological systems develop immunity as a way to respond to infections and other attacks, so too must cyber systems adapt to ever-changing threats that continue to attack vital system functions, and to bounce back from the effects of the attacks. Here, we explain the basic concepts of resilience in the context of systems, discuss related properties, and make business case of cyber resilience. We also offer a brief summary of ways to assess cyber resilience of a system, and approaches to improving cyber resilience.Comment: This is a preprint version of a chapter that appears in the book "Cyber Resilience of Systems and Networks," Springer 201

Smart contract-based blockchain solution to reduce supply chain risks

Companies are becoming aware of the potential risks arising from sustainability aspects in supply chains. These risks can affect ecological, economic or social aspects. One important element in managing those risks is improved transparency in supply chains by means of digital transformation. Innovative technologies like blockchain technology can be used to enforce transparency. In this paper, we present a smart contract-based Supply Chain Control Solution to reduce risks. Technological capabilities of the solution will be compared to a similar technology approach and evaluated regarding their benefits and challenges within the framework of supply chain models. As a result, the proposed solution is suitable for the dynamic administration of complex supply chains

Categorical implicit learning in real-world scenes: Evidence from contextual cueing

International audienceThe present study examined the extent to which learning mechanisms are deployed on semantic-categorical regularities during a visual searching within real-world scenes. The contextual cueing paradigm was used with photographs of indoor scenes in which the semantic category did or did not predict the target position on the screen. No evidence of a facilitation effect was observed in the predictive condition compared to the nonpredictive condition when participants were merely instructed to search for a target T or L (Experiment 1). However, a rapid contextual cueing effect occurred when each display containing the search target was preceded by a preview of the scene on which participants had to make a decision regarding the scene's category (Experiment 2). A follow-up explicit memory task indicated that this benefit resulted from implicit learning. Similar implicit contextual cueing effects were also obtained when the scene to categorize was different from the subsequent search scene (Experiment 3) and when a mere preview of the search scene preceded the visual searching (Experiment 4). These results suggested that if enhancing the processing of the scene was required with the present material, such implicit semantic learning can nevertheless take place when the category is task irrelevant