The newest papers that have not yet reached the front page.
  1. Enabling Privacy-Preserving, Compute- and Data-Intensive Computing using Heterogeneous Trusted Execution Environment 2020 Oakland TEE
    Jianping Zhu, Rui Hou, XiaoFeng Wang, Wenhao Wang, Jiangfeng Cao, Lutan Zhao, Fengkai Yuan, Peinan Li, Zhongpu Wang, Boyan Zhao, Lixin Zhang, Dan Meng

    There is an urgent demand for privacy-preserving techniques capable of supporting compute and data intensive (CDI) computing in the era of big data. However, none of existing TEEs can truly support CDI computing tasks, as CDI requires high throughput accelerators like GPU and TPU but TEEs do not offer security protection of such accelerators. This paper present HETEE (Heterogeneous TEE), the first design of TEE capable of strongly protecting heterogeneous computing with unsecure accelerators. HETEE is uniquely constructed to work with today’s servers, and does not require any changes for existing commercial CPUs or accelerators. The key idea of our design runs security controller as a stand-alone computing system to dynamically adjust the boundary of between secure and insecure worlds through the PCIe switches, rendering the control of an accelerator to the host OS when it is not needed for secure computing, and shifting it back when it is. The controller is the only trust unit in the system and it runs the custom OS and accelerator runtimes, together with the encryption, authentication and remote attestation components. The host server and other computing systems communicate with controller through an in memory task queue that accommodates the computing tasks offloaded to HETEE, in the form of encrypted and signed code and data. Also, HETEE offers a generic and efficient programming model to the host CPU. We have implemented the HETEE design on a hardware prototype system, and evaluated it with large-scale Neural Networks inference and training tasks. Our evaluations show that HETEE can easily support such secure computing tasks and only incurs a 12.34% throughput overhead for inference and 9.87% overhead for training on average.

  2. Zexe: Enabling Decentralized Private Computation 2020 Blockchains Oakland Privacy
    Sean Bowe and Alessandro Chiesa and Matthew Green and Ian Miers and Pratyush Mishra and Howard Wu

    Ledger-based systems that support rich applications often suffer from two limitations. First, validating a transaction requires re-executing the state transition that it attests to. Second, transactions not only reveal which application had a state transition but also reveal the application’s internal state.

    We design, implement, and evaluate ZEXE, a ledger-based system where users can execute offline computations and subsequently produce transactions, attesting to the correctness of these computations, that satisfy two main properties. First, transactions hide all information about the offline computations. Second, transactions can be validated in constant time by anyone, regardless of the offline computation.

    The core of ZEXE is a construction for a new cryptographic primitive that we introduce, decentralized private computation (DPC) schemes. In order to achieve an efficient implementation of our construction, we leverage tools in the area of cryptographic proofs, including succinct zero knowledge proofs and recursive proof composition. Overall, transactions in ZEXE are 968 bytes regardless of the offline computation, and generating them takes less than a minute plus a time that grows with the offline computation.

    We demonstrate how to use ZEXE to realize privacy-preserving analogues of popular applications: private decentralized exchanges for user-defined fungible assets and regulation-friendly private stablecoins.

  3. Transparent Polynomial Delegation and Its Applications to Zero Knowledge Proof 2020 NIZK Oakland ZK
    Jiaheng Zhang and Tiancheng Xie and Yupeng Zhang and Dawn Song

    We present a new succinct zero knowledge argument scheme for layered arithmetic circuits without trusted setup. The prover time is O(C+nlogn) and the proof size is O(DlogC+log2n) for a D-depth circuit with n inputs and C gates. The verification time is also succinct, O(DlogC+log2n), if the circuit is structured. Our scheme only uses lightweight cryptographic primitives such as collision-resistant hash functions and is plausibly post-quantum secure. We implement a zero knowledge argument system, Virgo, based on our new scheme and compare its performance to existing schemes. Experiments show that it only takes 53 seconds to generate a proof for a circuit computing a Merkle tree with 256 leaves, at least an order of magnitude faster than all other succinct zero knowledge argument schemes. The verification time is 50ms, and the proof size is 253KB, both competitive to existing systems. Underlying Virgo is a new transparent zero knowledge verifiable polynomial delegation scheme with logarithmic proof size and verification time. The scheme is in the interactive oracle proof model and may be of independent interest.

