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Megha Byali

dblp:216/6352 · DBLP profile ↗
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3ranked-venue papers
3as first author
0since 2021 · last 2020
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Security and privacy · 3 · 3 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Network and information security
2 papers
Cryptographic protocols and secure computation · 74% Cryptographic primitives and cryptanalysis · 26%

Topics — the 6 heaviest of 6, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Cryptographic protocols and secure computation
secure multiparty computation
0.722019
Fast Actively Secure Five-Party Computation with Security Beyond Abort · CCS 2019
Fast Secure Computation for Small Population over the Internet · CCS 2018
Cryptographic primitives and cryptanalysis › provable security
security notions
0.722019
Fast Actively Secure Five-Party Computation with Security Beyond Abort · CCS 2019
Fast Secure Computation for Small Population over the Internet · CCS 2018
Cryptographic protocols and secure computation › secure multiparty computation
active security
0.412019
Fast Actively Secure Five-Party Computation with Security Beyond Abort · CCS 2019
Cryptographic protocols and secure computation › secure multiparty computation
guaranteed output delivery
0.412019
Fast Actively Secure Five-Party Computation with Security Beyond Abort · CCS 2019
Cryptographic protocols and secure computation › secure multiparty computation › round complexity
constant-round MPC
0.312018
Fast Secure Computation for Small Population over the Internet · CCS 2018
Cryptographic protocols and secure computation › secure multiparty computation
honest-majority MPC
0.222019
Fast Actively Secure Five-Party Computation with Security Beyond Abort · CCS 2019
Fast Secure Computation for Small Population over the Internet · CCS 2018

Methods — techniques the papers use, named apart from their topics

garbled circuits · 0.7broadcast channel · 0.7
YearPublicationVenuePosition
2020 FLASH: Fast and Robust Framework for Privacy-preserving Machine Learning
abstract
Abstract Privacy-preserving machine learning (PPML) via Secure Multi-party Computation (MPC) has gained momentum in the recent past. Assuming a minimal network of pair-wise private channels, we propose an efficient four-party PPML framework over rings ℤ2ℓ, FLASH, the first of its kind in the regime of PPML framework, that achieves the strongest security notion of Guaranteed Output Delivery (all parties obtain the output irrespective of adversary’s behaviour). The state of the art ML frameworks such as ABY3 by Mohassel et.al (ACM CCS’18) and SecureNN by Wagh et.al (PETS’19) operate in the setting of 3 parties with one malicious corruption but achieve the weaker security guarantee of abort. We demonstrate PPML with real-time efficiency, using the following custom-made tools that overcome the limitations of the aforementioned state-of-the-art– (a) dot product, which is independent of the vector size unlike the state-of-the-art ABY3, SecureNN and ASTRA by Chaudhari et.al (ACM CCSW’19), all of which have linear dependence on the vector size. (b) Truncation and MSB Extraction, which are constant round and free of circuits like Parallel Prefix Adder (PPA) and Ripple Carry Adder (RCA), unlike ABY3 which uses these circuits and has round complexity of the order of depth of these circuits. We then exhibit the application of our FLASH framework in the secure server-aided prediction of vital algorithms– Linear Regression, Logistic Regression, Deep Neural Networks, and Binarized Neural Networks. We substantiate our theoretical claims through improvement in benchmarks of the aforementioned algorithms when compared with the current best framework ABY3. All the protocols are implemented over a 64-bit ring in LAN and WAN. Our experiments demonstrate that, for MNIST dataset, the improvement (in terms of throughput) ranges from 24 × to 1390 × over LAN and WAN together.
Megha Byali, Harsh Chaudhari, Arpita Patra, Ajith Suresh
Proc. Priv. Enhancing Technol.1
2019 Fast Actively Secure Five-Party Computation with Security Beyond Abort
abstract
Secure Multi-party Computation (MPC) with small population and honest majority has drawn focus specifically due to customization in techniques and resulting efficiency that the constructions can offer. In this work, we investigate a wide range of security notions in the five-party setting, tolerating two active corruptions. Being constant-round, our protocols are best suited for real-time, high latency networks such as the Internet. In a minimal setting of pairwise-private channels, we present efficient instantiations with unanimous abort (where either all honest parties obtain the output or none of them do) and fairness (where the adversary obtains its output only if all honest parties also receive it). With the presence of an additional broadcast channel (known to be necessary), we present a construction with guaranteed output delivery (where any adversarial behaviour cannot prevent the honest parties from receiving the output). The broadcast communication is minimal and independent of circuit size. In terms of performance (communication and run time), our protocols incur minimal overhead over the best known protocol of Chandran et al. (ACM CCS 2016) that achieves the least security of selective abort. Further, our protocols for fairness and unanimous abort can be extended to n-parties with at most √n corruptions, similar to Chandran et al. Going beyond the most popular honest-majority setting of three parties with one corruption, our results demonstrate feasibility of attaining stronger security notions for more than one active corruption at an expense not too far from the least desired security of selective abort.
Megha Byali, Carmit Hazay, Arpita Patra, Swati Singla
CCS1
2018 Fast Secure Computation for Small Population over the Internet
abstract
Secure Multi-Party Computation (MPC) with small number of parties is an interesting area of research, primarily due to its ability to model most real-life MPC applications and the simplicity and efficiency of the resulting protocols. In this work, we present efficient, constant-round 3-party (3PC) and 4-party (4PC) protocols in the honest-majority setting that achieve strong security notions of fairness (corrupted parties receive their output only if all honest parties receive output) and guaranteed output delivery (corrupted parties cannot prevent honest parties from receiving their output). Being constant-round, our constructions are suitable for Internet-like high-latency networks and are built from garbled circuits (GC). Assuming the minimal model of pairwise-private channels, we present two protocols that involve computation and communication of a single GC-- (a) a 4-round 3PC with fairness, (b) a 5-round 4PC with guaranteed output delivery. Empirically, our protocols are on par with the best known 3PC protocol of Mohassel et al. [CCS 2015] that only achieves security with selective abort, in terms of the computation time, LAN runtime, WAN runtime and communication cost. In fact, our 4PC outperforms the 3PC of Mohassel et al. significantly in terms of per-party computation and communication cost. With an extra GC, we improve the round complexity of our 4PC to four rounds. The only 4PC in our setting, given by Ishai et al. [CRYPTO 2015], involves 12 GCs. Assuming an additional broadcast channel, we present a 5-round 3PC with guaranteed output delivery that involves computation and communication of a single GC. A broadcast channel is inevitable in this setting for achieving guaranteed output delivery, owing to an impossibility result in the literature. The overall broadcast communication of our protocol is nominal and most importantly, is independent of the circuit size. This protocol too induces a nominal overhead compared to the protocol of Mohassel et al.
Megha Byali, Arpita Patra, Divya Ravi 0001
CCS1