arXiv subjects

Lixia Zhang

Publications and source records attributed to Lixia Zhang.

At least 19 recordsLinked to original sources

arXiv2026

SRAN: Scaling NDN Routing via Map-and-Attach

Network routing scalability becomes difficult when forwarding state scales with an external identifier space rather than network topology. Named Data Networking (NDN) faces this challenge acutely because routing directly on application name prefixes ties forwarding state to an unbounded namespace. This paper presents SRAN, an intra-domain NDN routing architecture that applies the routing-scalability principle underlying Map-and-Encap through Map-and-Attach: application prefixes are mapped to egress routers, and the resulting mapping information is attached to the original Interest. This enables network routing and forwarding to operate on topological identifiers while keeping NDN Interests intact and preserving native NDN communication semantics, including Interest/Data exchange, in-network caching, and data-centric security. SRAN further uses the same prefix-to-egress mapping to realize Bit Index Explicit Replication (BIER) for scalable NDN Interest multicast. SRAN leverages existing NDN mechanisms to securely maintain prefix-to-router mappings among user-facing routers without introducing new protocols. Evaluation on Rocketfuel topologies shows that routers' forwarding state scales with network topology rather than application-prefix count, while prefix updates are disseminated in real time with low communication overhead.

cs.NI↗

arXiv2026

The Internet Runs on Names

The Internet's TCP/IP architecture was designed for resilient packet delivery between hosts identified by IP addresses. Over time, however, the consolidation of applications and services into large-scale platforms built on that universal packet-delivery substrate drove deployment practices that fundamentally changed the Internet's operational model: the network now operates primarily on names. DNS names have become the basis for service identity, reachability, load balancing, and trust, while IP addresses have become ephemeral routing locators. This change was driven by application needs and platform consolidation in the absence of any overarching plan. The resulting mismatch between the original address-based design and the current name-based operation leads to serious consequences: operational complexity that grows with each new layer of indirection, fragility, and vulnerability - as seen in recent high-profile outages. This paper exposes this mismatch as a necessary first step toward understanding its consequences and addressing the risks of continuing on the same path.

cs.NI↗

arXiv2026

From Map-and-Encap to BIER: Observations on Network Routing Scalability

The TCP/IP protocol stack uses IP addresses for two distinct roles: identifying hosts and locating their attachment points in the network topology. This dual purpose creates a fundamental tension that has led to routing and forwarding scalability challenges throughout the history of the Internet in unicast packet delivery and, more notably, in multicast delivery. This paper reviews the evolution of routing scalability solutions over the years and makes four observations. First, map-and-encap is a recurring architectural solution shared by all scalable unicast and multicast delivery methods, developed independently across different problem contexts. Second, a new solution tends to succeed when it can bring immediate local gains to early adopters without requiring coordination across administrative domains. Third, network routing and forwarding designs that depend on external factors, such as the number of distinct end sites or even application-specific deliveries, inherently preclude an upper bound on their scalability. Fourth, today's inter-domain routing protocol, BGP, lacks a topological abstraction equivalent to an egress router within a routing domain, thereby inherently preventing a map-and-encap solution for scalability. These observations offer insights into the design of future scalable routing system architectures.

cs.NI↗

arXiv2026

Intelligent Pathological Diagnosis of Gestational Trophoblastic Diseases via Visual-Language Deep Learning Model

The pathological diagnosis of gestational trophoblastic disease(GTD) takes a long time, relies heavily on the experience of pathologists, and the consistency of initial diagnosis is low, which seriously threatens maternal health and reproductive outcomes. We developed an expert model for GTD pathological diagnosis, named GTDoctor. GTDoctor can perform pixel-based lesion segmentation on pathological slides, and output diagnostic conclusions and personalized pathological analysis results. We developed a software system, GTDiagnosis, based on this technology and conducted clinical trials. The retrospective results demonstrated that GTDiagnosis achieved a mean precision of over 0.91 for lesion detection in pathological slides (n=679 slides). In prospective studies, pathologists using GTDiagnosis attained a Positive Predictive Value of 95.59% (n=68 patients). The tool reduced average diagnostic time from 56 to 16 seconds per case (n=285 patients). GTDoctor and GTDiagnosis offer a novel solution for GTD pathological diagnosis, enhancing diagnostic performance and efficiency while maintaining clinical interpretability.

