Autonomous vehicles (AVs) are becoming increasingly prevalent. However, current AVs are unable to handle unexpected traffic signs (e.g., construction zones, road closures) encountered on the roads. To address this limitation, we propose MOSER, a Multimodal rOad Sign intERpretation system, to enable automated detection and interpretation of diverse road signs. Our system consists of a pipeline architecture with three main components, including perception, text processing, and planning. The perception component detects arbitrary road signs and extracts the sign text into proper groups and orders. The text processing component then identifies the high-level semantics of the text and determines whether any actions are required for the autonomous vehicle. Based on the interpretation of the signs, the planning component provides navigation guidance, such as instructing the vehicle to stop at a specific location or adding rules to its internal map. To the best of our knowledge, this is the first attempt to address the interpretation of arbitrary road signs using a multimodal processing strategy. Our work provides important insights and capabilities to support Level 4 autonomous vehicles, ensuring their safety and smoothness of operation.

Ensuring the authenticity and integrity of data transferred over the Internet is still a daunting task. Although various mechanisms have been proposed to strengthen the key management infrastructure, they still rely on trusted third parties (TTPs) or require additional entities to monitor the system. This paper introduces Bidirectional Blockchain - a collection of protocols that ensure the authenticity of data sent from a collection of one or more servers to distributed clients (e.g., Internet of Things (IoT) devices) without relying on TTPs. Bidirectional Blockchain is based on the benefits of multi-party computation and blockchain to ensure the secrecy of keys used to sign the distributed data and the correctness and integrity of the received data, respectively. We implemented Bidirectional Blockchain on a Raspberry Pi, and our evaluation results confirm that Bidirectional Blockchain is lightweight and hence can be used to secure a variety of data transactions, including software updates, even on resource-constrained devices.

This paper introduces a system for providing integrity, authenticity, and privacy of data transactions for resource-limited Internet of Things (IoT) smart devices using blockchain (BC) and Multi-Party Computation (MPC). In particular, we introduce two mechanisms: one provides privacy and integrity protections on the data being collected by the smart devices, such as medical records or diagnostic data, and the other provides authenticity and integrity of data going into the smart devices, such as software updates. Our experimental results indicate that our proposed mechanisms incur small overhead in terms of storage, communication, and computation, indicating their feasibility to IoT devices with limited storage, computational, and communicational capabilities.

In a secret sharing scheme a dealer shares a secret s among n parties such that an adversary corrupting up to t parties does not learn s, while any t+1 parties can efficiently recover s. Over a long period of time all parties may be corrupted thus violating the threshold, which is accounted for in Proactive Secret Sharing (PSS). PSS schemes periodically rerandomize (refresh) the shares of the secret and invalidate old ones. PSS retains confidentiality even when all parties are corrupted over the lifetime of the secret, but no more than t during a certain window of time, called the refresh period. Existing PSS schemes only guarantee secrecy in the presence of an honest majority with less than n2 total corruptions during a refresh period; an adversary corrupting a single additional party, even if only passively, obtains the secret. This work is the first feasibility result demonstrating PSS tolerating a dishonest majority, it introduces the first PSS scheme secure against t<n passive adversaries without recovery of lost shares, it can also recover from honest faulty parties losing their shares, and when tolerating e faults the scheme tolerates t<n-e passive corruptions. A non-robust version of the scheme can tolerate t

Most current digital currency schemes and associated ledgers are either centralized or completely distributed similar to the design adopted by Bitcoin. Centralized schemes enable accountability, but leave the privacy of users' identities and transactions in the hands of one organization. Distributed schemes can ensure better privacy but provide little accountability. In this paper we design a privacy-preserving proactively-secure distributed ledger and associated transaction protocols that can be used to implement an accountable digital currency that inherits the ledger's privacy and security features. One of the main technical challenges that we address is dealing with the increase in ledger size over time, an unavoidable aspect as the currency spreads and the ledger is required to be maintained for a long time in the future. We accomplish this by reducing the distributed (secret-shared) storage footprint and the required bandwidth and computation for proactively refreshing the ledger to ensure long-term confidentiality and security. In the full version, we provide performance analysis of some of the subprotocols to estimate the time required to perform transactions and the proactive refreshing of the ledger.

In this paper we argue that privacy-preserving digital coins with low computation and communication overhead can be utilized as micropayments to harden online applications and services. We call such digital coins App Coins, and the applications that use them App Coins-hardened applications. Our thesis is that App Coins-hardened applications can greatly increase the financial cost (to the attackers) of large classes of malicious behavior on the Internet. App Coins can also be used to incentivize and reward cooperative and honest online behavior. We develop cryptographic protocols for such privacy-preserving non-malleable and double-spending resistant App Coins. We show how to modify two sample applications, email and onion routing, to utilize such App Coins. Our performance analysis demonstrates that our protocols are practical and can be easily implemented using commodity hardware.

In PODC 1991 Ostrovsky and Yung [35] introduced the proactive security model, where corruptions spread throughout the network, analogous to the spread of a virus or a worm. PODC 2006 distinguished lecture by Danny Dolev, that also appears in the PODC06 proceedings, lists the above work as one of PODC's "Century Papers at the First Quarter-Century Milestone" [22]. At the very center of this work is the notion of proactive secret sharing schemes. Secret sharing schemes allow a dealer to distribute a secret among a group of parties such that while the group of parties jointly possess the secret, no sufficiently small subset of the parties can learn any information about the secret. The secret can be reconstructed only when a sufficient number of shares are combined together. Most secret sharing schemes assume that an adversary can only corrupt some fixed number of the parties over the entire lifetime of the secret; such a model is unrealistic in the case where over a long enough period of time, an adversary can eventually corrupt all parties or a large enough fraction that exceeds such a threshold. More specifically, in the proactive security model, the adversary is not limited in the number of parties it can corrupt, but rather in the rate of corruption with respect to a "rebooting" rate. Ostrovsky and Yung proposed the first proactive secret sharing scheme, which received a lot of follow-up attention. In the same paper, Ostrovsky and Yung also showed that constructing a general purpose secure multiparty computation (MPC) protocol in the proactive security model is feasible as long as the rate of corruption is a constant fraction of the parties. Their result, however, was shown only for stand-alone security and incurred a large polynomial communication overhead for each gate of the computation. Following the initial work defining the proactive security model, numerous cryptographic primitives and distributed protocols have been adapted to the proactive security model, such as proactively secure threshold encryption, proactive Byzantine agreement, proactive key management, proactive digital signatures, and many others. All these results use proactive secret sharing schemes. In this paper, we introduce a new "packed" proactive secret sharing (PPSS) scheme, where the amortized communication and the amortized computational cost of maintaining each individual secret is optimal (e.g., a constant rate), resolving a long standing problem in this area. Assuming secure point-to-point channels and authenticated, reliable broadcast over a synchronous network, our PPSS scheme can tolerate a 1/3-ε (resp. 1/2-ε) corruption rate against a malicious adversary, and is perfectly (resp. statistically) UC-secure, whereas all previous proactive secret sharing schemes have been secure under cryptographic assumptions only. As an application of our PPSS scheme, we show how to construct a proactive multiparty computation (PMPC) protocol with the same threshold as the PPSS scheme and near-linear communication complexity. PMPC problem is very general and implies, for example, proactive Byzantine Agreement. Our PMPC result also matches the asymptotic communication complexity of the best known MPC results in the "classical" model of stationary faults [19].