Amyand's hernias in childhood (a report on 21 patients): a single-centre experience

Amyand's hernia is a very rare type of hernia and is characterised by the presence of a vermiform appendix in the inguinal hernia sac. It may present as a tender inguinal or inguinoscrotal swelling, and is usually misdiagnosed as an irreducible or strangulated inguinal hernia. This is a presentation of our experiences with these unusual hernias

Vulnerability Prediction from Source Code Using Machine Learning

As the role of information and communication technologies gradually increases in our lives, software security becomes a major issue to provide protection against malicious attempts and to avoid ending up with noncompensable damages to the system. With the advent of data-driven techniques, there is now a growing interest in how to leverage machine learning (ML) as a software assurance method to build trustworthy software systems. In this study, we examine how to predict software vulnerabilities from source code by employing ML prior to their release. To this end, we develop a source code representation method that enables us to perform intelligent analysis on the Abstract Syntax Tree (AST) form of source code and then investigate whether ML can distinguish vulnerable and nonvulnerable code fragments. To make a comprehensive performance evaluation, we use a public dataset that contains a large amount of function-level real source code parts mined from open-source projects and carefully labeled according to the type of vulnerability if they have any.We show the effectiveness of our proposed method for vulnerability prediction from source code by carrying out exhaustive and realistic experiments under different regimes in comparison with state-of-art methods

SoK:Investigation of security and functional safety in industrial IoT

There has been an increasing popularity of industrial usage of Internet of Things (IoT) technologies in parallel to advancements in connectivity and automation. Security vulnerabilities in industrial systems, which are considered less likely to be exploited in conventional closed settings, have now started to be a major concern with Industrial IoT. One of the critical components of any industrial control system turning into a target for attackers is functional safety. This vital function is not originally designed to provide protection against malicious intentional parties but only accidents and errors. In this paper, we explore a generic IoT-based smart manufacturing use-case from a combined perspective of security and functional safety, which are indeed tightly correlated. Our main contribution is the presentation of a taxonomy of threats targeting directly the critical safety function in industrial IoT applications. Besides, based on this taxonomy, we identified particular attack scenarios that might have severe impact on physical assets like manufacturing equipment, even human life and cyber-assets like availability of Industrial IoT application. Finally, we recommend some solutions to mitigate such attacks based mainly on industry standards and advanced security features of mobile communication technologies