CFP: PPML Workshop at NIPS 2018

Privacy Preserving Machine Learning

NIPS 2018 Workshop

Montreal, December 8, 2018

Description

This one day workshop focuses on privacy preserving techniques for training, inference, and disclosure in large scale data analysis, both in the distributed and centralized settings. We have observed increasing interest of the ML community in leveraging cryptographic techniques such as Multi-Party Computation (MPC) and Homomorphic Encryption (HE) for privacy preserving training and inference, as well as Differential Privacy (DP) for disclosure. Simultaneously, the systems security and cryptography community has proposed various secure frameworks for ML. We encourage both theory and application-oriented submissions exploring a range of approaches, including:

  • secure multi-party computation techniques for ML
  • homomorphic encryption techniques for ML
  • hardware-based approaches to privacy preserving ML
  • centralized and decentralized protocols for learning on encrypted data
  • differential privacy: theory, applications, and implementations
  • statistical notions of privacy including relaxations of differential privacy
  • empirical and theoretical comparisons between different notions of privacy
  • trade-offs between privacy and utility

We think it will be very valuable to have a forum to unify different perspectives and start a discussion about the relative merits of each approach. The workshop will also serve as a venue for networking people from different communities interested in this problem, and hopefully foster fruitful long-term collaboration.

Submission Instructions

Submissions in the form of extended abstracts must be at most 4 pages long (not including references) and adhere to the NIPS format. We do accept submissions of work recently published or currently under review. Submissions should be anonymized. The workshop will not have formal proceedings, but authors of accepted abstracts can choose to have a link to arxiv or a pdf published on the workshop webpage.

Program Committee

  • Pauline Anthonysamy (Google)
  • Borja de Balle Pigem (Amazon)
  • Keith Bonawitz (Google)
  • Emiliano de Cristofaro (University College London)
  • David Evans (University of Virginia)
  • Irene Giacomelli (Wisconsin University)
  • Nadin Kokciyan (King’s College London)
  • Kim Laine (Microsoft Research)
  • Payman Mohassel (Visa Research)
  • Catuscia Palamidessi (Ecole Polytechnique & INRIA)
  • Mijung Park (Max Planck Institute for Intelligent Systems)
  • Benjamin Rubinstein (University of Melbourne)
  • Anand Sarwate (Rutgers University)
  • Philipp Schoppmann (HU Berlin)
  • Nigel Smart (KU Leuven)
  • Carmela Troncoso (EPFL)
  • Pinar Yolum (Utrecht University)
  • Samee Zahur (University of Virginia)

Organizers

  • Adria Gascon (Alan Turing Institute & Edinburgh)
  • Niki Kilbertus (MPI for Intelligent Systems & Cambridge)
  • Olya Ohrimenko (Microsoft Research)
  • Mariana Raykova (Yale)
  • Adrian Weller (Alan Turing Institute & Cambridge)
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IHP “Nexus” Workshop on Privacy and Security: Days 4-5

Wrapping this up, finally. Maybe conference blogging has to go by the wayside for me… my notes got a bit sketchier so I’ll just do a short rundown of the topics.

Days 4-5 were a series of “short” talks by Moni Naor, Kobbi Nissim, Lalitha Sankar, Sewoong Oh, Delaram Kahrobaie, Joerg Kliewer, Jon Ullman, and Sasho Nikolov on a rather eclectic mix of topics.

Moni’s talk was on secret sharing in an online setting — parties arrive one by one and the qualified sets (who can decode the secret) is revealed by all parties. The shares have to be generated online as well. Since the access structure is evolving, what kinds of systems can we support? As I understood it, the idea is to use something similar to threshold scheme and a “doubling trick”-like argument by dividing the users/parties into generations. It’s a bit out of area for me so I had a hard time keeping up with the connections to other problems. Kobbi talked about reconstruction attacks based on observing traffic from outsourced database systems. A user wants to get the records but the server shouldn’t be able to reconstruct: it knows how many records were returned from a query and knows if the same record was sent on subsequent queries — this is a sort of access pattern leakage. He presented attacks based on this information and also based on just knowing the volume (e.g. total size of response) from the queries.

