Dissent in Numbers: Making Strong Anonymity Scale

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The advancement of face recognition technology has delivered substantial societal advantages. However, it has also raised global privacy concerns due to the ubiquitous collection and potential misuse of individuals' facial data. This presents a notable par ...

Federated learning is a semi-distributed algorithm, where a server communicates with multiple dispersed clients to learn a global model. The federated architecture is not robust and is sensitive to communication and computational overloads due to its one-m ...

Humans can express their actions and intentions, resorting to verbal and/or non-verbal communication. In verbal communication, humans use language to express, in structured linguistic terms, the desired action they wish to perform. Non-verbal communication ...

Internet blackouts are challenging environments for anonymity and censorship resistance. Existing popular anonymity networks (e.g., Freenet, I2P, Tor) rely on Internet connectivity to function, making them impracticable during such blackouts. In such a set ...

Improving the energy efficiency of data centers while guaranteeing Quality of Service (QoS), together with detecting performance variability of servers caused by either hardware or software failures, are two of the major challenges for efficient resource m ...

Machine learning (ML) solutions are nowadays distributed, according to the so-called server/worker architecture. One server holds the model parameters while several workers train the model. Clearly, such architecture is prone to various types of component ...

Most communication systems (e.g., e-mails, instant messengers, VPNs) use encryption to prevent third parties from learning sensitive information. However, encrypted communications protect the contents but often leak metadata: the amount of data sent and th ...

In online data-intensive (OLDI) services, each client request typically executes on multiple servers in parallel; as a result, “system hiccups”, although rare within a single server, can interfere with many client requests and cause violations of service-l ...

We present GARFIELD, a library to transparently make machine learning (ML) applications, initially built with popular (but fragile) frameworks, e.g., TensorFlow and PyTorch, Byzantine–resilient. GARFIELD relies on a novel object–oriented design, reducing t ...

Virtually every connection to an Internet service is preceded by a DNS lookup. Lookups are performed without any traffic-level protection, thus enabling manipulation, redirection, surveillance, and censorship. To address these issues, large organizations s ...

Coding techniques have been well studied and used for improving communication quality by combating noise and mitigating interference. Recently, it has been shown that the same coding techniques can also be exploited to further improve communication perform ...

Machine Learning (ML) solutions are nowadays distributed, according to the so-called server/worker architecture. One server holds the model parameters while several workers train the model. Clearly, such architecture is prone to various types of component ...

Can we improve Internet transparency without worsening user anonymity? For a long time, researchers have been proposing transparency systems, where traffic reports produced at strategic network points help assess network behavior and verify service-level a ...

In a modern data center (DC), a large majority of costs arise from energy consumption. The most popular technique used to mitigate this issue is virtualization and more precisely virtual machine (VM) consolidation. Although consolidation may increase serve ...

To meet today's data management needs, it is a widespread practice to use distributed data storage and processing systems. Since the publication of the MapReduce paradigm, a plethora of such systems arose, but although widespread, the capabilities of these ...

Exemplary embodiments of the present disclosure provide cryptographically-strong tracking protection with unnoticeable "single-hop" network latencies by leveraging a client-relay- server architecture, in which the clients, relays (trusted or untrusted), an ...

Causal consistency is an attractive consistency model for geo-replicated data stores. It is provably the strongest model that tolerates network partitions. It avoids the long latencies associated with strong consistency, and, especially when using read-onl ...

A simple task of storing a database or transferring it to a different point via a communication channel turns far more complex as the size of the database grows large. Limited bandwidth available for transmission plays a central role in this predicament. I ...

The booming popularity of online services is rapidly raising the demands for modern datacenters. In order to cope with data deluge, growing user bases, and tight quality of service constraints, service providers deploy massive datacenters with tens to hund ...

Dissent in Numbers: Making Strong Anonymity Scale

Chattez avec Graph Search

PRO-Face C: Privacy-Preserving Recognition of Obfuscated Face via Feature Compensation

Privatized graph federated learning

Non-verbal Communication between Humans and Robots: Imitation, Mutual Understanding and Inferring Object Properties

Moby: A Blackout-Resistant Anonymity Network for Mobile Devices

MAGNETIC: Multi-Agent Machine Learning-Based Approach for Energy Efficient Dynamic Consolidation in Data Centers

Genuinely distributed Byzantine machine learning

Analyzing and Protecting Communication Metadata

When to Hedge in Interactive Services

GARFIELD: System Support for Byzantine Machine Learning (Regular Paper)

Encrypted DNS double right arrow Privacy? A Traffic Analysis Perspective

Cooperative Data Exchange and Private Information Retrieval

Genuinely Distributed Byzantine Machine Learning

MorphIT: Morphing Packet Reports for Internet Transparency

Drowsy-DC: Data center power management system

Formal Approaches to Querying Big Data in Shared-Nothing Systems

Systems and method for anonymous, low-latencey, tracking-resistant communications in a networked environment

Causal Consistency and Latency Optimality: Friend or Foe? [Extended Version]

Causal Consistency and Latency Optimality: Friend or Foe?

Caching and Distributed Storage : Models, Limits and Designs

Network-Compute Co-Design for Distributed In-Memory Computing