Synesthesia: Detecting Screen Content via Remote Acoustic Side Channels

We show that subtle acoustic noises emanating from within computer screens can be used to detect the content displayed on the screens. This sound can be picked up by ordinary microphones built into webcams or screens, and is inadvertently transmitted to other parties, e.g., during a videoconference call or archived recordings. It can also be recorded by a smartphone or "smart speaker" placed on a desk next to the screen, or from as far as 10 meters away using a parabolic microphone. Empirically demonstrating various attack scenarios, we show how this channel can be used for real-time detection of on-screen text, or users' input into on-screen virtual keyboards. We also demonstrate how an attacker can analyze the audio received during video call (e.g., on Google Hangout) to infer whether the other side is browsing the web in lieu of watching the video call, and which web site is displayed on their screen

Oblivious Message Retrieval

Anonymous message delivery systems, such as private messaging services and privacy-preserving payment systems, need a mechanism for recipients to retrieve the messages addressed to them, without leaking metadata or letting their messages be linked. Recipients could download all posted messages and scan for those addressed to them, but communication and computation costs are excessive at scale. We show how untrusted servers can detect messages on behalf of recipients, and summarize these into a compact encrypted digest that recipients can easily decrypt. These servers operate obliviously and do not learn anything about which messages are addressed to which recipients. Privacy, soundness, and completeness hold even if everyone but the recipient is adversarial and colluding (unlike in prior schemes). Our starting point is an asymptotically-efficient approach, using Fully Homomorphic Encryption and homomorphically-encoded Sparse Random Linear Codes. We then address the concrete performance using bespoke tailoring of lattice-based cryptographic components, alongside various algebraic and algorithmic optimizations. This reduces the digest size to a few bits per message scanned. Concretely, the servers\u27 cost is ~$1 per million messages scanned, and the resulting digests can be decoded by recipients in ~20ms. Our schemes can thus practically attain the strongest form of receiver privacy for current applications such as privacy-preserving cryptocurrencies

Group Oblivious Message Retrieval

Anonymous message delivery, as in private communication and privacy-preserving blockchain applications, ought to protect recipient metadata: a message should not be inadvertently linkable to its destination. But how can messages then be delivered to each recipient, without each recipient scanning all messages? Recent work constructed Oblivious Message Retrieval (OMR) protocols that outsource this job to untrusted servers in a privacy-preserving manner. We consider the case of group messaging, where each message may have multiple recipients (e.g., in a group chat or blockchain transaction). Direct use of prior OMR protocols in the group setting increases the servers\u27 work linearly in the group size, rendering it prohibitively costly for large groups. We thus devise new protocols where the servers\u27 cost grows very slowly with the group size, while recipients\u27 cost is low and independent of the group size. Our approach uses Fully Homomorphic Encryption and other lattice-based techniques, building on and improving on prior work. The efficient handling of groups is attained by encoding multiple recipient-specific clues into a single polynomial or multilinear function that can be efficiently evaluated under FHE, and via preprocessing and amortization techniques. We formally study several variants of Group Oblivious Message Retrieval (GOMR) and describe corresponding GOMR protocols. Our implementation and benchmarks show, for parameters of interest, cost reductions of orders of magnitude compared to prior schemes. For example, the servers\u27 cost is ~3.36 per million messages scanned, where each message may address up to 15 recipients

Secure Association for the Internet of Things

Existing standards (ZigBee and Bluetooth Low Energy) for networked low-power wireless devices do not support secure association (or pairing) of new devices into a network: their association process is vulnerable to man-in-the-middle attacks. This paper addresses three essential aspects in attaining secure association for such devices. First, we define a user-interface primitive, oblivious comparison, that allows users to approve authentic associations and abort compromised ones. This distills and generalizes several existing approve/abort mechanisms, and moreover we experimentally show that OC can be implemented using very little hardware: one LED and one switch. Second, we provide a new Message Recognition Protocol (MRP) that allows devices associated using oblivious comparison to exchange authenticated messages without the use of public-key cryptography (which exceeds the capabilities of many IoT devices). This protocol improves upon previously proposed MRPs in several respects. Third, we propose a robust definition of security for MRPs that is based on universal composability, and show that our MRP satisfies this definition

Get Your Hands Off My Laptop: Physical Side-Channel Key-Extraction Attacks on PCs

We demonstrate physical side-channel attacks on a popular software implementation of RSA and ElGamal, running on laptop computers. Our attacks use novel side channels, based on the observation that the ground electric potential, in many computers, fluctuates in a computation-dependent way. An attacker can measure this signal by touching exposed metal on the computer\u27s chassis with a plain wire, or even with a bare hand. The signal can also be measured at the remote end of Ethernet, VGA or USB cables. Through suitable cryptanalysis and signal processing, we have extracted 4096-bit RSA keys and 3072-bit ElGamal keys from laptops, via each of these channels, as well as via power analysis and electromagnetic probing. Despite the GHz-scale clock rate of the laptops and numerous noise sources, the full attacks require a few seconds of measurements using Medium Frequency signals (around 2 MHz), or one hour using Low Frequency signals (up to 40 kHz)

