Industrial practitioners' mental models of adversarial machine learning

Although machine learning is widely used in practice, little is known about practitioners' understanding of potential security challenges. In this work, we close this substantial gap and contribute a qualitative study focusing on developers' mental models of the machine learning pipeline and potentially vulnerable components. Similar studies have helped in other security fields to discover root causes or improve risk communication. Our study reveals two facets of practitioners' mental models of machine learning security. Firstly, practitioners often confuse machine learning security with threats and defences that are not directly related to machine learning. Secondly, in contrast to most academic research, our participants perceive security of machine learning as not solely related to individual models, but rather in the context of entire workflows that consist of multiple components. Jointly with our additional findings, these two facets provide a foundation to substantiate mental models for machine learning security and have implications for the integration of adversarial machine learning into corporate workflows, decreasing practitioners' reported uncertainty, and appropriate regulatory frameworks for machine learning security

Shape Evasion: Preventing Body Shape Inference of Multi-Stage Approaches

Modern approaches to pose and body shape estimation have recently achieved strong performance even under challenging real-world conditions. Even from a single image of a clothed person, a realistic looking body shape can be inferred that captures a users' weight group and body shape type well. This opens up a whole spectrum of applications -- in particular in fashion -- where virtual try-on and recommendation systems can make use of these new and automatized cues. However, a realistic depiction of the undressed body is regarded highly private and therefore might not be consented by most people. Hence, we ask if the automatic extraction of such information can be effectively evaded. While adversarial perturbations have been shown to be effective for manipulating the output of machine learning models -- in particular, end-to-end deep learning approaches -- state of the art shape estimation methods are composed of multiple stages. We perform the first investigation of different strategies that can be used to effectively manipulate the automatic shape estimation while preserving the overall appearance of the original image

Quick response code secure: a cryptographically secure anti-phishing tool for QR code attacks.

The two-dimensional quick response (QR) codes can be misleading due to the difficulty in differentiating a genuine QR code from a malicious one. Since, the vulnerability is practically part of their design, scanning a malicious QR code can direct the user to cloned malicious sites resulting in revealing sensitive information. In order, to evaluate the vulnerabilities and propose subsequent countermeasures, we demonstrate this type of attack through a simulated experiment, where a malicious QR code directs a user to a phishing site. For our experiment, we cloned Google's web page providing access to their email service (Gmail). Since, the URL is masqueraded into the QR code the unsuspecting user who opens the URL is directed to the malicious site. Our results proved that hackers could easily leverage QR codes into phishing attack vectors targeted at smartphone users, even bypassing web browsers safe browsing feature. In addition, the second part of our paper presents adequate countermeasures and introduces QRCS (Quick Response Code Secure). QRCS is a universal efficient and effective solution focusing exclusively on the authenticity of the originator and consequently, the integrity of QR code by using digital signatures

Upgrade capacity scenarios enabled by multi-band optical systems

The ITU-G.652D is the most deployed optical fiber worldwide and presents a wide low-loss window with negligible water absorption peak. Multi-band systems exploit this characteristic to increase the transmission capacity. In this work, we show the optical degradation in terms of generalized signal-to-noise ratio, on different bands, resulting from successive channel upgrades until the complete low-loss window is occupied

A semi-automated security advisory system to resist cyber-attack in social networks

Social networking sites often witness various types of social engineering (SE) attacks. Yet, limited research has addressed the most severe types of social engineering in social networks (SNs). The present study investigates the extent to which people respond differently to different types of attack in a social network context and how we can segment users based on their vulnerability. In turn, this leads to the prospect of a personalised security advisory system. 316 participants have completed an online-questionnaire that includes a scenario-based experiment. The study result reveals that people respond to cyber-attacks differently based on their demographics. Furthermore, people’s competence, social network experience, and their limited connections with strangers in social networks can decrease their likelihood of falling victim to some types of attacks more than others

The influence of processing on key properties of cellulose fibre filled PP composites and extruded hollow profiles

Zu den wichtigsten Einflussgrößen auf die Eigenschaften von extrudierten Hohlkammerprofilen zählen neben Matrixpolymeren und Haftvermittlern die technologischen Ausrüstungen und Bedingungen. Um das Leistungs-potential von Fasern und darauf basierenden Materialsystemen möglichst weitgehend in Profile zu überführen, müssen die Fasern mit geeigneten Anlagen in den Extruder dosiert werden können. Um eine homogene Schmelze zu erzeugen, sind geeignete PP-Typen (Schmelzverhalten, Viskositäten) auszuwählen. Die optimalen Prozessfenster müssen insbesondere gewährleisten, dass die Fasern nicht geschädigt werden und ein ausreichend hoher Schmelzedruck für die Versorgung aller Bereiche der Werkzeuge erzeugt wird. Das Ergebnis muss am Bauteil überprüft werden, z. B. durch gut differenzierende Biegeprüfungen. Noch detailliertere Ergebnisse erbrachte ein Stochastikprogramm: Abhängig von der Position im Profil wurden Material-Kennwerte wie E-Modul und Biegefestigkeit untersucht.. Es ist davon auszugehen das ein iterativer Optimierungsprozess erforderlich ist, der Materialsysteme, technologische Bedingungen und Bauteilkonstruktion beinhaltet