Lalitha talked about mutual information privacy, which was quite a bit different than the differential privacy models from the CS side, but more in line with Ye Wang’s talk earlier in the week. Although she didn’t get to spend as much time on it, the work on interactive communication and privacy might have been interesting to folks earlier in the workshop studying communication complexity. In general, the connection between communication complexity problems and MPC, for example, are elusive to me (probably from lack of trying).

Sewoong talked about optimal mechanisms for differentially private composition — I had to miss his talk, unfortunately. Delaram talked about cryptosystems based on group theory and I had to try and check back in all the things I learned in 18.701/702 and the graduate algebra class I (mistakenly) took my first year of graduate school. I am not sure I could even do justice to it, but I took a lot of notes. Joerg talked about using polar codes to enable private function computation — initially privacy was measured by equivocation but towards the end he made a connection to differential privacy. Since most folks (myself included) are not experts on polar codes, he gave a rather nice tutorial (I thought) on polar coding. It being the last day of the workshop, the audience had unfortunately thinned out a bit.

Jon spoke about estimating marginal distributions for high-dimensional problems. There were some nice connections to composite hypothesis testing problems that came out of the discussion during the talk — the model seems a bit complex to get into based on my notes, but I think readers who are experts on hypothesis testing might want to check out his work. Sasho rounded off the workshop with a talk about the sensitivity polytope of linear queries on a statistical database and connections to Gaussian widths. The main result was on the sample complexity of answering the queries in time polynomial in the number of individuals, size of the universe, and size of the query set.

IHP “Nexus” Workshop on Privacy and Security: Day 1

The view from my office at IHP

The view from my office at IHP

I am attending the Nexus of Information and Computation Theories workshop at the Institut Henri Poincaré in Paris this week. It’s the last week of a 10 week program that brought together researchers from information theory and CS theory in workshops around various themes such as distributed computation, inference, lower bounds, inequalities, and security/privacy. The main organizers were Bobak Nazer, Aslan Tchamkerten, Anup Rao, and Mark Braverman. The last two weeks are on Privacy and Security: I helped organize these two weeks with Prakash Narayan, Salil Vadhan, Aaron Roth, and Vinod Vaikuntanathan.

Due to teaching and ICASSP, I missed last week, but am here for this week, for which the sub-topics are security multiparty computation and differential privacy. I’ll try to blog about the workshop since I failed to blog at all about ITA, CISS, or ICASSP. The structure of the workshop was to have 4 tutorials (two per week) and then a set of hopefully related talks. The first week had tutorials on pseudorandomness and information theoretic secrecy.

The second week of the workshop kicked off with a tutorial from Yuval Ishai and Manoj Prabhakaran on secure multiparty computation (MPC). Yuval gave an abbreviated version/update of his tutorial from the Simons Institute (pt1/pt2) that set up the basic framework and language around MPC: k parties with inputs x_1, x_2, \ldots, x_k want to exchange messages to implement a functionality (evaluate a function) f(x_1, x_2, \ldots, x_k) over secure point-to-point channels such they successfully learn the output of the function but don’t learn anything additional about each others’ inputs. There is a landscape of definitions within this general framework: some parties could collude, behave dishonestly with respect to the protocol, and so on. The guarantees could be exact (in the real/ideal paradigm in which you compare the real system with an simulated system), statistical (the distribution in the real system is close in total variation distance to an ideal evaluation), or computational (some notion of indistinguishability). The example became a bit clearer when he described a 2-party example with a “trusted dealer” who can give parties some correlated random bits and they could use those to randomly shift the truth table/evaluation of f(x_1, x_2) to guarantee correctness and security.

Manoj, on the other hand talked about some notions of reductions between secure computations: given a protocol which evaluates f, can you simulate/compute g using calls to f? How many do you need? this gives a notion of the complexity rate of one function in terms of another. For example, can Alice and Bob simulate a BEC using calls to an oblivious transfer (OT) protocol? What about vice versa? What about using a BSC? These problems seem sort of like toy channel problems (from an information theory perspective) but seem like fundamental building blocks when thinking about secure computation. As I discussed with Hoeteck Wee today, in information theory we often gain some intuition from continuous alphabets or large/general alphabet settings, whereas cryptography arguments/bounds come from considering circuit complexity: these are ideas that we don’t think about too much in IT since we don’t usually care about computational complexity/implementation.

