Seeking Anonymity in an Internet Panopticon

Obtaining and maintaining anonymity on the Internet is challenging. The state of the art in deployed tools, such as Tor, uses onion routing (OR) to relay encrypted connections on a detour passing through randomly chosen relays scattered around the Internet. Unfortunately, OR is known to be vulnerable at least in principle to several classes of attacks for which no solution is known or believed to be forthcoming soon. Current approaches to anonymity also appear unable to offer accurate, principled measurement of the level or quality of anonymity a user might obtain. Toward this end, we offer a high-level view of the Dissent project, the first systematic effort to build a practical anonymity system based purely on foundations that offer measurable and formally provable anonymity properties. Dissent builds on two key pre-existing primitives - verifiable shuffles and dining cryptographers - but for the first time shows how to scale such techniques to offer measurable anonymity guarantees to thousands of participants. Further, Dissent represents the first anonymity system designed from the ground up to incorporate some systematic countermeasure for each of the major classes of known vulnerabilities in existing approaches, including global traffic analysis, active attacks, and intersection attacks. Finally, because no anonymity protocol alone can address risks such as software exploits or accidental self-identification, we introduce WiNon, an experimental operating system architecture to harden the uses of anonymity tools such as Tor and Dissent against such attacks.Comment: 8 pages, 10 figure

ARPA Whitepaper

We propose a secure computation solution for blockchain networks. The correctness of computation is verifiable even under malicious majority condition using information-theoretic Message Authentication Code (MAC), and the privacy is preserved using Secret-Sharing. With state-of-the-art multiparty computation protocol and a layer2 solution, our privacy-preserving computation guarantees data security on blockchain, cryptographically, while reducing the heavy-lifting computation job to a few nodes. This breakthrough has several implications on the future of decentralized networks. First, secure computation can be used to support Private Smart Contracts, where consensus is reached without exposing the information in the public contract. Second, it enables data to be shared and used in trustless network, without disclosing the raw data during data-at-use, where data ownership and data usage is safely separated. Last but not least, computation and verification processes are separated, which can be perceived as computational sharding, this effectively makes the transaction processing speed linear to the number of participating nodes. Our objective is to deploy our secure computation network as an layer2 solution to any blockchain system. Smart Contracts\cite{smartcontract} will be used as bridge to link the blockchain and computation networks. Additionally, they will be used as verifier to ensure that outsourced computation is completed correctly. In order to achieve this, we first develop a general MPC network with advanced features, such as: 1) Secure Computation, 2) Off-chain Computation, 3) Verifiable Computation, and 4)Support dApps' needs like privacy-preserving data exchange

Hang With Your Buddies to Resist Intersection Attacks

Some anonymity schemes might in principle protect users from pervasive network surveillance - but only if all messages are independent and unlinkable. Users in practice often need pseudonymity - sending messages intentionally linkable to each other but not to the sender - but pseudonymity in dynamic networks exposes users to intersection attacks. We present Buddies, the first systematic design for intersection attack resistance in practical anonymity systems. Buddies groups users dynamically into buddy sets, controlling message transmission to make buddies within a set behaviorally indistinguishable under traffic analysis. To manage the inevitable tradeoffs between anonymity guarantees and communication responsiveness, Buddies enables users to select independent attack mitigation policies for each pseudonym. Using trace-based simulations and a working prototype, we find that Buddies can guarantee non-trivial anonymity set sizes in realistic chat/microblogging scenarios, for both short-lived and long-lived pseudonyms.Comment: 15 pages, 8 figure