cs.CV↗

arXiv2026

The Landscape of Prompt Injection Threats in LLM Agents: From Taxonomy to Analysis

The evolution of Large Language Models (LLMs) has resulted in a paradigm shift towards autonomous agents, necessitating robust security against Prompt Injection (PI) vulnerabilities where untrusted inputs hijack agent behaviors. This SoK presents a comprehensive overview of the PI landscape, covering attacks, defenses, and their evaluation practices. Through a systematic literature review and quantitative analysis, we establish taxonomies that categorize PI attacks by payload generation strategies (heuristic vs. optimization) and defenses by intervention stages (text, model, and execution levels). Our analysis reveals a key limitation shared by many existing defenses and benchmarks: they largely overlook context-dependent tasks, in which agents are authorized to rely on runtime environmental observations to determine actions. To address this gap, we introduce AgentPI, a new benchmark designed to systematically evaluate agent behavior under context-dependent interaction settings. Using AgentPI, we empirically evaluate representative defenses and show that no single approach can simultaneously achieve high trustworthiness, high utility, and low latency. Moreover, we show that many defenses appear effective under existing benchmarks by suppressing contextual inputs, yet fail to generalize to realistic agent settings where context-dependent reasoning is essential. This SoK distills key takeaways and open research problems, offering structured guidance for future research and practical deployment of secure LLM agents.

cs.CR↗

arXiv2025

SRM at 30: Lessons from Early Data-Centric Networking and Their Impact on Named Data Networking

A 1995 SIGCOMM paper, "A Reliable Multicast Framework for Light-weight Sessions and Application-Level Framing", commonly known as SRM, explored a fundamentally new approach to reliable multiparty data delivery. Rather than adapting established sender-driven reliable unicast mechanisms to multicast, as most contemporaneous proposals did, SRM introduced a data-centric model in which data receivers recover losses by explicitly requesting missing data. Thirty years later, we revisit the SRM framework, examining the challenges it faced, the lessons learned, and its influence on the later development of Named Data Networking (NDN). Experimentations with SRM revealed a fundamental semantic mismatch between its data-centric framework and IP's address-based delivery; while the application layer named data, the network layer remained 'blind' to those names, resulting in inefficient loss recovery. NDN resolves this architectural friction by aligning network delivery with the data-retrieval model and by securing data directly rather than securing communication channels. This retrospective highlights how early insights from SRM informed key design decisions in NDN and illustrates how NDN's design emerged from the cumulative insights gained over decades of networking research and development.

cs.NI↗

arXiv2025

Observatory Science with eXTP

Scheduled for launch in 2030, the enhanced X-ray Timing and Polarization (eXTP) telescope is a Chinese space-based mission aimed at studying extreme conditions and phenomena in astrophysics. eXTP will feature three main payloads: Spectroscopy Focusing Arrays (SFAs), Polarimetry Focusing Arrays (PFAs), and a Wide-field Camera (W2C). This white paper outlines observatory science, incorporating key scientific advances and instrumental changes since the publication of the previous white paper [1]. We will discuss perspectives of eXTP on the research domains of flare stars, supernova remnants, pulsar wind nebulae, cataclysmic variables, X-ray binaries, ultraluminous X-ray sources, AGN, and pulsar-based positioning and timekeeping.

