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Muaz Ali

Publications and source records attributed to Muaz Ali.

4 recordsLinked to original sources

Attacking the First-Principle: A Black-Box, Query-Free Targeted Mimicry Attack on Binary Function Classifiers

Binary function classifiers play a crucial role in maintaining the security and integrity of software systems by detecting malicious code and unauthorized modifications. However, machine learning-based classifiers are vulnerable to adversarial attacks that can evade detection. In this study, we present Kelpie, a novel framework for executing mimicry attacks, a stronger type of targeted evasion attacks, on binary function classifiers in a black-box, zero-query setting. Unlike previous approaches that rely on querying the target classifier to refine untargeted evasion attacks, Kelpie leverages code transformations that preserve the functionality of malicious payloads while causing them to be misclassified as we want. Through extensive experimentation, we demonstrate that Kelpie can successfully execute mimicry attacks against six state-of-the-art binary function classifiers representing different model architectures without requiring direct interaction with them. We further validate our approach with a practical demonstration, involving a keylogger and a wiper concealed within benign-looking functions embedded in an application. This work, to our best knowledge, is the first to demonstrate such a mimicry attack in a black-box, zero-query context, raising important questions about the reliability and security of existing machine learning-based binary function classifiers.

cs.LG

Starlink Constellation: Deployment, Configuration, and Dynamics

Starlink has rapidly emerged as the world's largest satellite constellation and the de facto reference system for low Earth orbit (LEO) networking research. Existing literature predominantly models Starlink as a static, symmetric, and fully deployed structure with uniformly distributed satellites. However, we reveal that Starlink's actual deployment, orbital configurations, and operational dynamics fundamentally deviate from these idealized assumptions. Leveraging satellite observation data spanning 2019 to 2025, we demonstrate that the constellation is highly dynamic across multiple temporal and spatial scales. Macroscopically, Starlink comprises multiple orbital shells undergoing continuous active deployment and reconfiguration. Microscopically, individual satellites exhibit high mobility, frequently executing collision-avoidance maneuvers, altitude adjustments, and intra-orbital relocations. We discover that while the majority of satellites form a relatively stable structure with near-uniform spacing, other satellites tend to cluster as twins or triads as in-orbit backups. Furthermore, empirical survival analysis indicates an operational lifespan of 4-6 years and an average daily failure probability of 0.0128%. Ultimately, our data-driven characterization exposes Starlink as a highly heterogeneous and continuously evolving network. We provide critical empirical insights that challenge prevailing simulation models, offering a more accurate foundation for future LEO topology design, routing protocols, and performance evaluations.

cs.NI

LEO Topology Design Under Real-World Deployment Constraints

The performance of large-scale Low-Earth-Orbit (LEO) networks, which consist of thousands of satellites interconnected by optical links, is dependent on its network topology. Existing topology designs often assume idealized conditions and do not account for real-world deployment dynamics, such as partial constellation deployment, daily node turnovers, and varying link availability, making them inapplicable to real LEO networks. In this paper, we develop two topology design methods that explicitly operate under real-world deployment constraints: the Long--Short Links (LSL) method, which systematically combines long-distance shortcut links with short-distance local links, and the Simulated Annealing (SA) method, which constructs topologies via stochastic optimization. Evaluated under both full deployment and partial deployment scenarios using 3-months of Starlink data, our methods achieve up to 45% lower average end-to-end delay, 65% fewer hops, and up to $2.3\times$ higher network capacity compared to +Grid. Both methods are designed to handle daily node turnovers by incrementally updating the topology, maintaining good network performance while avoiding costly full reconstruction of the topology.

cs.NI

VaulTor: Putting the TEE in Tor

Online services that desire to operate anonymously routinely host themselves as 'Hidden Services' in the Tor network. However, these services are frequently threatened by deanonymization attacks, whereby their IP address and location may be inferred by the authorities. We present VaulTor, a novel architecture for the Tor network to ensure an extra layer of security for the Hidden Services against deanonymization attacks. In this new architecture, a volunteer (vault) is incentivized to host the web application content on behalf of the Hidden Service. The vault runs the hosted application in a Trusted Execution Environment (TEE) and becomes the point of contact for interested clients. This setup can substantially reduce the uptime requirement of the original Hidden Service provider and hence significantly decrease the chance of deanonymization attacks against them. We also show that the VaulTor architecture does not cause any noticeable performance degradation in accessing the hosted content (the performance degradation ranges from 2.6-5.5%).

cs.CR