2945748
Time Series Compressibility and Privacy
In this paper we study the trade-offs between time series compressibility and partial information hiding and their fundamental implications on how we should introduce uncertainty about individual values by perturbing them. More specifically, if the perturbation does not have the same compressibility properties as the original data, then it can be detected and filtered out, reducing uncertainty. Thus, by making the perturbation "similar" to the original data, we can both preserve the structure of the data better, while simultaneously making breaches harder. However, as data become more compressible, a fraction of the uncertainty can be removed if true values are leaked, revealing how they were perturbed. We formalize these notions, study the above trade-offs on real data and develop practical schemes which strike a good balance and can also be extended for on-the-fly data hiding in a streaming environment.
1718945
Dynamic authenticated index structures for outsourced databases
In outsourced database (ODB)systems the database owner publishes its data through a number of remote servers, with the goal of enabling clients at the edge of the network to access and query the data more efficiently. As servers might be untrusted or can be compromised, query authentication becomes an essential component of ODB systems. Existing solutions for this problem concentrate mostly on static scenarios and are based on idealistic properties for certain cryptographic primitives. In this work, first we define a variety of essential and practical cost metrics associated with ODB systems. Then, we analytically evaluate a number of different approaches, in search for a solution that best leverages all metrics. Most importantly, we look at solutions that can handle dynamic scenarios, where owners periodically update the data residing at the servers. Finally, we discuss query freshness, a new dimension in data authentication that has not been explored before. A comprehensive experimental evaluation of the proposed and existing approaches is used to validate the analytical models and verify our claims. Our findings exhibit that the proposed solutions improve performance substantially over existing approaches, both for static and dynamic environments.
3002704
Approximate aggregation techniques for sensor databases
In the emerging area of sensor-based systems, a significant challenge is to develop scalable, fault-tolerant methods to extract useful information from the data the sensors collect. An approach to this data management problem is the use of sensor database systems, exemplified by TinyDB and Cougar, which allow users to perform aggregation queries such as MIN, COUNT and AVG on a sensor network. Due to power and range constraints, centralized approaches are generally impractical, so most systems use in-network aggregation to reduce network traffic. However, these aggregation strategies become bandwidth-intensive when combined with the fault-tolerant, multipath routing methods often used in these environments. For example, duplicate-sensitive aggregates such as SUM cannot be computed exactly using substantially less bandwidth than explicit enumeration. To avoid this expense, we investigate the use of approximate in-network aggregation using small sketches. Our contributions are as follows: 1) we generalize well known duplicate-insensitive sketches for approximating COUNT to handle SUM, 2) we present and analyze methods for using sketches to produce accurate results with low communication and computation overhead, and 3) we present an extensive experimental validation of our methods.
8490960
Proof-Infused Streams: Enabling Authentication of Sliding Window Queries On Streams
As computer systems are essential components of many critical commercial services, the need for secure online transactions is now becoming evident. The demand for such applications, as the market grows, exceeds the capacity of individual businesses to provide fast and reliable services, making outsourcing technologies a key player in alleviating issues of scale. Consider a stock broker that needs to provide a real-time stock trading monitoring service to clients. Since the cost of multicasting this information to a large audience might become prohibitive, the broker could outsource the stock feed to third-party providers, who are in turn responsible for forwarding the appropriate sub-feed to clients. Evidently, in critical applications the integrity of the third-party should not be taken for granted. In this work we study a variety of authentication algorithms for selection and aggregation queries over sliding windows. Our algorithms enable the end-users to prove that the results provided by the third-party are correct, i.e., equal to the results that would have been computed by the original provider. Our solutions are based on Merkle hash trees over a forest of space partitioning data structures, and try to leverage key features, like update, query, signing, and authentication costs. We present detailed theoretical analysis for our solutions and empirically evaluate the proposed techniques.
17450841
An information concierge for the Web
WWW Information Collection, Collaging and Programming (WICCAP) system is a software system for the generation of logical views of web resources, and the extraction of desired information in the form of a structured document. It is designed to enable people to obtain information of interests in a simple and effective manner as well as to make information from the WWW accessible to applications so as to afford automation, inter-operation and Web-awareness among services. A key factor in making this system useful in practice is that it provides tools to automate and facilitate the process of constructing logical representation of websites, to identify and define information of interest, and to retrieving them. In this paper we present the design of the WICCAP system and its two main components, namely Mapping Wizard and Network Extraction Agent.
11230966
Robust Aggregation in Sensor Networks
In the emerging area of sensor-based systems, a significant challenge is to develop scalable, fault-tolerant methods to extract useful information from the data the sensors collect. An approach to this data management problem is the use of sensor “database” systems, which allow users to perform aggregation queries on the readings of a sensor network. Due to power and range constraints, centralized approaches are generally impractical, so most systems use in-network aggregation to reduce network traffic. However, these aggregation strategies become bandwidthintensive when combined with the fault-tolerant, multi-path routing methods often used in these environments. In order to avoid this expense, we investigate the use of approximate in-network aggregation using small sketches and we survey robust and scalable methods for computing duplicate-sensitive aggregates.