astro-ph.IM↗

arXiv2024

A Novel Approach to Malicious Code Detection Using CNN-BiLSTM and Feature Fusion

With the rapid advancement of Internet technology, the threat of malware to computer systems and network security has intensified. Malware affects individual privacy and security and poses risks to critical infrastructures of enterprises and nations. The increasing quantity and complexity of malware, along with its concealment and diversity, challenge traditional detection techniques. Static detection methods struggle against variants and packed malware, while dynamic methods face high costs and risks that limit their application. Consequently, there is an urgent need for novel and efficient malware detection techniques to improve accuracy and robustness. This study first employs the minhash algorithm to convert binary files of malware into grayscale images, followed by the extraction of global and local texture features using GIST and LBP algorithms. Additionally, the study utilizes IDA Pro to decompile and extract opcode sequences, applying N-gram and tf-idf algorithms for feature vectorization. The fusion of these features enables the model to comprehensively capture the behavioral characteristics of malware. In terms of model construction, a CNN-BiLSTM fusion model is designed to simultaneously process image features and opcode sequences, enhancing classification performance. Experimental validation on multiple public datasets demonstrates that the proposed method significantly outperforms traditional detection techniques in terms of accuracy, recall, and F1 score, particularly in detecting variants and obfuscated malware with greater stability. The research presented in this paper offers new insights into the development of malware detection technologies, validating the effectiveness of feature and model fusion, and holds promising application prospects.

cs.CR↗

arXiv2024

Secure Web Objects: Building Blocks for Metaverse Interoperability and Decentralization

This position paper explores how to support the Web's evolution through an underlying data-centric approach that better matches the data-orientedness of modern and emerging applications. We revisit the original vision of the Web as a hypermedia system that supports document composability and application interoperability via name-based data access. We propose the use of secure web objects (SWO), a data-oriented communication approach that can reduce complexity, centrality, and inefficiency, particularly for collaborative and local-first applications, such as the Metaverse and other collaborative applications. SWO are named, signed, application-defined objects that are secured independently of their containers or communications channels, an approach that leverages the results from over a decade-long data-centric networking research. This approach does not require intermediation by aggregators of identity, storage, and other services that are common today. We present a brief design overview, illustrated through prototypes for two editors of shared hypermedia documents: one for 3D and one for LaTeX. We also discuss our findings and suggest a roadmap for future research.

cs.NI↗

arXiv2024

Exploring the Design of Collaborative Applications via the Lens of NDN Workspace

Metaverse applications desire to communicate with semantically identified objects among a diverse set of cyberspace entities, such as cameras for collecting images from, sensors for sensing environment, and users collaborating with each other, all could be nearby or far away, in a timely and secure way. However, supporting the above function faces networking challenges. Today's metaverse implementations are, by and large, use secure transport connections to communicate with cloud servers instead of letting participating entities communicate directly. In this paper, we use the design and implementation of NDN Workspace, a web-based, multi-user collaborative app to showcase a new way to networking that supports many-to-many secure data exchanges among communicating entities directly. NDN Workspace users establish trust relations among each other, exchange URI-identified objects directly, and can collaborate through intermittent connectivity, all in the absence of cloud servers. Its data-centric design offers an exciting new approach to metaverse app development.

cs.NI↗

arXiv2023

Enhancing NAC-ABE to Support Access Control for mHealth Applications and Beyond

Name-based access control (NAC) over NDN provides fine-grained data confidentiality and access control by encrypting and signing data at the time of data production. NAC utilizes specially crafted naming conventions to define and enforce access control policies. NAC-ABE, an extension to NAC, uses an attribute-based encryption (ABE) scheme to support access control with improved scalability and flexibility. However, existing NAC-ABE libraries are based on ciphertext-policy ABE (CP-ABE), which requires knowledge of the access policy when encrypting data packets. In some applications, including mHealth, the data access policy is unknown at the time of data generation, while data attributes and properties are known. In this paper, we present an extension to the existing NDN-ABE library which can be used by mHealth and other applications to enforce fine-granularity access control in data sharing. We also discuss the challenges we encountered during the application deployment, and remaining open issues together with potential solution directions.