  4. Towards Scalable Threshold Cryptosystems 2020 Blockchains Oakland
    Alin Tomescu, Robert Chen, Yiming Zheng, Ittai Abraham, Benny Pinkas, Guy Golan Gueta, and Srinivas Devadas

    The resurging interest in Byzantine fault tolerant systems will demand more scalable threshold cryptosystems. Unfortunately, current systems scale poorly, requiring time quadratic in the number of participants. In this paper, we present techniques that help scale threshold signature schemes (TSS), verifiable secret sharing (VSS) and distributed key generation (DKG) protocols to hundreds of thousands of participants and beyond. First, we use efficient algorithms for evaluating polynomials at multiple points to speed up computing Lagrange coefficients when aggregating threshold signatures. As a result, we can aggregate a 130,000 out of 260,000 BLS threshold signature in just 6 seconds (down from 30 minutes). Second, we show how “authenticating” such multipoint evaluations can speed up proving polynomial evaluations, a key step in communication-efficient VSS and DKG protocols. As a result, we reduce the asymptotic (and concrete) computational complexity of VSS and DKG protocols from quadratic time to quasilinear time, at a small increase in communication complexity. For example, using our DKG protocol, we can securely generate a key for the BLS scheme above in 2.3 hours (down from 8 days). Our techniques improve performance for thresholds as small as 255 and generalize to any Lagrange-based threshold scheme, not just threshold signatures. Our work has certain limitations: we require a trusted setup, we focus on synchronous VSS and DKG protocols and we do not address the worst-case complaint overhead in DKGs. Nonetheless, we hope it will spark new interest in designing large-scale distributed systems.

  5. The State of the Uniform: Attacks on Encrypted Databases Beyond the Uniform Query Distribution 2020 Attacks EncryptedDatabases Oakland
    Evgenios M. Kornaropoulos and Charalampos Papamanthou and Roberto Tamassia

    Recent foundational work on leakage-based attacks on encrypted databases has broadened our understanding of what an adversary can accomplish with a standard leakage profile. Nevertheless, all known value reconstruction attacks succeed under strong assumptions that may not hold in the real world. The most prevalent assumption is that queries should be issued uniformly at random by the client. We present the first value reconstruction attacks for encrypted databases without any assumptions about the query or data distribution. Our approach uses the search pattern leakage, which exists in all known structured encryption schemes but has not been effectively utilized so far. At the core of our method lies a support size estimator, a technique that utilizes the repetition of search tokens with the same response to estimate distances between encrypted values without any assumptions about the underlying distribution. We develop distribution-agnostic reconstruction attacks for both range queries and k-nearest-neighbor (k-NN) queries based on information extracted from the search pattern leakage. Our new range attack follows a different algorithmic approach than state-of-the-art attacks, which are fine-tuned to succeed under the uniform queries. Instead, we reconstruct plaintext values under a variety of skewed query distributions and even outperform the accuracy of previous approaches under uniform query distribution. Our new k-NN attack succeeds with far fewer samples than a previously proposed attack and scales to much larger values of k. We demonstrate the effectiveness of our attacks by experimentally testing them on a wide range of query distributions and database densities, both unknown to the adversary.

  6. The Last Mile: High-Assurance and High-Speed Cryptographic Implementations 2020 FormalVerification Oakland TLS
    José Bacelar Almeida, Manuel Barbosa, Gilles Barthe, Benjamin Grégoire, Adrien Koutsos, Vincent Laporte, Tiago Oliveira, Pierre-Yves Strub

    We develop a new approach for building cryptographic implementations. Our approach goes the last mile and delivers assembly code that is provably functionally correct, protected against side-channels, and as efficient as hand-written assembly. We illustrate ur approach using ChaCha20-Poly1305, one of the mandatory ciphersuites in TLS 1.3, and deliver formally verified vectorized implementations which outperform the fastest non-verified code.
    We realize our approach by combining the Jasmin framework, which offers in a single language features of high-level and low-level programming, and the EasyCrypt proof assistant, which offers a versatile verification infrastructure that supports proofs of functional correctness and equivalence checking. Neither of these tools had been used for functional correctness before. Taken together, these infrastructures empower programmers to develop efficient and verified implementations by “game hopping”, starting from reference implementations that are proved functionally correct against a specification, and gradually introducing program optimizations that are proved correct by equivalence checking.
    We also make several contributions of independent interest, including a new and extensible verified compiler for Jasmin, with a richer memory model and support for vectorized instructions, and a new embedding of Jasmin in EasyCrypt.

