A Diameter firewall is essential for mobile operators to protect their subscribers, as Diameter networks lack end-to-end authentication and heavily rely on trust among partner operators. Among the various attacks exploiting the Diameter protocol, one notable example involves falsely updating a subscriber's location and illegitimately requesting authentication data. Conventional methods, known as velocity checks, validate the originating network of messages by assessing the plausibility of subscriber movement based solely on network-provided information. However, attackers can still bypass these checks by simulating their presence in nearby or bordering countries. This poster introduces a user-interactive Diameter firewall, which incorporates user engagement by allowing subscribers to confirm suspicious requests.

New augmented-reality near-eye displays provide capabilities for enriching real-world visual experiences with digital content. Most current research focuses on improving both hardware and software to provide digital content that seamlessly blends with the real world. This is believed to not only contribute to the visual experience but also increase human task performance. In this work, we take a step further and ask the question of whether the capabilities of current and future display designs combined with efficient perception-inspired content optimizations can be used to improve human task performance beyond the human capabilities in the natural world. Based on an in-depth analysis of previous literature, we hypothesize here that such enhancements can be achieved when the human visual system is provided with content that optimizes the oculomotor responses. To further investigate possible gains, we present a series of perceptual experiments that built upon this idea. More specifically, we focus on speeding up accommodation response, which significantly contributes to the eye-adaptation when a new stimulus is shown. Through our experiments, we demonstrate that such speedups canbe achieved, and more importantly, they can lead to significant improvements in human task performance. While not all of our results give definite answers, we believe that they reveal plentiful opportunities for further enhancing the human experience and task performance when using new augmented-reality displays.

Quality, diversity, and size of training data are critical factors for learning-based gaze estimators. We create two datasets satisfying these criteria for near-eye gaze estimation under infrared illumination: a synthetic dataset using anatomically-informed eye and face models with variations in face shape, gaze direction, pupil and iris, skin tone, and external conditions (2M images at 1280x960), and a real-world dataset collected with 35 subjects (2.5M images at 640x480). Using these datasets we train neural networks performing with sub-millisecond latency. Our gaze estimation network achieves 2.06(±0.44)° of accuracy across a wide 30°×40° field of view on real subjects excluded from training and 0.5° best-case accuracy (across the same FOV) when explicitly trained for one real subject. We also train a pupil localization network which achieves higher robustness than previous methods.

Varifocal displays are a practical method to solve vergence-accommodation conflict in near-eye displays for both virtual and augmented reality, but they are reliant on knowing the user's focal state. One approach for detecting the focal state is to use the link between vergence and accommodation and employ binocular gaze tracking to determine the depth of the fixation point; consequently, the focal depth is also known. In order to ensure the virtual image is in focus, the display must be set to a depth which causes no negative perceptual or physiological effects to the viewer, which indicates error bounds for the calculation of fixation point. I analyze the required gaze tracker accuracy to ensure the display focus is set within the viewer's depth of field, zone of comfort, and zone of clear single binocular vision. My findings indicate that for the median adult using an augmented reality varifocal display, gaze tracking accuracy must be better than 0.541°. In addition, I discuss eye tracking approaches presented in the literature to determine their ability to meet the specified requirements.

We describe a system which corrects dynamically for the focus of the real world surrounding the near-eye display of the user and simultaneously the internal display for augmented synthetic imagery, with an aim of completely replacing the user prescription eyeglasses. The ability to adjust focus for both real and virtual stimuli will be useful for a wide variety of users, but especially for users over 40 years of age who have limited accommodation range. Our proposed solution employs a tunable-focus lens for dynamic prescription vision correction, and a varifocal internal display for setting the virtual imagery at appropriate spatially registered depths. We also demonstrate a proof of concept prototype to verify our design and discuss the challenges to building an auto-focus augmented reality eyeglasses for both real and virtual.

Accommodative depth cues, a wide field of view, and ever-higher resolutions all present major hardware design challenges for near-eye displays. Optimizing a design to overcome one of these challenges typically leads to a trade-off in the others. We tackle this problem by introducing an all-in-one solution - a new wide field of view, gaze-tracked near-eye display for augmented reality applications. The key component of our solution is the use of a single see-through, varifocal deformable membrane mirror for each eye reflecting a display. They are controlled by airtight cavities and change the effective focal power to present a virtual image at a target depth plane which is determined by the gaze tracker. The benefits of using the membranes include wide field of view (100° diagonal) and fast depth switching (from 20 cm to infinity within 300 ms). Our subjective experiment verifies the prototype and demonstrates its potential benefits for near-eye see-through displays.

Abstract To simplify the difficult task of writing fault‐tolerant parallel software, we implemented extensions to the basic functionality of the LINDA or tuple‐space programming model. Our approach implements a mechanism oftransaction processingto ensure that tuples are properly handled in the event of a node or communications failure. If a process retrieving a tuple fails to complete processing or a tuple posting or retrieval message is lost, the system is automatically rolled back to a previous stable state. Processing failures and lost messages are detected by time‐out alarms. Roll‐back is accomplished by reposting pertinent tuples. Intermediate tuples produced during partial processing are not committed or made available until a process completes. In the absence of faults, system overhead is low. The fault‐tolerance mechanism is implemented at the system level and requires little programmer effort or expertise. Two implementations of the model are discussed, one using a UNIX network of workstations and one using a Transputer network. Data measuring model overhead and some aspects of system performance in the presence of faults is presented for an example system.