cs.CR↗

arXiv2023

On the Security Bootstrapping in Named Data Networking

By requiring all data packets been cryptographically authenticatable, the Named Data Networking (NDN) architecture design provides a basic building block for secured networking. This basic NDN function requires that all entities in an NDN network go through a security bootstrapping process to obtain the initial security credentials. Recent years have witnessed a number of proposed solutions for NDN security bootstrapping protocols. Built upon the existing results, in this paper we take the next step to develop a systematic model of security bootstrapping: Trust-domain Entity Bootstrapping (TEB). This model is based on the emerging concept of trust domain and describes the steps and their dependencies in the bootstrapping process. We evaluate the expressiveness and sufficiency of this model by using it to describe several current bootstrapping protocols.

cs.CR↗

arXiv2023

Characterizing the emission region property of blazars

The studies and constraints on the emission region are crucial to the blazar radiation mechanism. Yet the previous works mainly focus on individual sources. In this work, we make use of the largest and the latest spectral energy distribution (SED) fitting results in the literature to statistically study the blazar emission region property in the framework of leptonic one-zone. Our results reveal (1) FSRQs show lower electron energy ($γ_{\rm p} \lesssim 1.6 \times 10^{3}$) than BL Lacs and tend to have a stronger magnetic field ($B$) and smaller electron-to-magnetic energy ratio ($U_{\rm e}/U_{\rm B}$) than BL Lacs; (2) we find the electro-magnetic equipartition would rather happen in the jets of BL Lacs than happen in the jets of FSRQs; (3) there are 682 blazars with a magnetic field weaker critical value of generating the Kelvin-Helmholtz instability, thus one-third of the blazars in our sample are able to produce this instability; (4) the distance ($d_{\rm em}$) between the emission region and the central black hole (BH) is in the scale of $\sim$0.1 pc, the location of the emission region may be evenly distributed inside and outside the broad line region (BLR).

astro-ph.HE↗

arXiv2022

Generalized weighted number operators on functionals of discrete-time normal martingales

Let $M$ be a discrete-time normal martingale that has the chaotic representation property. Then, from the space of square integrable functionals of $M$, one can construct generalized functionals of $M$. In this paper, by using a type of weights, we introduce a class of continuous linear operators acting on generalized functionals of $M$, which we call generalized weighted number (GWN) operators. We prove that GWN operators can be represented in terms of generalized annihilation and creation operators (acting on generalized functionals of $M$). We also examine commutation relations between a GWN operator and a generalized annihilation (or creation) operator, and obtain several formulas expressing such commutation relations.

math.PR↗

arXiv2022

Hydra -- A Federated Data Repository over NDN

Today's big data science communities manage their data publication and replication at the application layer. These communities utilize myriad mechanisms to publish, discover, and retrieve datasets - the result is an ecosystem of either centralized, or otherwise a collection of ad-hoc data repositories. Publishing datasets to centralized repositories can be process-intensive, and those repositories do not accept all datasets. The ad-hoc repositories are difficult to find and utilize due to differences in data names, metadata standards, and access methods. To address the problem of scientific data publication and storage, we have designed Hydra, a secure, distributed, and decentralized data repository made of a loose federation of storage servers (nodes) provided by user communities. Hydra runs over Named Data Networking (NDN) and utilizes the State Vector Sync (SVS) protocol that lets individual nodes maintain a "global view" of the system. Hydra provides a scalable and resilient data retrieval service, with data distribution scalability achieved via NDN's built-in data anycast and in-network caching and resiliency against individual server failures through automated failure detection and maintaining a specific degree of replication. Hydra utilizes "Favor", a locally calculated numerical value to decide which nodes will replicate a file. Finally, Hydra utilizes data-centric security for data publication and node authentication. Hydra uses a Network Operation Center (NOC) to bootstrap trust in Hydra nodes and data publishers. The NOC distributes user and node certificates and performs the proof-of-possession challenges. This technical report serves as the reference for Hydra. It outlines the design decisions, the rationale behind them, the functional modules, and the protocol specifications.