  7. SoK: Understanding the Prevailing Security Vulnerabilities in TrustZone-assisted TEE Systems 2020 Attacks IntelSGX Oakland TEE
    David Cerdeira, Centro Algoritmi, Pedro Fonseca, and Sandro Pinto

    Hundreds of millions of mobile devices worldwide rely on Trusted Execution Environments (TEEs) built with Arm TrustZone for the protection of security-critical applications (e.g., DRM) and operating system (OS) components (e.g., Android keystore). TEEs are often assumed to be highly secure; however, over the past years, TEEs have been successfully attacked multiple times, with highly damaging impact across various platforms. Unfortunately, these attacks have been possible by the presence of security flaws in TEE systems. In this paper, we aim to understand which types of vulnerabilities and limitations affect existing TrustZone-assisted TEE systems, what are the main challenges to build them correctly, and what contributions can be borrowed from the research community to overcome them. To this end, we present a security analysis of popular TrustZone-assisted TEE systems (targeting Cortex-A processors) developed by Qualcomm, Trustonic, Huawei, Nvidia, and Linaro. By studying publicly documented exploits and vulnerabilities as well as by reverse engineering the TEE firmware, we identified several critical vulnerabilities across existing systems which makes it legitimate to raise reasonable concerns about the security of commercial TEE implementations

  8. Pseudorandom Black Swans: Cache Attacks on CTR_DRBG 2020 Attacks Oakland RandomnessGeneration SideChannels
    Shaanan Cohney and Andrew Kwong and Shachar Paz and Daniel Genkin and Nadia Heninger and Eyal Ronen and Yuval Yarom

    Modern cryptography requires the ability to securely generate pseudorandom numbers. However, despite decades of work on side channel attacks, there is little discussion of their application to pseudorandom number generators (PRGs). In this work we set out to address this gap, empirically evaluating the side channel resistance of common PRG implementations. We find that hard-learned lessons about side channel leakage from encryption primitives have not been applied to PRGs, at all levels of abstraction. At the design level, the NIST-recommended CTR_DRBG design does not have forward security if an attacker is able to compromise the state via a side-channel attack. At the primitive level, popular implementations of CTR_DRBG such as OpenSSL’s FIPS module and NetBSD’s kernel use leaky T-table AES as their underlying block cipher, enabling cache side-channel attacks. Finally, we find that many implementations make parameter choices that enable an attacker to fully exploit the side-channel attack in a realistic scenario and recover secret keys from TLS connections. We empirically demonstrate our attack in two scenarios. In the first, we carry out an asynchronous cache attack that recovers the private state from vulnerable CTR_DRBG implementations under realistic conditions to recover long-term authentication keys when the attacker is a party in the TLS connection. In the second scenario, we show that an attacker can exploit the high temporal resolution provided by Intel SGX to carry out a blind attack to recover CTR_DRBG’s state within three AES encryptions, without viewing output, and thus to decrypt passively collected TLS connections from the victim.

  9. Path Oblivious Heap: Optimal and Practical Oblivious Priority Queue 2020 Oakland ORAM
    Elaine Shi

    We propose Path Oblivious Heap, an extremely simple, practical, and optimal oblivious priority queue. Our construction also implies a practical and optimal oblivious sorting algorithm which we call Path Oblivious Sort. Not only are our algorithms asymptotically optimal, we show that their practical performance is only a small constant factor worse than insecure baselines. More specificially, assuming roughly logarithmic client private storage, Path Oblivious Heap consumes 2× to 7× more bandwidth than the ordinary insecure binary heap; and Path Oblivious Sort consumes 4.5× to 6× more bandwidth than the insecure Merge Sort. We show that these performance results improve existing works by 1-2 orders of magnitude. Finally, we evaluate our algorithm for a multi-party computation scenario and show 7× to 8× reduction in the number of symmetric encryptions relative to the state of the art.

  10. OHIE: Blockchain Scaling Made Simple 2020 CryptocurrencyScaling Oakland
    Haifeng Yu, Ivica Nikolic, Ruomu Hou, Prateek Saxena

    Many blockchain consensus protocols have been proposed recently to scale the throughput of a blockchain with available bandwidth. However, these protocols are becoming increasingly complex, making it more and more difficult to produce proofs of their security guarantees. We propose a novel permissionless blockchain protocol OHIE which explicitly aims for simplicity. OHIE composes as many parallel instances of Bitcoin’s original (and simple) backbone protocol as needed to achieve excellent throughput. We formally prove the safety and liveness properties of OHIE. We demonstrate its performance with a prototype implementation and large-scale experiments with up to 50,000 nodes. In our experiments, OHIE achieves linear scaling with available bandwidth, providing about 4-10 Mbps transaction throughput (under 8-20 Mbps per-node available bandwidth configurations) and at least about 20x better decentralization over prior works.