Universally Verifiable Poll-Site Voting Schemes Providing Everlasting Privacy

Computer based voting brings up huge challenges for technology. On the one hand an electronic voting system has to be transparent enough to allow verification of its correct functioning; on the other hand, it must ensure that these verification procedures do not allow an attacker to violate voter privacy. Both requirements can be addressed by providing cryptographically secured voting receipts. Each voter cast his or her vote in encoded form and receives a copy of the recorded ballot as receipt. The voters can use these receipts to verify that their vote is contained in the input of the tally. Furthermore, the encoded votes are publicly processed, which allows voters and observers to check that the election outcome has been determined correctly. However, to provide a private and free election, no voter should be able to prove to someone else for whom he or she voted. This must not only be prevented during the election, but also afterwards for an indefinite period of time. Especially with respect to everlasting privacy this is not ensured by most verifiable voting systems. If the receipt contains, for instance, the voting decision encrypted using some public key cryptography, an attacker can determine the candidates selected as soon as the underlying computational problem has been solved for the key length chosen. In this work we provide a summary of privacy weaknesses that may arise in verifiable electronic poll-site voting systems, and we identify and solve open issues. More precisely, we concentrate on the following three questions: (1) How can we show correct anonymization of votes in an efficient and privacy preserving manner using a generic approach? (2) How can we introduce everlasting privacy to mixing and homomorphic tallying based voting schemes? (3) How can we reduce the amount of trust voters have to put in authorities regarding privacy? In electronic voting so-called reencryption mix-nets are used to anonymize votes. These mix-nets shuffles votes in a universally verifiable manner, i.e., they publish some audit information allowing voters and observers to verify that the votes came out as they went in. In practice, mostly generic verification procedures are used to show correctness of this process. However, many of them do not provide an adequate level of privacy. To address (1), we investigate several proposals and introduce a new protocol that combines existing approaches but improves them with respect to privacy and efficiency. Another drawback of mixing based voting schemes is that all implementations provide computational privacy only. We address (2) by presenting a mix-net that uses a homomorphic and unconditionally hiding commitment scheme to encode the votes and audit data, implying everlasting privacy. The correctness of the anonymization process is guaranteed with overwhelming probability, even if all authorities collaborate. An implication of our result is that many current voting systems that use mix-nets can be upgraded to everlasting privacy. Subsequently, we show that this protocol can be applied to Prêt à Voter and Split-Ballot imposing only minor changes to current implementations. The same approach is used to introduce everlasting privacy to homomorphic tallying based schemes. The votes are encoded with an unconditionally hiding commitment scheme, they are homomorphically tallied in public, and the result is decoded afterwards. To show that our solution can be applied to poll-site voting, we describe how the Scratch & Vote voting system can be improved using our tallying protocol. Again only minor changes to the classical scheme are necessary. To address (3), the approach of non-personalized receipts is analyzed. If the receipts handed out to the voters do not contain a link to their vote cast, they do not have to put their trust in authorities keeping this association secret. We introduce an electronic ballot box that generates non-personalized receipts using a process that is similar to the anonymization procedure carried out by mix-nets. The correctness of the receipt generation is universally verifiable. Furthermore, our approach improves on existing solutions with respect to correctness and privacy. Finally, we compare all voting systems that are improved in this work, highlight their advantages and disadvantages, and conclude with key issues for future work

Distributed secure storage scheme based on sharding blockchain

Distributed storage can store data in multiple devices or servers to improve data security. However, in today’s explosive growth of network data, traditional distributed storage scheme is faced with some severe challenges such as insufficient performance, data tampering, and data lose. A distributed storage scheme based on blockchain has been proposed to improve security and efficiency of traditional distributed storage. Under this scheme, the following improvements have been made in this paper. This paper first analyzes the problems faced by distributed storage. Then proposed to build a new distributed storage blockchain scheme with sharding blockchain. The proposed scheme realizes the partitioning of the network and nodes by means of blockchain sharding technology, which can improve the efficiency of data verification between nodes. In addition, this paper uses polynomial commitment to construct a new verifiable secret share scheme called PolyVSS. This new scheme is one of the foundations for building our improved distributed storage blockchain scheme. Compared with the previous scheme, our new scheme does not require a trusted third party and has some new features such as homomorphic and batch opening. The security of VSS can be further improved. Experimental comparisons show that the proposed scheme significantly reduces storage and communication costs

An Analysis of Chaum's Voter-Verifiable Election Scheme

Chaum's Voter-Verifiable election scheme introduces a new direction for electronic voting. The scheme eliminates the need to trust any machinery or authority, and instead relies on mathematical proof to certify the trustworthiness of an election. Audits at every stage of the election create transparency that should restore voter confidence in the election process. We survey and categorize the field of electronic voting, and place Chaum's scheme within this context. We then define a framework of formal requirements of a voting system. We present Chaum's scheme itself, and give an analysis. Based on our technical analysis, we find the scheme to be secure. However, after considering other implementation concerns, we recognize various minor obstacles limiting its widespread adoption in today's elections. Despite this, we believe that the substance of the scheme is promising and maybe an improved, simpler variant might better suit future elections

Protecting privacy of users in brain-computer interface applications

Machine learning (ML) is revolutionizing research and industry. Many ML applications rely on the use of large amounts of personal data for training and inference. Among the most intimate exploited data sources is electroencephalogram (EEG) data, a kind of data that is so rich with information that application developers can easily gain knowledge beyond the professed scope from unprotected EEG signals, including passwords, ATM PINs, and other intimate data. The challenge we address is how to engage in meaningful ML with EEG data while protecting the privacy of users. Hence, we propose cryptographic protocols based on secure multiparty computation (SMC) to perform linear regression over EEG signals from many users in a fully privacy-preserving(PP) fashion, i.e., such that each individual's EEG signals are not revealed to anyone else. To illustrate the potential of our secure framework, we show how it allows estimating the drowsiness of drivers from their EEG signals as would be possible in the unencrypted case, and at a very reasonable computational cost. Our solution is the first application of commodity-based SMC to EEG data, as well as the largest documented experiment of secret sharing-based SMC in general, namely, with 15 players involved in all the computations