cs.NI↗

arXiv2022

Coiling of cellular protrusions around extracellular fibers

Protrusions at the leading-edge of a cell play an important role in sensing the extracellular cues, during cellular spreading and motility. Recent studies provided indications that these protrusions wrap (coil) around the extra-cellular fibers. The details of this coiling process, and the mechanisms that drive it, are not well understood. We present a combined theoretical and experimental study of the coiling of cellular protrusions on fibers of different geometry. Our theoretical model describes membrane protrusions that are produced by curved membrane proteins that recruit the protrusive forces of actin polymerization, and identifies the role of bending and adhesion energies in orienting the leading-edges of the protrusions along the azimuthal (coiling) direction. Our model predicts that the cell's leading-edge coils on round fibers, but the coiling ceases for a fiber of elliptical (flat) cross-section. These predictions are verified by 3D visualization and quantitation of coiling on suspended fibers using Dual-View light-sheet microscopy (diSPIM). Overall, we provide a theoretical framework supported by high spatiotemporal resolution experiments capable of resolving coiling of cellular protrusions around extracellular fibers of varying diameters.

physics.bio-ph↗

arXiv2021

The relativistic jet and its central engine of $Fermi$ blazars

Jet origination is one of the most important questions of AGN, yet it stays obscure. In this work, we made use of information of emission lines, spectral energy distributions (SEDs), \textit{Fermi}-LAT $γ$-ray emission, construct a blazar sample that contains 667 sources. We notice that jet power originations are different for BL Lacs and for FSRQs. The correlation between jet power $P_{\rm jet}$ and the normalized disk luminosity $L_{\rm Disk}/L_{\rm Edd}$ shows a slope of -1.77 for BL Lacs and a slope of 1.16 for FSRQs. The results seem to suggest that BL Lac jets are powered by extracting blackhole rotation energy, while FSRQ jets are mostly powered by accretion disks. Meanwhile, we find the accretion ratio $\dot{M} / \dot{M}_{\rm Edd}$ increase with the normalized $γ$-ray luminosity. Base on this, we propose a dividing line, ${\rm log} (L_{\rm BLR}/L_{\rm Edd}) = 0.25 \ {\rm log} (L_{\rm γ}/L_{\rm Edd}) - 2.23$, to separate FSRQs and BL Lacs in the diagram of $L_{\rm BLR}/L_{\rm Edd}$ against $L_{\rm γ}/L_{\rm Edd}$ through using the machine learning method, the method gives an accuracy of 84.5\%. In addition, we propose an empirical formula, $M_{\rm BH}/M_{\rm \odot} \simeq L_{\rm γ}^{0.65}/21.46$, to estimate blackhole mass based on a strong correlation between $γ$-ray luminosity and blackhole mass. Strong $γ$-ray emission is typical in blazars, and the emission is always boosted by a Doppler beaming effect. In this work, we generate a new method to estimate a lower-limit of Doppler factor $δ$ and give $δ_{\rm BL Lac} = 7.94$ and $δ_{\rm FSRQ} = 11.55$.

astro-ph.HE↗

arXiv2021

Sovereign: User-Controlled Smart Homes

Recent years have witnessed the rapid deployment of smart homes; most of them are controlled by remote servers in the cloud. Such designs raise security and privacy concerns for end users. In this paper, we describe the design of Sovereign, a home IoT system framework that provides end users complete control of their home IoT systems. Sovereign lets home IoT devices and applications communicate via application-named data and secures data directly. This enables direct, secure, one-to-one and one-to-many device-to-device communication over wireless broadcast media. Sovereign utilizes semantic names to construct usable security solutions. We implement Sovereign as a publish-subscribe-based development platform together with a prototype home IoT controller. Our preliminary evaluation shows that Sovereign provides a systematic, easy-to-use solution to user-controlled, self-contained smart homes running on existing IoT hardware without imposing noticeable overhead.

cs.NI↗