The Internet of Things (IoT) has become increasingly popular in people's daily lives. The pervasive IoT devices are encouraged to share data with each other in order to better serve the users. However, users are reluctant to share sensitive data due to privacy concerns. In this paper, we study the anonymous data aggregation for the IoT system, in which the IoT company servers, though not fully trustworthy, are used to assist the aggregation. We propose an efficient and accountable aggregation scheme that can preserve the data anonymity. We analyze the communication and computation overheads of the proposed scheme, and evaluate the total execution time and the per-user communication overhead with extensive simulations. The results show that our scheme is more efficient than the previous peer-shuffle protocol, especially for data aggregation from multiple providers.
Protection of privacy has become an important problem in data mining. In particular, individuals have become increasingly unwilling to share their data, frequently resulting in individuals either refusing to share their data or providing incorrect data. In turn, such problems in data collection can affect the success of data mining, which relies on sufficient amounts of accurate data in order to produce meaningful results. Random perturbation and randomized response techniques can provide some level of privacy in data collection, but they have an associated cost in accuracy. Cryptographic privacy-preserving data mining methods provide good privacy and accuracy properties. However, in order to be efficient, those solutions must be tailored to specific mining tasks, thereby losing generality.In this paper, we propose efficient cryptographic techniques for online data collection in which data from a large number of respondents is collected anonymously, without the help of a trusted third party. That is, our solution allows the miner to collect the original data from each respondent, but in such a way that the miner cannot link a respondent's data to the respondent. An advantage of such a solution is that, because it does not change the actual data, its success does not depend on the underlying data mining problem. We provide proofs of the correctness and privacy of our solution, as well as experimental data that demonstrates its efficiency. We also extend our solution to tolerate certain kinds of malicious behavior of the participants. Informally, a communication protocol is sender k - anonymous if it can guarantee that an adversary, trying to determine the sender of a particular message, can only narrow down its search to a set of k suspects. Receiver k-anonymity places a similar guarantee on the receiver: an adversary, at best, can only narrow down the possible receivers to a set of size k. In this paper we introduce the notions of sender and receiver k-anonymity and consider their applications. We show that there exist simple and efficient protocols which are k-anonymous for both the sender and the receiver in a model where a polynomial time adversary can see all traffic in the network and can control up to a constant fraction of the participants. Our protocol is provably secure, practical, and does not require the existence of trusted third parties. This paper also provides a conceptually simple augmentation to Chaum's DC-Nets that adds robustness against adversaries who attempt to disrupt the protocol through perpetual transmission or selective non-participation. This paper presents Riposte, a new system for anonymous broadcast messaging. Riposte is the first such system, to our knowledge, that simultaneously protects against traffic-analysis attacks, prevents anonymous denial-of-service by malicious clients, and scales to million-user anonymity sets. To achieve these properties, Riposte makes novel use of techniques used in systems for private information retrieval and secure multi-party computation. For latency-tolerant workloads with many more readers than writers (e.g. Twitter, Wikileaks), we demonstrate that a three-server Riposte cluster can build an anonymity set of 2,895,216 users in 32 hours. Current anonymous communication systems make a trade-off between weak anonymity among many nodes, via onion routing, and strong anonymity among few nodes, via DC-nets. We develop novel techniques in Dissent, a practical group anonymity system, to increase by over two orders of magnitude the scalability of strong, traffic analysis resistant approaches. Dissent derives its scalability from a client server architecture, in which many unreliable clients depend on a smaller and more robust, but administratively decentralized, set of servers. Clients trust only that at least one server in the set is honest, but need not know or choose which server to trust. Unlike the quadratic costs of prior peer-to-peer DC-nets schemes, Dissent's client server design makes communication and processing costs linear in the number of clients, and hence in anonymity set size. Further, Dissent's servers can unilaterally ensure progress, even if clients respond slowly or disconnect at arbitrary times, ensuring robustness against client churn, tail latencies, and DoS attacks. On DeterLab, Dissent scales to 5,000 online participants with latencies as low as 600 milliseconds for 600-client groups. An anonymous Web browsing application also shows that Dissent's performance suffices for interactive communication within smaller local-area groups. Users often wish to participate in online groups anonymously, but misbehaving users may abuse this anonymity to disrupt the group's communication. Existing messaging protocols such as DC-nets leave groups vulnerable to denial-of-service and Sybil attacks, Mix-nets are difficult to protect against traffic analysis, and accountable voting protocols are unsuited to general anonymous messaging. We present the first general messaging protocol that offers provable anonymity with accountability for moderate-size groups, and efficiently handles unbalanced loads where few members wish to transmit in a given round. The N group members first cooperatively shuffle an N x N matrix of pseudorandom seeds, then use these seeds in N "pre-planned" DC-nets protocol runs. Each DC-nets run transmits the variable-length bulk data comprising one member's message, using the minimum number of bits required for anonymity under our attack model. The protocol preserves message integrity and one-to-one correspondence between members and messages, makes denial-of-service attacks by members traceable to the culprit, and efficiently handles large, unbalanced message loads. A working prototype demonstrates the protocol's practicality for anonymous messaging in groups of 40+ members. Among anonymity systems, DC-nets have long held attraction for their resistance to traffic analysis attacks, but practical implementations remain vulnerable to internal disruption or "jamming" attacks, which require time-consuming detection procedures to resolve. We present Verdict, the first practical anonymous group communication system built using proactively verifiable DC-nets: participants use public-key cryptography to construct DC-net ciphertexts, and use zero-knowledge proofs of knowledge to detect and exclude misbehavior before disruption. We compare three alternative constructions for verifiable DC-nets: one using bilinear maps and two based on simpler ElGamal encryption. While verifiable DC-nets incur higher computational overheads due to the public-key cryptography involved, our experiments suggest that Verdict is practical for anonymous group messaging or microblogging applications, supporting groups of 100 clients at 1 second per round or 1000 clients at 10 seconds per round. Furthermore, we show how existing symmetric-key DC-nets can "fall back" to a verifiable DC-net to quickly identify misbehavior, speeding up previous detections schemes by two orders of magnitude. 