Bloom Filters in Adversarial Environments

Many efficient data structures use randomness, allowing them to improve upon deterministic ones. Usually, their efficiency and correctness are analyzed using probabilistic tools under the assumption that the inputs and queries are independent of the internal randomness of the data structure. In this work, we consider data structures in a more robust model, which we call the adversarial model. Roughly speaking, this model allows an adversary to choose inputs and queries adaptively according to previous responses. Specifically, we consider a data structure known as "Bloom filter" and prove a tight connection between Bloom filters in this model and cryptography. A Bloom filter represents a set $S$ of elements approximately, by using fewer bits than a precise representation. The price for succinctness is allowing some errors: for any $x \in S$ it should always answer `Yes', and for any $x \notin S$ it should answer `Yes' only with small probability. In the adversarial model, we consider both efficient adversaries (that run in polynomial time) and computationally unbounded adversaries that are only bounded in the number of queries they can make. For computationally bounded adversaries, we show that non-trivial (memory-wise) Bloom filters exist if and only if one-way functions exist. For unbounded adversaries we show that there exists a Bloom filter for sets of size $n$ and error $\varepsilon$, that is secure against $t$ queries and uses only $O(n \log{\frac{1}{\varepsilon}}+t)$ bits of memory. In comparison, $n\log{\frac{1}{\varepsilon}}$ is the best possible under a non-adaptive adversary

Faster Deterministic Algorithms for Packing, Matching and tt-Dominating Set Problems

In this paper, we devise three deterministic algorithms for solving the $m$-set $k$-packing, $m$-dimensional $k$-matching, and $t$-dominating set problems in time $O^*(5.44^{mk})$, $O^*(5.44^{(m-1)k})$ and $O^*(5.44^{t})$, respectively. Although recently there has been remarkable progress on randomized solutions to those problems, our bounds make good improvements on the best known bounds for deterministic solutions to those problems.Comment: ISAAC13 Submission. arXiv admin note: substantial text overlap with arXiv:1303.047

Chameleon: a Blind Double Trapdoor Hash Function for Securing AMI Data Aggregation

Data aggregation is an integral part of Advanced Metering Infrastructure (AMI) deployment that is implemented by the concentrator. Data aggregation reduces the number of transmissions, thereby reducing communication costs and increasing the bandwidth utilization of AMI. However, the concentrator poses a great risk of being tampered with, leading to erroneous bills and possible consumer disputes. In this paper, we propose an end-to-end integrity protocol using elliptic curve based chameleon hashing to provide data integrity and authenticity. The concentrator generates and sends a chameleon hash value of the aggregated readings to the Meter Data Management System (MDMS) for verification, while the smart meter with the trapdoor key computes and sends a commitment value to the MDMS so that the resulting chameleon hash value calculated by the MDMS is equivalent to the previous hash value sent by the concentrator. By comparing the two hash values, the MDMS can validate the integrity and authenticity of the data sent by the concentrator. Compared with the discrete logarithm implementation, the ECC implementation reduces the computational cost of MDMS, concentrator and smart meter by approximately 36.8%, 80%, and 99% respectively. We also demonstrate the security soundness of our protocol through informal security analysis

Trading Determinism for Time in Space Bounded Computations

Savitch showed in $1970$ that nondeterministic logspace (NL) is contained in deterministic $\mathcal{O}(\log^2 n)$ space but his algorithm requires quasipolynomial time. The question whether we can have a deterministic algorithm for every problem in NL that requires polylogarithmic space and simultaneously runs in polynomial time was left open. In this paper we give a partial solution to this problem and show that for every language in NL there exists an unambiguous nondeterministic algorithm that requires $\mathcal{O}(\log^2 n)$ space and simultaneously runs in polynomial time.Comment: Accepted in MFCS 201