Interactive Reputation Systems - How to Cope with Malicious Behavior in Feedback Mechanisms

Early reputation systems use simple computation metrics that can easily be manipulated by malicious actors. Advanced computation models that mitigate their weaknesses, however, are non-transparent to the end-users thus lowering their understandability and the users’ trust towards the reputation system. The paper proposes the concept of interactive reputation systems that combine the cognitive capabilities of the user with the advantages of robust metrics while preserving the system’s transparency. Results of the evaluation show that interactive reputation systems increase both the users’ detection ability (robustness) and understanding of malicious behavior while avoiding trade-offs in usability

TRIVIA: visualizing reputation profiles to detect malicious sellers in electronic marketplaces

Reputation systems are an essential part of electronic marketplaces that provide a valuable method to identify honest sellers and punish malicious actors. Due to the continuous improvement of the computation models applied, advanced reputation systems have become non-transparent and incomprehensible to the end-user. As a consequence, users become skeptical and lose their trust toward the reputation system. In this work, we are taking a step to increase the transparency of reputation systems by means of providing interactive visual representations of seller reputation profiles. We thereto propose TRIVIA - a visual analytics tool to evaluate seller reputation. Besides enhancing transparency, our results show that through incorporating the visual-cognitive capabilities of a human analyst and the computing power of a machine in TRIVIA, malicious sellers can be reliably identified. In this way we provide a new perspective on how the problem of robustness could be addressed

How to use human pose estimation to measure the hand-arm motion in craft application with no influence on the natural user behavior

The interaction between human and machine plays an important role in the design and optimization of human-machine systems. This interaction is characterized by human motion using the technical system. Especially in the field of hand and power tool applications, the motion capture should be performed under the real working condition and without influencing the user. There are already motion tracking systems that allow capturing the motion during the interaction, but there is no mobile motion capture system that allows an individual analysis of the user for biomechanical analysis in the normal work process without influencing him. Therefore, requirements for a motion capture system are derived and a system is presented that meets these requirements. This system consists of two cameras and is based on the pose estimation algorithm OpenPose. The comparison of the presented system and the state-of-the-art system Xsens is performed and based on the measured elbow angle and the wrist position. The results show a very good correspondence between the curve characteristic of the elbow angle and the wrist position of both systems. However, inexplicable values shifting at two different levels still occur, which need to be investigated further. Overall, the presented system shows great potential in terms of mobility and flexibility of the presented system with some weaknesses in the data processing and efficiency. By addressing these weaknesses, the presented system can be used in the analysis and optimization of human-machine systems

Tribological and mechanical properties of lubricant filled microcapsules in thermoplastic composites

Polymeric materials with long lifetime and low frictional energy loss are frequently required for a broad range of applications. Microencapsulation of lubricating oils by in-situ polymerization (melamine-formaldehyde) and interfacial polymerization (polyurethane/polyurea) was used to obtain free-flowing powders, which can be used as additive for thermoplastic materials resulting in microcapsule-containing self-lubricating composites. The specific functionality of such composites is achieved via portioned and localised release of the lubricant in the areas of the interface, which experiences the highest degrees of stress and wear due to the friction. Friction-triggered on-demand release of the lubricating oil results in materials with higher wear resistance and potentially leading to new products with prolonged lifetime. In this study, different ratios of microcapsules were added in polyoxymethylene (POM) and polybutylterephthalat (PBT) matrices by using laboratory scale twin-screw extruder resulting in self-lubricating composite materials. The effect of such modification on the tribological and mechanical properties of the thermoplastic composites were investigated. Rotational ball on disc tests were used to investigate the wear loss and coefficient of friction for the composites with varied microcapsule concentrations. Tensile tests revealed decreased mechanical stability for the composites with higher microcapsule content regardless of microcapsule wall material composition. Addition of 5 wt.- % of encapsulated lubricant oil led to the substantial decrease of the frictional and wear coefficients. Further increase of encapsulated lubricant oil content to 10 wt.-% had a major decreasing impact on the mechanical properties, whilst the effect on the tribological performance was rather small

Dynamic Trust-based Recertifications in Identity and Access Management

Security compliance has become an important topic for medium- and large-sized companies in the recent years. In order to fulfill all requirements legally imposed, high quality identity management – particularly with respect to correct and consistent access control – is essential. In this context, the concept of recertification has proven itself to maintain the quality and correctness of access rights over a long period of time. In this paper, we show how the traditional recertification concept can be notably enhanced through involving the notion of trust. We thereto propose a trust-based recertification model and demonstrate its benefits by means of a realistic use case. Our dynamic concept can help to better spread the recertification overhead compared to the traditional approach with fixed periods. Furthermore, it aids in the identification of risky employees

ApOL-Application Oriented Workload Model for Digital Human Models for the Development of Human-Machine Systems

Since musculoskeletal disorders are one of the most common work-related diseases for assemblers and machine operators, it is crucial to find new ways to alleviate the physical load on workers. Support systems such as exoskeletons or handheld power tools are promising technology to reduce the physical load on the humans. The development of such systems requires consideration of the interactions between human and technical systems. The physical relief effect of the exoskeleton can be demonstrated in experimental studies or by simulation with the digital human model (DHM). For the digital development of these support systems, an application-oriented representation of the workload is necessary. To facilitate digital development, an application-oriented workload model (ApOL model) of an overhead working task is presented. The ApOL model determines the load (forces, torques) onto the DHM during an overhead screw-in task using a cordless screwdriver, based on experimental data. The ApOL model is verified by comparing the simulated results to the calculated values from a mathematical model, using experimental data from three participants. The comparison demonstrates successful verification, with a maximum relative mean-absolute-error (rMAE) of the relevant load components at 11.4%. The presented ApOL model can be utilized to assess the impact of cordless screwdriver design on the human workload and facilitate a strain-based design approach for support systems e.g., exoskeletons

Evaluation of Active Shoulder Exoskeleton Support to Deduce Application-Oriented Optimization Potentials for Overhead Work

Repetitive overhead work with a heavy load increases the risk for work-related shoulder disorders. Occupational exoskeletons supporting arm elevation are potential solutions to reduce that risk by lowering the physical strains on the shoulder. Many studies have reported a reduction in shoulder stress in various overhead tasks by using such exoskeletons. However, the support demand can vary in each phase of motion as well as in each individual task. This paper presents a laboratory study with five participants to evaluate the influence of the support level of an active shoulder exoskeleton in different motion phases (e.g., arm lifting, screw-in, and arm lowering of two overhead tasks) to identify the potential optimization of support at each phase. Results show that the support level of the exoskeleton should be adapted to the motion phase of the two chosen tasks. A higher support force is desired for the screw phase compared to the arm lifting and lowering phases, and the support level needs to be reduced immediately for arm lowering after the screw phase. The time for switching the support levels can be recognized by the electric current of the screwdriver

Look Before You Leap: Improving the Users’ Ability to Detect Fraud in Electronic Marketplaces

Reputation systems in current electronic marketplaces can easily be manipulated by malicious sellers in order to appear more reputable than appropriate. We conducted a controlled experiment with 40 UK and 41 German participants on their ability to detect malicious behavior by means of an eBay-like feedback profile versus a novel interface involving an interactive visualization of reputation data. The results show that participants using the new interface could better detect and understand malicious behavior in three out of four attacks (the overall detection accuracy 77% in the new vs. 56% in the old interface). Moreover, with the new interface, only 7% of the users decided to buy from the malicious seller (the options being to buy from one of the available sellers or to abstain from buying), as opposed to 30% in the old interface condition