  11. HydRand: Practical Continuous Distributed Randomness 2020 Blockchains Oakland RandomnessGeneration
    Philipp Schindler and Aljosha Judmayer and Nicholas Stifter and Edgar Weippl

    A reliable source of randomness is not only an essential building block in various cryptographic, security, and distributed systems protocols, but also plays an integral part in the design of many new blockchain proposals. Consequently, the topic of publicly-verifiable, bias-resistant and unpredictable randomness has recently enjoyed increased attention. In particular random beacon protocols, aimed at continuous operation, can be a vital component for current Proof-of-Stake based distributed ledger proposals. We improve upon previous random beacon approaches with HydRand, a novel distributed protocol based on publicly-verifiable secret sharing (PVSS) to ensure unpredictability, bias-resistance, and public-verifiability of a continuous sequence of random beacon values. Furthermore, HydRand provides guaranteed output delivery of randomness at regular and predictable intervals in the presence of adversarial behavior and does not rely on a trusted dealer for the initial setup. Compared to existing PVSS based approaches that strive to achieve similar properties, our solution improves scalability by lowering the communication complexity from O(n3) to O(n2). Furthermore, we are the first to present a detailed comparison of recently described schemes and protocols that can be used for implementing random beacons.

  12. Flyclient: Super-Light Clients for Cryptocurrencies 2020 Blockchains CryptocurrencyScaling Oakland
    Benedikt Bünz and Lucianna Kiffer and Loi Luu and Mahdi Zamani

    To validate transactions, cryptocurrencies such as Bitcoin and Ethereum require nodes to verify that a blockchain is valid. This entails downloading and verifying all blocks, taking hours and requiring gigabytes of bandwidth and storage. Hence, clients with limited resources cannot verify transactions independently without trusting full nodes. Bitcoin and Ethereum offer light clients known as simplified payment verification (SPV) clients, that can verify the chain by downloading only the block headers. Unfortunately, the storage and bandwidth requirements of SPV clients still increase linearly with the chain length. For example, as of July 2019, an SPV client in Ethereum needs to download and store about 4 GB of data. Recently, Kiayias et al. proposed a solution known as non-interactive proofs of proof-of-work (NIPoPoW) that allows a light client to download and store only a polylogarithmic number of block headers in expectation. Unfortunately, NIPoPoWs are succinct only as long as no adversary influences the honest chain, and can only be used in chains with fixed block difficulty, contrary to most cryptocurrencies which adjust block difficulty frequently according to the network hashrate.

    We introduce Flyclient, a novel transaction verification light client for chains of variable difficulty. Flyclient is efficient both asymptotically and practically and requires downloading only a logarithmic number of block headers while storing only a single block header between executions. Using an optimal probabilistic block sampling protocol and Merkle Mountain Range (MMR) commitments, Flyclient overcomes the limitations of NIPoPoWs and generates shorter proofs over all measured parameters. In Ethereum, Flyclient achieves a synchronization proof size of less than 500 KB which is roughly 6,600x smaller than SPV proofs. We finally discuss how Flyclient can be deployed with minimal changes to the existing cryptocurrencies via an uncontentious velvet fork.

  13. EverCrypt: A Fast, Verified, Cross-Platform Cryptographic Provider 2020 FormalVerification Oakland TEE
    Jonathan Protzenko, Bryan Parno, Aymeric Fromherz, Chris Hawblitzel, Marina Polubelova, Karthikeyan Bhargavan, Benjamin Beurdouche, Joonwon Choi, Antoine Delignat-Lavaud, Cédric Fournet, Natalia Kulatova, Tahina Ramananandro, Aseem Rastogi, and more

    We present EverCrypt: a comprehensive collection of verified, high-performance cryptographic functionalities available via a carefully designed API. The API provably supports agility (choosing between multiple algorithms for the same functionality) and multiplexing (choosing between multiple implementations of the same algorithm). Through abstraction and zero-cost generic programming, we show how agility can simplify verification without sacrificing performance, and we demonstrate how C and assembly can be composed and verified against shared specifications. We substantiate the effectiveness of these techniques with new verified implementations (including hashes, Curve25519, and AES-GCM) whose performance matches or exceeds the best unverified implementations. We validate the API design with two high-performance verified case studies built atop EverCrypt, resulting in line-rate performance for a secure network protocol and a Merkle-tree library, used in a production blockchain, that supports 2.7 million insertions/sec. Altogether, EverCrypt consists of over 124K verified lines of specs, code, and proofs, and it produces over 29K lines of C and 14K lines of assembly code.