Efficient Cache Attacks on AES, and Countermeasures

We describe several software side-channel attacks based on inter-process leakage through the state of the CPU's memory cache. This leakage reveals memory access patterns, which can be used for cryptanalysis of cryptographic primitives that employ data-dependent table lookups. The attacks allow an unprivileged process to attack other processes running in parallel on the same processor, despite partitioning methods such as memory protection, sandboxing, and virtualization. Some of our methods require only the ability to trigger services that perform encryption or MAC using the unknown key, such as encrypted disk partitions or secure network links. Moreover, we demonstrate an extremely strong type of attack, which requires knowledge of neither the specific plaintexts nor ciphertexts and works by merely monitoring the effect of the cryptographic process on the cache. We discuss in detail several attacks on AES and experimentally demonstrate their applicability to real systems, such as OpenSSL and Linux's dm-crypt encrypted partitions (in the latter case, the full key was recovered after just 800 writes to the partition, taking 65 milliseconds). Finally, we discuss a variety of countermeasures which can be used to mitigate such attacks

Cloud-Assisted Multiparty Computation from Fully Homomorphic Encryption

We construct protocols for secure multiparty computation with the help of a computationally powerful party, namely the cloud\u27\u27. Our protocols are simultaneously efficient in a number of metrics: * Rounds: our protocols run in 4 rounds in the semi-honest setting, and 5 rounds in the malicious setting. * Communication: the number of bits exchanged in an execution of the protocol is independent of the complexity of function f being computed, and depends only on the length of the inputs and outputs. * Computation: the computational complexity of all parties is independent of the complexity of the function f, whereas that of the cloud is linear in the size of the circuit computing f. In the semi-honest case, our protocol relies on the ``ring learning with errors\u27\u27 (RLWE) assumption, whereas in the malicious case, security is shown under the Ring LWE assumption as well as the existence of simulation-extractable NIZK proof systems and succinct non-interactive arguments. In the malicious setting, we also relax the communication and computation requirements above, and only require that they be ``small\u27\u27 -- polylogarithmic in the computation size and linear in the size of the joint size of the inputs. Our constructions leverage the key homomorphic property of the recent fully homomorphic encryption scheme of Brakerski and Vaikuntanathan (CRYPTO 2011, FOCS 2011). Namely, these schemes allow combining encryptions of messages under different keys to produce an encryption (of the sum of the messages) under the sum of the keys. We also design an efficient, non-interactive threshold decryption protocol for these fully homomorphic encryption schemes

On-the-Fly Multiparty Computation on the Cloud via Multikey Fully Homomorphic Encryption

We propose a new notion of secure multiparty computation aided by a computationally-powerful but untrusted cloud server. In this notion that we call on-the-fly multiparty computation (MPC), the cloud can non-interactively perform arbitrary, dynamically chosen computations on data belonging to arbitrary sets of users chosen on-the-fly. All user\u27s input data and intermediate results are protected from snooping by the cloud as well as other users. This extends the standard notion of fully homomorphic encryption (FHE), where users can only enlist the cloud\u27s help in evaluating functions on their own encrypted data. In on-the-fly MPC, each user is involved only when initially uploading his (encrypted) data to the cloud, and in a final output decryption phase when outputs are revealed; the complexity of both is independent of the function being computed and the total number of users in the system. When users upload their data, they need not decide in advance which function will be computed, nor who they will compute with; they need only retroactively approve the eventually-chosen functions and on whose data the functions were evaluated. This notion is qualitatively the best possible in minimizing interaction, since the users\u27 interaction in the decryption stage is inevitable: we show that removing it would imply generic program obfuscation and is thus impossible. Our contributions are two-fold: 1. We show how on-the-fly MPC can be achieved using a new type of encryption scheme that we call multikey FHE, which is capable of operating on inputs encrypted under multiple, unrelated keys. A ciphertext resulting from a multikey evaluation can be jointly decrypted using the secret keys of all the users involved in the computation. 2. We construct a multikey FHE scheme based on NTRU, a very efficient public-key encryption scheme proposed in the 1990s. It was previously not known how to make NTRU fully homomorphic even for a single party. We view the construction of (multikey) FHE from NTRU encryption as a main contribution of independent interest. Although the transformation to a fully homomorphic system deteriorates the efficiency of NTRU somewhat, we believe that this system is a leading candidate for a practical FHE scheme