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About

About

My name is Tânia Esteves, and I am a Ph.D. student at HASLab / INESC TEC. I completed my integrated master's degree in Informatics Engineering in 2018 at the University of Minho, and I have joined HASLab during the development of my master thesis named “Secure and Configurable Storage Systems.” Currently, I am attending the Doctoral Program in Informatics (PDINF) at the University of Minho, and my main research interests are focused on security and distributed systems.

Interest
Topics
Details

Details

  • Name

    Tânia Conceição Araújo
  • Role

    Research Assistant
  • Since

    01st April 2018
  • Nationality

    Portugal
  • Contacts

    +351253604440
    tania.c.araujo@inesctec.pt
001
Publications

2023

Diagnosing applications' I/O behavior through system call observability

Authors
Esteves, T; Macedo, R; Oliveira, R; Paulo, J;

Publication
2023 53RD ANNUAL IEEE/IFIP INTERNATIONAL CONFERENCE ON DEPENDABLE SYSTEMS AND NETWORKS WORKSHOPS, DSN-W

Abstract
We present DIO, a generic tool for observing inefficient and erroneous I/O interactions between applications and in-kernel storage systems that lead to performance, dependability, and correctness issues. DIO facilitates the analysis and enables near real-time visualization of complex I/O patterns for data-intensive applications generating millions of storage requests. This is achieved by non-intrusively intercepting system calls, enriching collected data with relevant context, and providing timely analysis and visualization for traced events. We demonstrate its usefulness by analyzing two production-level applications. Results show that DIO enables diagnosing resource contention in multi-threaded I/O that leads to high tail latency and erroneous file accesses that cause data loss.

2023

Toward a Practical and Timely Diagnosis of Application's I/O Behavior

Authors
Esteves, T; Macedo, R; Oliveira, R; Paulo, J;

Publication
IEEE ACCESS

Abstract
We present DIO, a generic tool for observing inefficient and erroneous I/O interactions between applications and in-kernel storage backends that lead to performance, dependability, and correctness issues. DIO eases the analysis and enables near real-time visualization of complex I/O patterns for data-intensive applications generating millions of storage requests. This is achieved by non-intrusively intercepting system calls, enriching collected data with relevant context, and providing timely analysis and visualization for traced events. We demonstrate its usefulness by analyzing four production-level applications. Results show that DIO enables diagnosing inefficient I/O patterns that lead to poor application performance, unexpected and redundant I/O calls caused by high-level libraries, resource contention in multithreaded I/O that leads to high tail latency, and erroneous file accesses that cause data loss. Moreover, through a detailed evaluation, we show that, when comparing DIO's inline diagnosis pipeline with a similar state-of-the-art solution, our system captures up to 28x more events while keeping tracing performance overhead between 14% and 51%.

2023

CRIBA: A Tool for Comprehensive Analysis of Cryptographic Ransomware's I/O Behavior

Authors
Esteves, T; Pereira, B; Oliveira, RP; Marco, J; Paulo, J;

Publication
2023 42nd International Symposium on Reliable Distributed Systems (SRDS)

Abstract

2021

S2Dedup: SGX-enabled secure deduplication

Authors
Miranda, M; Esteves, T; Portela, B; Paulo, J;

Publication
SYSTOR '21: The 14th ACM International Systems and Storage Conference, Haifa, Israel, June 14-16, 2021.

Abstract
Secure deduplication allows removing duplicate content at third-party storage services while preserving the privacy of users' data. However, current solutions are built with strict designs that cannot be adapted to storage service and applications with different security and performance requirements. We present S2Dedup, a trusted hardware-based privacy-preserving deduplication system designed to support multiple security schemes that enable different levels of performance, security guarantees and space savings. An in-depth evaluation shows these trade-offs for the distinct Intel SGX-based secure schemes supported by our prototype. Moreover, we propose a novel Epoch and Exact Frequency scheme that prevents frequency analysis leakage attacks present in current deterministic approaches for secure deduplication while maintaining similar performance and space savings to state-of-the-art approaches.

2021

CAT: content-aware tracing and analysis for distributed systems

Authors
Esteves, T; Neves, F; Oliveira, R; Paulo, J;

Publication
Middleware '21: 22nd International Middleware Conference, Québec City, Canada, December 6 - 10, 2021

Abstract