  14. Efficient and Secure Multiparty Computation from Fixed-Key Block Ciphers 2020 MPC Oakland
    Chun Guo and Jonathan Katz and Xiao Wang and Yu Yu

    Many implementations of secure computation use fixed-key AES (modeled as a random permutation); this results in substantial performance benefits due to existing hardware support for~AES and the ability to avoid recomputing the AES key schedule. Surveying these implementations, however, we find that most utilize AES in a heuristic fashion; in the best case this leaves a gap in the security proof, but in many cases we show it allows for explicit attacks.

    Motivated by this unsatisfactory state of affairs, we initiate a comprehensive study of how to use fixed-key block ciphers for secure computation—in particular for OT extension and circuit garbling—efficiently and securely. Specifically:

    • We consider several notions of pseudorandomness for hash functions (e.g., correlation robustness), and show provably secure schemes for OT extension, garbling, and other applications based on hash functions satisfying these notions.

    • We provide provably secure constructions, in the random-permutation model, of hash functions satisfying the different notions of pseudorandomness we consider.

    Taken together, our results provide end-to-end security proofs for implementations of secure-computation protocols based on fixed-key block ciphers (modeled as random permutations). Perhaps surprisingly, at the same time our work also results in noticeable performance improvements over the state-of-the-art.

  15. CrypTFlow: Secure TensorFlow Inference 2020 MachineLearning MPC Oakland TEE
    Nishant Kumar, Mayank Rathee, Nishanth Chandran, Divya Gupta, Aseem Rastogi, Rahul Sharma

    We present CrypTFlow, a first of its kind system that converts TensorFlow inference code into Secure Multi-party Computation (MPC) protocols at the push of a button. To do this, we build three components. Our first component, Athos, is an end-to-end compiler from TensorFlow to a variety of semi-honest MPC protocols. The second component, Porthos, is an improved semi-honest 3-party protocol that provides significant speedups for TensorFlow like applications. Finally, to provide malicious secure MPC protocols, our third component, Aramis, is a novel technique that uses hardware with integrity guarantees to convert any semi-honest MPC protocol into an MPC protocol that provides malicious security. The malicious security of the protocols output by Aramis relies on integrity of the hardware and semi-honest security of MPC. Moreover, our system matches the inference accuracy of plaintext TensorFlow.
    We experimentally demonstrate the power of our system by showing the secure inference of real-world neural networks such as ResNet50 and DenseNet121 over the ImageNet dataset with running times of about 30 seconds for semi-honest security and under two minutes for malicious security. Prior work in the area of secure inference has been limited to semi-honest security of small networks over tiny datasets such as MNIST or CIFAR. Even on MNIST/CIFAR, CrypTFlow outperforms prior work.

  16. Trident: Efficient 4PC Framework for Privacy Preserving Machine Learning 2020 MachineLearning MPC NDSS
    Rahul Rachuri and Ajith Suresh

    Machine learning has started to be deployed in fields such as healthcare and finance, which involves dealing with a lot of sensitive data. This propelled the need for and growth of privacy-preserving machine learning (PPML). We propose an actively secure four-party protocol (4PC), and a framework for PPML, showcasing its applications on four of the most widely-known machine learning algorithms – Linear Regression, Logistic Regression, Neural Networks, and Convolutional Neural Networks.

    Our 4PC protocol tolerating at most one malicious corruption is practically efficient as compared to Gordon et al. (ASIACRYPT 2018) as the 4th party in our protocol is not active in the online phase, except input sharing and output reconstruction stages. Concretely, we reduce the online communication as compared to them by 1 ring element. We use the protocol to build an efficient mixed-world framework (Trident) to switch between the Arithmetic, Boolean, and Garbled worlds. Our framework operates in the offline-online paradigm over rings and is instantiated in an outsourced setting for machine learning, where the data is secretly shared among the servers. Also, we propose conversions especially relevant to privacy-preserving machine learning. With the privilege of having an extra honest party, we outperform the current state-of-the-art ABY3 (for three parties), in terms of both rounds as well as communication complexity.