1808525
A Compiler-Based Approach to Data Security
With the proliferation of personal electronic devices and embedded systems, personal and financial data is more easily accessible. As a consequence, we also observe a proliferation of techniques that attempt to illegally access sensitive data without proper authorization. Due to the severe financial and social ramifications of such data leakage, the need for secure memory has become critical. However, working with secure memories can have performance, power, and code size overheads since accessing a secure memory involves additional overheads for encryption/decryption and/or password checks. In addition, an application code may need to be restructured to work under such a memory system. In this paper, we propose a compiler-directed strategy to generate code for a secure memory based embedded architecture. The idea is to let the programmer mark certain data elements, called the seed elements, as secure (i.e., need to be stored in secure memory), and let the compiler determine the remaining secure elements automatically. We also address the problem of code size increase due to our strategy. The experimental results obtained through simulations clearly show that the proposed approach is effective in reducing the total secure memory size. The results also indicate that it is possible to reduce the resulting code size increase by clustering accesses to secure memory.
4657376
Traffic Management
Quality of service in network communication is mainly assured by traffic management consisting in a variety of protocols and mechanisms whose role is to prevent the network from being congested. Traffic management has been a very active area of research for two decades following the conception of packetswitched integrated services networks, such as the Internet. This chapter provides samples of the state of the art in traffic management. It includes contributions on traffic theory, traffic and service models, quality monitoring, as well as traffic control and measurements. M. Smirnov et al. (Eds.): COST 263 Final Report, LNCS 2856, pp. 10–79, 2003. c © Springer-Verlag Berlin Heidelberg 2003 Traffic Management 11
1528533
Application, Network and Link Layer Measurements of Streaming Video over a Wireless Campus Network
The growth of wireless LANs has brought the expectation for high-bitrate streaming video to wireless PCs. However, it remains unknown how to best adapt video to wireless channel characteristics as they degrade. This paper presents results from experiments that stream commercial video over a wireless campus network and analyze performance across application, network and wireless link layers. Some of the key findings include: 1) Wireless LANs make it difficult for streaming video to gracefully degrade as network performance decreases; 2) Video streams with multiple encoding levels can more readily adapt to degraded wireless network conditions than can clips with a single encoding level; 3) Under degraded wireless network conditions, TCP streaming can provide higher video frame rates than can UDP streaming, but TCP streaming will often result in significantly longer playout durations than will UDP streaming; 4) Current techniques used by streaming media systems to determine effective capacity over wireless LAN are inadequate, resulting in streaming target bitrates significantly higher than can be effectively supported by the wireless network.
9337355
Weather forecasting: predicting performance for streaming video over wireless LANs
The growth of wireless LANs has brought the expectation for high-bitrate streaming video to wireless PCs. However, it remains unclear how wireless channel characteristics impact the quality of streaming video sent over wireless LANs. This paper presents results from experiments that stream commercial video over a wireless campus network. By analyzing the streaming video quality and capturing wireless LAN characteristics across network and wireless link layers, "weather forecasts" are created such that selected wireless LAN performance indicators might be used to predict the streaming video quality. Furthermore, a quantified measurement of accuracy is presented to evaluate the effectiveness of individual weather forecasts. The paper evaluates six distinct weather forecasts four different streaming configurations including TCP and UDP streaming, and single and multiple-level encoded videos. The results show that the wireless Received Signal Strength Indicator (RSSI) and average wireless link capacity are the most accurate indicators to predict the performance of streaming video over wireless LANs. The weather forecast philosophy can be beneficial for adapting video streaming in wireless LAN environments.
2691860
Design and Management of 3D Chip Multiprocessors Using Network-in-Memory
Long interconnects are becoming an increasingly important problem from both power and performance perspectives. This motivates designers to adopt on-chip network-based communication infrastructures and three-dimensional (3D) designs where multiple device layers are stacked together. Considering the trends towards increasing use of chip multiprocessing, it is timely to consider 3D chip multiprocessor design and memory networking issues, especially in the context of data management in large L2 caches. The overall goal of this paper is to study the challenges for L2 design and management in 3D chip multiprocessors. Our first contribution is to propose a router architecture and a topology design that makes use of a network architecture embedded into the L2 cache memory. Our second contribution is to demonstrate, through extensive experiments, that a 3D L2 memory architecture generates much better results than the conventional two-dimensional (2D) designs under different number of layers and vertical (inter-wafer) connections. In particular, our experiments show that a 3D architecture with no dynamic data migration generates better performance than a 2D architecture that employs data migration. This also helps reduce power consumption in L2 due to a reduced number of data movements