Alishah Chator

dblp:206/7162 · DBLP profile ↗
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4ranked-venue papers
1as first author
2since 2021 · last 2026
—ORCID · none

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Security and privacy · 3 · 2 since 2021Artificial intelligence and machine learning · 1 · 1 first-author
YearPublicationVenuePosition
2026 Making Sense of Private Advertising: A Principled Approach to a Complex Ecosystem
abstract
In this work, we model the end-to-end pipeline of the advertising ecosystem, allowing us to identify two main issues with the current trajectory of private advertising proposals. First, prior work has largely considered ad targeting and engagement metrics individually rather than in composition. This has resulted in privacy notions that, while reasonable for each protocol in isolation, fail to compose to a natural notion of privacy for the ecosystem as a whole, permitting advertisers to extract new information about the audience of their advertisements. The second issue serves to explain the first: we prove that perfect privacy is impossible for any, even minimally, useful advertising ecosystem, due to the advertisers' expectation of conducting market research on the results. Having demonstrated that leakage is inherent in advertising, we re-examine what privacy could realistically mean in advertising, building on the well-established notion of sensitive data in a specific context. We identify that fundamentally new approaches are needed when designing privacy-preserving advertising subsystems in order to ensure that the privacy properties of the end-to-end advertising system are well aligned with people's privacy desires.
Kyle Hogan, Alishah Chator, Gabriel Kaptchuk, Mayank Varia, Srini Devadas
Proc. Priv. Enhancing Technol.2
2024 SocIoTy: Practical Cryptography in Smart Home Contexts
abstract
Smartphones form an important source of trust in modern computing. But, while their mobility is convenient, smartphones can be stolen or seized, allowing an adversary to impersonate the user in their digital life: accessing the user's services and decrypting their sensitive files. With this in mind, we build SocIoTy, which leverages a user's existing IoT devices to add a context-sensitive layer of security for non-expert users. Instead of assuming the existence of dedicated hardware, SocIoTy re-uses the devices of a user's smart home to provide cryptographic services, which we term at-home cryptography. We show that at-home cryptography can be built from simple cryptographic primitives, and that our SocIoTy solution is able to provide useful functionalities, like two-factor authentication (2FA) and secure file storage, while protecting against powerful adversaries in this setting. We implement and evaluate SocIoTy in real-world use cases and provide microbenchmarks for individual cryptographic operations on realistic models of IoT devices. We also provide full benchmarks of an end-to-end deployment on a simulated smart home, using a smartphone and 9 IoT devices to generate and display 2FA one-time passwords in less than 200 milliseconds. SocIoTy is able to provide strong, practical cryptography while binding its execution to the smart home itself, all without requiring additional hardware.
Tushar M. Jois, Gabrielle Beck, Sofia Belikovetsky, Joseph Carrigan, Alishah Chator, Logan Kostick, Maximilian Zinkus, Gabriel Kaptchuk, Aviel D. Rubin
Proc. Priv. Enhancing Technol.5
2020 BlockSci: Design and applications of a blockchain analysis platform
Harry A. Kalodner, Malte Möser, Steven Goldfeder, Martin Plattner, Alishah Chator, Arvind Narayanan
USENIX Security Symposium6
2018 Don't Talk to Strangers - On the Challenges of Intelligent Vehicle Authentication
Alishah Chator, Matthew Green 0001
VEHITS1