    The highlights of our framework include using a minimal number of expensive circuits overall as compared to ABY3. This can be seen in our technique for truncation, which does not affect the online cost of multiplication and removes the need for any circuits in the offline phase. Our B2A conversion has an improvement of 7× in rounds and 18× in the communication complexity. In addition to these, all of the special conversions for machine learning, e.g. Secure Comparison, achieve constant round complexity.

    The practicality of our framework is argued through improvements in the benchmarking of the aforementioned algorithms when compared with ABY3. All the protocols are implemented over a 64-bit ring in both LAN and WAN settings. Our improvements go up to 187× for the training phase and 158× for the prediction phase when observed over LAN and WAN.

  17. Practical Traffic Analysis Attacks on Secure Messaging Applications 2020 Attacks NDSS SecureMessaging
    Alireza Bahramali, Ramin Soltani, Amir Houmansadr, Dennis Goeckel, Don Towsley

    Instant Messaging (IM) applications like Telegram, Signal, and WhatsApp have become extremely popular in recent years. Unfortunately, such IM services have been targets of continuous governmental surveillance and censorship, as these services are home to public and private communication channels on socially and politically sensitive topics. To protect their clients, popular IM services deploy state-of-the-art encryption mechanisms. In this paper, we show that despite the use of advanced encryption, popular IM applications leak sensitive information about their clients to adversaries who merely monitor their encrypted IM traffic, with no need for leveraging any software vulnerabilities of IM applications. Specifically, we devise traffic analysis attacks that enable an adversary to identify administrators as well as members of target IM channels (e.g., forums) with high accuracies. We believe that our study demonstrates a significant, real-world threat to the users of such services given the increasing attempts by oppressive governments at cracking down controversial IM channels.
    We demonstrate the practicality of our traffic analysis attacks through extensive experiments on real-world IM communications. We show that standard countermeasure techniques such as adding cover traffic can degrade the effectiveness of the attacks we introduce in this paper. We hope that our study will encourage IM providers to integrate effective traffic obfuscation countermeasures into their software. In the meantime, we have designed and deployed an open-source, publicly available countermeasure system, called IMProxy, that can be used by IM clients with no need for any support from IM providers. We have demonstrated the effectiveness of IMProxy through experiments.

  18. MACAO: A Maliciously-Secure and Client-Efficient Active ORAM Framework 2020 NDSS ORAM
    Thang Hoang and Jorge Guajardo and Attila A. Yavuz

    Oblivious Random Access Machine (ORAM) allows a client to hide the access pattern and thus, offers a strong level of privacy for data outsourcing. An ideal ORAM scheme is expected to offer desirable properties such as low client bandwidth, low server computation overhead and the ability to compute over encrypted data. S3ORAM (CCS’17) is an efficient active ORAM scheme, which takes advantage of secret sharing to provide ideal properties for data outsourcing such as low client bandwidth, low server computation and low delay. Despite its merits, S3ORAM only offers security in the semi-honest setting. In practice, an ORAM protocol is likely to operate in the presence of malicious adversaries who might deviate from the protocol to compromise the client privacy.

    In this paper, we propose MACAO, a new multi-server ORAM framework, which offers integrity, access pattern obliviousness against active adversaries, and the ability to perform secure computation over the accessed data. MACAO harnesses authenticated secret sharing techniques and tree-ORAM paradigm to achieve low client communication, efficient server computation, and low storage overhead at the same time. We fully implemented MACAO and conducted extensive experiments in real cloud platforms (Amazon EC2) to validate the performance of MACAO compared with the state-of-the-art. Our results indicate that MACAO can achieve comparable performance to S3ORAM while offering security against malicious adversaries. MACAO is a suitable candidate for integration into distributed file systems with encrypted computation capabilities towards enabling an oblivious functional data outsourcing infrastructure.

