Human errors in performing security-critical tasks are typically blamed on the complexity of those tasks. However, such errors can also occur because of (possibly unexpected) sensory distractions. A sensory distraction that produces negative effects can be abused by the adversary that controls the environment. Meanwhile, a distraction with positive effects can be artificially introduced to improve user performance. The goal of this work is to explore the effects of visual stimuli on the performance of security-critical tasks. To this end, we experimented with a large number of subjects who were exposed to a range of unexpected visual stimuli while attempting to perform Bluetooth Pairing. Our results clearly demonstrate substantially increased task completion times and markedly lower task success rates. These negative effects are noteworthy, especially, when contrasted with prior results on audio distractions which had positive effects on performance of similar tasks. Experiments were conducted in a novel (fully automated and completely unattended) experimental environment. This yielded more uniform experiments, better scalability and significantly lower financial and logistical burdens. We discuss this experience, including benefits and limitations of the unattended automated experiment paradigm.
For example, Short Authenticated String (SAS) protocols ask the user to compare two strings of about 20 bits each @cite_10 .
@cite_10
1819119697 2104145890 1686853624 2157233202
We propose a protocol for secure comparison of integers based on homomorphic encryption. We also propose a homomorphic encryption scheme that can be used in our protocol and makes it more efficient than previous solutions. Our protocol is well-suited for application in on-line auctions, both with respect to functionality and performance. It minimizes the amount of information bidders need to send, and for comparison of 16 bit numbers with security based on 1024 bit RSA (executed by two parties), our implementation takes 0.28 seconds including all computation and communication. Using precomputation, one can save a factor of roughly 10. We consider the problem of securely evaluating the Greater Than (GT) predicate and its extension - transferring one of two secrets, depending on the result of comparison. We generalize our solutions and show how to securely decide membership in the union of a set of intervals. We then consider the related problem of comparing two encrypted numbers. We show how to efficiently apply our solutions to practical settings, such as auctions with the semi-honest auctioneer, proxy selling, etc. All of our protocols are one round. We propose new primitives, Strong Conditional Oblivious Transfer (SCOT) and Conditional En- crypted Mapping (CEM), which capture common security properties of one round protocols in a variety of settings, which may be of independent interest. Key agreement protocols are frequently based on the Diffie-Hellman protocol but require authenticating the protocol messages in two ways. This can be made by a cross-authentication protocol. Such protocols, based on the assumption that a channel which can authenticate short strings is available (SAS-based), have been proposed by Vaudenay. In this paper, we survey existing protocols and we propose a new one. Our proposed protocol requires three moves and a single SAS to be authenticated in two ways. It is provably secure in the random oracle model. We can further achieve security with a generic construction (e.g. in the standard model) at the price of an extra move. We discuss applications such as secure peer-to-peer VoIP. There is a wide range of applications that require to query a large database of texts to search for similar strings or substrings. Traditional approximate substring matching requests a user to specify a similarity threshold. Without top-k approximate substring matching, users have to try repeatedly different maximum distance threshold values when the proper threshold is unknown in advance. In our paper, we first propose the efficient algorithms for finding the top-k approximate substring matches with a given query string in a set of data strings. To reduce the number of expensive distance computations, the proposed algorithms utilize our novel filtering techniques which take advantages of q-grams and inverted q-gram indexes available. We conduct extensive experiments with real-life data sets. Our experimental results confirm the effectiveness and scalability of our proposed algorithms.