Huijia (Rachel) Lin gave an introduction to zero-knowledge proofs and proof systems: a verifier wants to know if a statement X is true and can ask queries to a prover P which has some evidence w that it wants to keep secret. For example, the statement might be “the number y is a perfect square” and the evidence might be an \alpha such that y = \alpha^2 \mod n. The prover doesn’t want to reveal w = \alpha, but instead should convince the verifier that such an alpha exists. She gave a protocol for this before turning to a more complicated statement like proving that a graph has a Hamiltonian cycle. She then talked about using commitment schemes, at which point I sort of lost the thread of things since I’m not as familiar with these cryptography constructions. I probably should have asked more questions, so it was my loss.

Daniel Wichs discussed two problems he called “multi-key” and “spooky” fully-homomorphic encryption (FHE). The idea in multi-key FHE is that you have N users who encrypt values \{ x_i : i \in [N] \} with their public key and upload them to a server. Someone with access to the server wants to be able to decode only a function f(x_1, x_2, \ldots, x_N) using the combined private keys of all the users. In “spooky” FHE, you have N decoders, each with one of the private keys, but they want to decode values \{y_i : i \in [N]\} which are functions of all of the encoded data. A simple example of this is when y_1 \oplus y_2 = x_1 \wedge x_2: that is, the XOR of the outputs is equal to the AND of the inputs. This generalizes to the XOR of multiple outputs being some function of the inputs, something he called additive function sharing. He then presented schemes for these two problems based on the “learning with errors” from Gentry, Sahai, and Waters, which I would apparently have to read to really understand the scheme. It’s some sort of linear algebra thing over \mathbb{Z}_q. Perhaps there are some connections to linear block codes or network coding to be exploited here.

Mathematical Tools of Information-Theoretic Security Workshop: Day 1

It’s been a while since I have conference-blogged but I wanted to set aside a little time for it. Before going to Allerton I went to a lovely workshop in Paris on the Mathematical Tools of Information-Theoretic Security thanks to a very kind invitation from Vincent Tan and Matthieu Bloch. This was a 2.5 day workshop covering a rather wide variety of topics, which was good for me since I learned quite a bit. I gave a talk on differential privacy and machine learning with a little more of a push on the mathematical aspects that might be interesting from an information-theory perspective. Paris was appropriately lovely, and it was great to see familiar and new faces there. Now that I am at Rutgers I should note especially our three distinguished alumnae, Şennur Ulukuş, Aylin Yener, and Lalitha Sankar.

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Linkage

It’s been a busy week, deadline-wise, but I did see a few cool things on the interwebs which seemed worth sharing:

Tarantulas molting, courtesy of my high school biology teacher and ExploraVision coach extraordinare, Mr. Stone (his blog is cool too).

Keeping with the nature theme, find the cuttlefish!. The octopus video is cool too. Thanks to my commute being a bit longer, I listen to Science Friday podcasts as well as Story Collider, which is a pretty cool Moth-meets-science storytelling podcast.

Sometimes papers use pretty strong words in their titles (see for more context). On that note, some letters from John Nash (see also) were recently declassified by the NSA wherein he seems to predict fundamentals of cryptography and computational complexity. In more Rivest news, he coded up the cryptosystem.

In sadder news (also not so recent now), De Bruijn passed away. I’ve started a bioinformatics project recently (maybe more like “started”) and DeBruijn graphs are a pretty useful tool for making sense of data from next-generation sequencing technologies. Here are some animations describing how Illumina and 454 sequencing work.

Maybe when it gets warmer I will put together a worm bin — I miss the curbside composting of Berkeley.

I get a lot of positive comments about this shirt, but Topatoco are discontinuing it. Speaking of potatoes, Lav has a nice post with some links to papers on the importance and history of potatoes.