  19. Dynamic Searchable Encryption with Small Client Storage 2020 NDSS SearchableEncryption
    Ioannis Demertzis and Javad Ghareh Chamani and Dimitrios Papadopoulos and Charalampos Papamanthou

    We study the problem of dynamic searchable encryption (DSE) with forward-and-backward privacy. Many DSE schemes have been proposed recently but the most efficient ones have one limitation: they require maintaining an operation counter for each unique keyword, either stored locally at the client or accessed obliviously (e.g., with an oblivious map) at the server, during every operation. We propose three new schemes that overcome the above limitation and achieve constant permanent client storage with improved performance, both asymptotically and experimentally, compared to prior state-of-the-art works. In particular, our first two schemes adopt a “static-to-dynamic” transformation which eliminates the need for oblivious accesses during searches. Due to this, they are the first practical schemes with minimal client storage and non-interactive search. Our third scheme is the first quasi-optimal forward-and-backward DSE scheme with only a logarithmic overhead for retrieving the query result (independently of previous deletions). While it does require an oblivious access during search in order to keep permanent client storage minimal, its practical performance is up to four orders of magnitude better than the best existing scheme with quasi-optimal search.

  20. BLAZE: Blazing Fast Privacy-Preserving Machine Learning 2020 MachineLearning MPC NDSS
    Arpita Patra and Ajith Suresh

    Machine learning tools have illustrated their potential in many significant sectors such as healthcare and finance, to aide in deriving useful inferences. The sensitive and confidential nature of the data, in such sectors, raise natural concerns for the privacy of data. This motivated the area of Privacy-preserving Machine Learning (PPML) where privacy of the data is guaranteed. Typically, ML techniques require large computing power, which leads clients with limited infrastructure to rely on the method of Secure Outsourced Computation (SOC). In SOC setting, the computation is outsourced to a set of specialized and powerful cloud servers and the service is availed on a pay-per-use basis. In this work, we explore PPML techniques in the SOC setting for widely used ML algorithms– Linear Regression, Logistic Regression, and Neural Networks.
    We propose BLAZE, a blazing fast PPML framework in the three server setting tolerating one malicious corruption over a ring (\Z{\ell}). BLAZE achieves the stronger security guarantee of fairness (all honest servers get the output whenever the corrupt server obtains the same). Leveraging an input-independent preprocessing phase, BLAZE has a fast input-dependent online phase relying on efficient PPML primitives such as: (i) A dot product protocol for which the communication in the online phase is independent of the vector size, the first of its kind in the three server setting; (ii) A method for truncation that shuns evaluating expensive circuit for Ripple Carry Adders (RCA) and achieves a constant round complexity. This improves over the truncation method of ABY3 (Mohassel et al., CCS 2018) that uses RCA and consumes a round complexity that is of the order of the depth of RCA.
    An extensive benchmarking of BLAZE for the aforementioned ML algorithms over a 64-bit ring in both WAN and LAN settings shows massive improvements over ABY3.

  21. Private Set Intersection in the Internet Setting From Lightweight Oblivious PRF 2020 Crypto PSI
    Melissa Chase and Peihan Miao

    We present a new protocol for two-party private set intersection (PSI) with semi-honest security in the plain model and one-sided malicious security in the random oracle model. Our protocol achieves a better balance between computation and communication than existing PSI protocols. Specifically, our protocol is the fastest in networks with moderate bandwidth (e.g., 30 - 100 Mbps). Considering the monetary cost (proposed by Pinkas et al. in CRYPTO 2019) to run the protocol on a cloud computing service, our protocol also compares favorably.

    Underlying our PSI protocol is a new lightweight multi-point oblivious pesudorandom function (OPRF) protocol based on oblivious transfer (OT) extension. We believe this new protocol may be of independent interest.

  22. Improved Primitives for MPC over Mixed Arithmetic-Binary Circuits 2020 Crypto MPC
    Daniel Escudero and Satrajit Ghosh and Marcel Keller and Rahul Rachuri and Peter Scholl

    This work introduces novel techniques to improve the translation between arithmetic and binary data types in secure multi-party computation. We introduce a new approach to performing these conversions using what we call extended doubly-authenticated bits (edaBits), which correspond to shared integers in the arithmetic domain whose bit decomposition is shared in the binary domain. These can be used to considerably increase the efficiency of non-linear operations such as truncation, secure comparison and bit-decomposition.

    Our edaBits are similar to the daBits technique introduced by Rotaru et al. (Indocrypt 2019). However, we show that edaBits can be directly produced much more efficiently than daBits, with active security, while enabling the same benefits in higher-level applications. Our method for generating edaBits involves a novel cut-and-choose technique that may be of independent interest, and improves efficiency by exploiting natural, tamper-resilient properties of binary circuits that occur in our construction. We also show how edaBits can be applied to efficiently implement various non-linear protocols of interest, and we thoroughly analyze their correctness for both signed and unsigned integers.

