Related papers: Nahida: In-Band Distributed Tracing with eBPF
Searchable Symmetric Encryption (SSE) allows users to search over encrypted data stored on untrusted servers, like cloud providers. While SSE hides the content of queries and documents, it still leaks patterns, such as how often a query is…
This paper presents Packet Chasing, an attack on the network that does not require access to the network, and works regardless of the privilege level of the process receiving the packets. A spy process can easily probe and discover the…
Performance analysis of microservices can be a challenging task, as a typical request to these systems involves multiple Remote Procedure Calls (RPC) spanning across independent services and machines. Practitioners primarily rely on…
Embedded distributed inference of Neural Networks has emerged as a promising approach for deploying machine-learning models on resource-constrained devices in an efficient and scalable manner. The inference task is distributed across a…
Tracing serves as a key method for evaluating the performance of microservices-based architectures, which are renowned for their scalability, resource efficiency, and high availability. Despite their advantages, these architectures often…
Microservice systems expose rich telemetry streams, including metrics, logs, and distributed traces. Existing performance anomaly detection methods increasingly model these systems as graphs, where nodes represent services and edges…
Modern cloud applications delivering global services are often built on distributed systems with a microservice architecture. In such systems, end-to-end user requests traverse multiple different services and machines, exhibiting intricate…
Sharding has emerged as a critical solution to address the scalability challenges faced by blockchain networks, enabling them to achieve higher transaction throughput, reduced latency, and optimized resource usage. This paper investigates…
By placing computation resources within a one-hop wireless topology, the recent edge computing paradigm is a key enabler of real-time Internet of Things (IoT) applications. In the context of IoT scenarios where the same information from a…
A wide variety of deep neural applications increasingly rely on the cloud to perform their compute-heavy inference. This common practice requires sending private and privileged data over the network to remote servers, exposing it to the…
In the recent years, cybersecurity has gained high relevance, converting the detection of attacks or intrusions into a key task. In fact, a small breach in a system, application, or network, can cause huge damage for the companies. However,…
Edge computing is a fast-growing computing paradigm where data is processed at the local site where it is generated, close to the end-devices. This can benefit a set of disruptive applications like autonomous driving, augmented reality, and…
This paper introduces Mayfly, a federated analytics approach enabling aggregate queries over ephemeral on-device data streams without central persistence of sensitive user data. Mayfly minimizes data via on-device windowing and contribution…
The rapid expansion of the Internet of Things (IoT) has intensified security challenges, notably from Distributed Denial of Service (DDoS) attacks launched by compromised, resource-constrained devices. Traditional defenses are often…
Distributed tracing has become a fundamental tool for diagnosing performance issues in the cloud by recording causally ordered, end-to-end workflows of request executions. However, tracing in production workloads can introduce significant…
System-level resource monitoring with both precision and efficiency is a continuous challenge. We introduce eHashPipe, a lightweight, real-time resource observability system utilizing eBPF and the HashPipe sketching algorithm. eHashPipe…
It is generally recognized that the traffic generated by an individual connected to a network acts as his biometric signature. Several tools exploit this fact to fingerprint and monitor users. Often, though, these tools assume to access the…
Contact tracing is an important method to control the spread of an infectious disease such as COVID-19. However, existing contact tracing methods alone cannot provide sufficient coverage and do not successfully address privacy concerns of…
This article examines the significant challenges encountered in implementing sharding within distributed replication systems. It identifies the impediments of achieving consensus among large participant sets, leading to scalability,…
Service discovery is a crucial component in today's massively distributed applications. In this paper, we propose NDNSD -- a fully distributed and general-purpose service discovery protocol for Named Data Networking (NDN). By leveraging…