skip to main content

Attention:

The NSF Public Access Repository (PAR) system and access will be unavailable from 11:00 PM ET on Friday, December 13 until 2:00 AM ET on Saturday, December 14 due to maintenance. We apologize for the inconvenience.


Title: Aegean: replication beyond the client-server model
This paper presents Aegean, a new approach that allows fault-tolerant replication to be implemented beyond the confines of the client-server model. In today’s computing, where services are rarely standalone, traditional replication protocols such as Primary-Backup, Paxos, and PBFT are not directly applicable, as they were designed for the client-server model. When services interact, these protocols run into a number of problems, affecting both correctness and performance. In this paper, we rethink the design of replication protocols in the presence of interactions between services and introduce new techniques that accommodate such interactions safely and efficiently. Our evaluation shows that a prototype implementation of Aegean not only ensures correctness in the presence of service interactions, but can further improve throughput by an order of magnitude.  more » « less
Award ID(s):
1814507
PAR ID:
10123582
Author(s) / Creator(s):
;
Date Published:
Journal Name:
Proceedings of the 27th ACM Symposium on Operating Systems Principles
Page Range / eLocation ID:
385 to 398
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. This paper introduces protocols for authenticated private information retrieval. These schemes enable a client to fetch a record from a remote database server such that (a) the server does not learn which record the client reads, and (b) the client either obtains the "authentic" record or detects server misbehavior and safely aborts. Both properties are crucial for many applications. Standard private-information-retrieval schemes either do not ensure this form of output authenticity, or they require multiple database replicas with an honest majority. In contrast, we offer multi-server schemes that protect security as long as at least one server is honest. Moreover, if the client can obtain a short digest of the database out of band, then our schemes require only a single server. Performing an authenticated private PGP-public-key lookup on an OpenPGP key server's database of 3.5 million keys (3 GiB), using two non-colluding servers, takes under 1.2 core-seconds of computation, essentially matching the time taken by unauthenticated private information retrieval. Our authenticated single-server schemes are 30-100 more costly than state-of-the-art unauthenticated single-server schemes, though they achieve incomparably stronger integrity properties. 
    more » « less
  2. This paper introduces Flamingo, a system for secure aggregation of data across a large set of clients. In secure aggregation, a server sums up the private inputs of clients and obtains the result without learning anything about the individual inputs beyond what is implied by the final sum. Flamingo focuses on the multi-round setting found in federated learning in which many consecutive summations (averages) of model weights are performed to derive a good model. Previous protocols, such as Bell et al. (CCS ’20), have been designed for a single round and are adapted to the federated learning setting by repeating the protocol multiple times. Flamingo eliminates the need for the per-round setup of previous protocols, and has a new lightweight dropout resilience protocol to ensure that if clients leave in the middle of a sum the server can still obtain a meaningful result. Furthermore, Flamingo introduces a new way to locally choose the so-called client neighborhood introduced by Bell et al. These techniques help Flamingo reduce the number of interactions between clients and the server, resulting in a significant reduction in the end-to-end runtime for a full training session over prior work.We implement and evaluate Flamingo and show that it can securely train a neural network on the (Extended) MNIST and CIFAR-100 datasets, and the model converges without a loss in accuracy, compared to a non-private federated learning system. 
    more » « less
  3. Dunkelman, D. ; Dziembowski, S. (Ed.)
    We construct new private-information-retrieval protocols in the single-server setting. Our schemes allow a client to privately fetch a sequence of database records from a server, while the server answers each query in average time sublinear in the database size. Specifically, we introduce the first single-server private-information-retrieval schemes that have sublinear amortized server time, require sublinear additional storage, and allow the client to make her queries adaptively. Our protocols rely only on standard cryptographic assumptions (decision Diffie-Hellman, quadratic residuosity, learning with errors, etc.). They work by having the client first fetch a small “hint” about the database contents from the server. Generating this hint requires server time linear in the database size. Thereafter, the client can use the hint to make a bounded number of adaptive queries to the server, which the server answers in sublinear time—yielding sublinear amortized cost. Finally, we give lower bounds proving that our most efficient scheme is optimal with respect to the trade-off it achieves between server online time and client storage. 
    more » « less
  4. In an IoP environment, edge computing has been proposed to address the problems of resource limitations of edge devices such as smartphones as well as the high-latency, user privacy exposure and network bottleneck that the cloud computing platform solutions incur. This paper presents a context management framework comprised of sensors, mobile devices such as smartphones and an edge server to enable high performance, context-aware computing at the edge. Key features of this architecture include energy-efficient discovery of available sensors and edge services for the client, an automated mechanism for task planning and execution on the edge server, and a dynamic environment where new sensors and services may be added to the framework. A prototype of this architecture has been implemented, and an experimental evaluation using two computer vision tasks as example services is presented. Performance measurement shows that the execution of the example tasks performs quite well and the proposed framework is well suited for an edge-computing environment. 
    more » « less
  5. Private information retrieval (PIR) enables clients to query and retrieve data from untrusted servers without the untrusted servers learning which data was retrieved. In this paper, we present a new class of multi-server PIR protocols, which we call heterogeneous PIR (HPIR). In such multi-server PIR protocols, the computation and communication overheads imposed on the PIR servers are non-uniform, i.e., some servers handle higher computation/communication burdens than the others. This enables heterogeneous PIR protocols to be suitable for a range of new PIR applications. What enables us to enforce such heterogeneity is a unique PIR-tailored secret sharing algorithm that we leverage in building our PIR protocol. We have implemented our HPIR protocol and evaluated its performance in comparison with regular (i.e., homogenous) PIR protocols. Our evaluations demonstrate that a querying client can trade off the computation and communication loads of the (heterogeneous) PIR servers by adjusting some parameters. For example in a two-server scenario with a heterogeneity degree of 4/1, to retrieve a 456KB file from a 0.2GB database, the rich (i.e., resourceful) PIR server will do 1.1 seconds worth of computation compared to 0.3 seconds by the poor (resource-constrained) PIR server; this is while each of the servers would do the same 1 seconds of computation in a homogeneous setting. Also, for this given example, our HPIR protocol will impose a 912KB communication bandwidth on the rich server compared to 228KB on the poor server (by contrast to 456KB overheads on each of the servers for a traditional homogeneous design). 
    more » « less