    The results of this work can be applied to any corruption threshold, although they seem best suited to dishonest majority protocols such as SPDZ. We implement and benchmark our constructions, and experimentally verify that our technique yield a substantial increase in efficiency. EdaBits save in communication by a factor that lies between 2 and 60 for secure comparisons with respect to a purely arithmetic approach, and between 2 and 25 with respect to using daBits. Improvements in throughput per second are slightly lower but still as high as a factor of 47. We also apply our novel machinery to the tasks of biometric matching and convolutional neural networks, obtaining a noticeable improvement as well.

  23. Better Concrete Security for Half-Gates Garbling (in the Multi-Instance Setting) 2020 2PC Attacks Crypto GarbledCircuits
    Chun Guo and Jonathan Katz and Xiao Wang and Chenkai Weng and Yu Yu

    We study the concrete security of high-performance implementations of half-gates garbling, which all rely on (hardware-accelerated)~AES. We find that current instantiations using k-bit wire labels can be completely broken—in the sense that the circuit evaluator learns all the inputs of the circuit garbler—in time O(2k/C), where C is the total number of (non-free) gates that are garbled, possibly across multiple independent executions. The attack can be applied to existing circuit-garbling libraries using k=80 when C≈109, and would require 267 machine-months and cost about USD 3500 to implement on the Google Cloud Platform. Since the attack can be entirely parallelized, the attack could be carried out in about a month using \approx 250 machines.

    With this as our motivation, we seek a way to instantiate the hash function in the half-gates scheme so as to achieve better concrete security. We present a construction based on AES that achieves optimal security in the single-instance setting (when only a single circuit is garbled). We also show how to modify the half-gates scheme so that its concrete security does not degrade in the multi-instance setting. Our modified scheme is as efficient as prior work in networks with up to 2 Gbps bandwidth.

  24. Stacked Garbling: Garbled Circuit Proportional to Longest Execution Path 2020 2PC Crypto GarbledCircuits
    David Heath and Vladimir Kolesnikov

    Secure two party computation (2PC) of arbitrary programs can be efficiently achieved using garbled circuits (GC). The bottleneck of GC efficiency is communication. It is widely believed that it is necessary to transmit the entire GC during 2PC, even for conditional branches that are not taken.

    This folklore belief is false.

    We propose a novel GC technique, stacked garbling, that eliminates the communication cost of inactive conditional branches. We extend the ideas of conditional GC evaluation explored in (Kolesnikov, Asiacrypt 18) and (Heath and Kolesnikov, Eurocrypt 20). Unlike these works, ours is for general 2PC where no player knows which conditional branch is taken.

    Our garbling scheme, Stack, requires communication proportional to the longest execution path rather than to the entire circuit. Stack is compatible with state-of-the-art techniques, such as free XOR and half-gates.

    Stack is a garbling scheme. As such, it can be plugged into a variety of existing protocols, and the resulting round complexity is the same as that of standard GC. The approach does incur computation cost quadratic in the conditional branching factor vs linear in standard schemes, but the tradeoff is beneficial for most programs: GC computation even on weak hardware is faster than GC transmission on fast channels.

    We implemented Stack in C++. Stack reduces communication cost by approximately the branching factor: for 16 branches, communication is reduced by 10.5x. In terms of wall-clock time for circuits with branching factor 16 over a 50 Mbps WAN on a laptop, Stack outperforms state-of- the-art half-gates-based 2PC by more than 4x.

  25. Comparing the difficulty of factorization and discrete logarithm: a 240-digit experiment 2020 Attacks Crypto PublicKeyEncryption
    F. Boudot and P. Gaudry and A. Guillevic and N. Heninger and E. Thomé and P. Zimmermann

    We report on two new records: the factorization of RSA-240, a 795-bit number, and a discrete logarithm computation over a 795-bit prime field. Previous records were the factorization of RSA-768 in 2009 and a 768-bit discrete logarithm computation in 2016. Our two computations at the 795-bit level were done using the same hardware and software, and show that computing a discrete logarithm is not much harder than a factorization of the same size. Moreover, thanks to algorithmic variants and well-chosen parameters, our computations were significantly less expensive than anticipated based on previous records.

    The last page of this paper also reports on the factorization of RSA-250.