Private Searching for Single and Conjunctive Keywords on Streaming Data

ABSTRACT Private searching on streaming data allows a user to collect potentially useful information from huge streaming sources of data without revealing his or her searching criteria. This technique can be used for airports, without knowing a classified "possible terrorists" list, to find if any of hundreds of passenger lists has a name from the "possible terrorists" list and if so his/hers itinerary. Current solutions for private searching on streaming data only support searching for "OR" of keywords or "AND" of two sets of keywords. In this paper, we extend the types of private queries to support searching on streaming data for an "OR" of a set of both single and conjunctive keywords, such as are single keywords and , , … , , are unordered conjunctive keywords. Our protocol is built on Boneh et al.'s result for the evaluation of 2-DNF formulas on ciphertexts. The size of our encrypted dictionary is | | only, which is much less than | | , the size of the encrypted dictionary if conjunctive keywords , ( = 1,2, … , ) is treated as single keyword, where we assume , ∈ ( = 1,2, … , )

A Selectivity based approach to Continuous Pattern Detection in Streaming Graphs

Cyber security is one of the most significant technical challenges in current times. Detecting adversarial activities, prevention of theft of intellectual properties and customer data is a high priority for corporations and government agencies around the world. Cyber defenders need to analyze massive-scale, high-resolution network flows to identify, categorize, and mitigate attacks involving networks spanning institutional and national boundaries. Many of the cyber attacks can be described as subgraph patterns, with prominent examples being insider infiltrations (path queries), denial of service (parallel paths) and malicious spreads (tree queries). This motivates us to explore subgraph matching on streaming graphs in a continuous setting. The novelty of our work lies in using the subgraph distributional statistics collected from the streaming graph to determine the query processing strategy. We introduce a "Lazy Search" algorithm where the search strategy is decided on a vertex-to-vertex basis depending on the likelihood of a match in the vertex neighborhood. We also propose a metric named "Relative Selectivity" that is used to select between different query processing strategies. Our experiments performed on real online news, network traffic stream and a synthetic social network benchmark demonstrate 10-100x speedups over selectivity agnostic approaches.Comment: in 18th International Conference on Extending Database Technology (EDBT) (2015

Finding video on the web

At present very little is known about how people locate and view videos. This study draws a rich picture of everyday video seeking strategies and video information needs, based on an ethnographic study of New Zealand university students. These insights into the participants’ activities and motivations suggest potentially useful facilities for a video digital library

When Things Matter: A Data-Centric View of the Internet of Things

With the recent advances in radio-frequency identification (RFID), low-cost wireless sensor devices, and Web technologies, the Internet of Things (IoT) approach has gained momentum in connecting everyday objects to the Internet and facilitating machine-to-human and machine-to-machine communication with the physical world. While IoT offers the capability to connect and integrate both digital and physical entities, enabling a whole new class of applications and services, several significant challenges need to be addressed before these applications and services can be fully realized. A fundamental challenge centers around managing IoT data, typically produced in dynamic and volatile environments, which is not only extremely large in scale and volume, but also noisy, and continuous. This article surveys the main techniques and state-of-the-art research efforts in IoT from data-centric perspectives, including data stream processing, data storage models, complex event processing, and searching in IoT. Open research issues for IoT data management are also discussed

Search for axions in streaming dark matter

A new search strategy for the detection of the elusive dark matter (DM) axion is proposed. The idea is based on streaming DM axions, whose flux might get temporally enormously enhanced due to gravitational lensing. This can happen if the Sun or some planet (including the Moon) is found along the direction of a DM stream propagating towards the Earth location. The experimental requirements to the axion haloscope are a wide-band performance combined with a fast axion rest mass scanning mode, which are feasible. Once both conditions have been implemented in a haloscope, the axion search can continue parasitically almost as before. Interestingly, some new DM axion detectors are operating wide-band by default. In order not to miss the actually unpredictable timing of a potential short duration signal, a network of co-ordinated axion antennae is required, preferentially distributed world-wide. The reasoning presented here for the axions applies to some degree also to any other DM candidates like the WIMPs.Comment: 5 page

How people find videos

At present very little is known about how people locate and view videos 'in the wild'. This study draws a rich picture of everyday video seeking strategies and video information needs, based on an ethnographic study of New Zealand university students. These insights into the participants' activities and motivations suggest potentially useful facilities for a video digital library