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Software security testing, particularly when enhanced with deep learning models, has become a powerful approach for improving software quality, enabling faster detection of known flaws in source code. However, many approaches miss post-fix…
Modern distributed systems employ aggressive optimization strategies that create latent risks - hidden vulnerabilities where exceptional performance masks catastrophic fragility when optimizations fail. Cache layers achieving 99% hit rates…
Low Earth Orbit (LEO) satellite networks are increasingly essential for space-based artificial intelligence (AI) applications. However, as commercial use expands, LEO satellite networks face heightened cyberattack risks, especially through…
The rapid proliferation of satellite constellations, particularly in Low Earth Orbit (LEO), has fundamentally altered the global space infrastructure, shifting the risk landscape from purely kinetic collisions to complex cyber-physical…
The number of low Earth orbit (LEO) satellite constellations has grown rapidly in recent years, bringing a major change to global wireless communications. As LEO satellite links take on a growing role in critical services such as emergency…
The high mobility of satellites in Low Earth Orbit (LEO) mega-constellations induces a highly dynamic network topology, leading to many problems like frequent service disruptions. To mitigate this, Packet-based Load Balancing (PBLB) is…
Resilient routing in large-scale Low Earth Orbit (LEO) satellite networks remains a key challenge due to frequent and unpredictable link and node failures, potentially in response to cybersecurity breaches. While prior work has explored…
Today's Low Earth Orbit (LEO) satellite networks, exemplified by SpaceX's Starlink, play a crucial role in delivering global internet access to millions of users. However, managing the dynamic and expansive nature of these networks poses…
The increased capabilities of modern real-time systems (RTS) expose them to various security threats. Recently, frameworks that integrate security tasks without perturbing the real-time tasks have been proposed, but they only target single…
Production LLM deployments increasingly maintain heterogeneous model pools spanning order-of-magnitude cost differences. Existing routers make binary strong-vs-weak decisions and couple learned parameters to specific model identities,…
Low Earth Orbit (LEO) satellite mega-constellations aim to enable high-speed Internet for numerous users anywhere on Earth. To safeguard their network infrastructure in congested outer space, they perform automatic orbital maneuvers to…
Machine learning drives Channel State Information (CSI)-based human sensing in modern wireless networks, enabling applications like device-free human activity recognition (HAR) and identification (HID). However, the susceptibility of these…
Temporal Graph Neural Networks (TGNNs) have become indispensable for analyzing dynamic graphs in critical applications such as social networks, communication systems, and financial networks. However, the robustness of TGNNs against…
In this paper, we investigate the performance of large-scale heterogeneous low Earth orbit (LEO) satellite networks in the context of three association schemes. In contrast to existing studies, where single-tier LEO satellite-based network…
This paper presents an new approach for detecting in the electrical power system of satellites operating in Low Earth Orbit (LEO) without an Attitude Determination and Control Subsystem (ADCS). Components of these systems are prone to…
Hardware faults on the regular 2-D computing array of a typical deep learning accelerator (DLA) can lead to dramatic prediction accuracy loss. Prior redundancy design approaches typically have each homogeneous redundant processing element…
Low Earth orbit (LEO) mega-constellation satellite networks have shown great potential to extend the coverage capability of conventional terrestrial networks. How to systematically define, quantify, and assess the technical performance of…
Low-orbit mega-constellation network, which utilize thousands of satellites to provide a variety of network services and collect a wide range of space information, is a rapidly growing field. Each satellite collects TB-level data daily,…
Low-cost, vision-centric 3D perception systems for autonomous driving have made significant progress in recent years, narrowing the gap to expensive LiDAR-based methods. The primary challenge in becoming a fully reliable alternative lies in…
The low-earth-orbit (LEO) satellite network with mega-constellations can provide global coverage while supporting the high-data rates. The coverage performance of such a network is highly dependent on orbit geometry parameters, including…