Enabling Ubiquitous Database Access with XML

The client-server model has been successfully used to support a wide variety of families of services in the context of distributed systems. However, its server-centric nature makes it insensitive to fast changing client characteristics like terminal capabilities, network features, user preferences and evolving needs.To overcome this key limitation, we present an approach to enabling a server to adapt to different clients by making it programmable. A service-description language is used to program server adaptations. This language is designed as a domain-specific language to offer expressiveness and conciseness without compromising safety and security. We show that our approach makes servers adaptable without requiring the deployment of new protocols or server implementations.We illustrate our approach with the Internet Message Access Protocol (IMAP). An IMAP server is made programmable and a language, named Pems, is introduced to program robust variations of e-mail services.Our approach is uniformly used to develop a platform for multimedia communication services. This platform is composed of programmable servers for telephony services, e-mail processing, remote-document processing and stream adapters.

As academic libraries wrestle with how to provide more CD-ROMs and more online remote access to databases to keep pace with demands, they first need to evaluate the effectiveness of their current services. This study identifies students’ preferences and effectiveness using CD-ROMs and assesses the whole CD-ROM environment at one university library. A questionnaire was used to ask students their preferences, confidence levels, skills, and training in searching CD-ROM databases, as well as their satisfaction with CD-ROM services (see the appendix). Analyses of the data revealed that users are satisfied and prefer CD-ROM databases over the print indices. Although students indicated they are confident searching, they admitted that they need to know basic search strategies and that they want more personal assistance, hands-on training, and remote online access to databases. Moreover, how can academic libraries meet increasing user demands for more database access and services when their resources are not increasing?

This chapter discusses the application fundamentals of JDBC and the JDBC API, which include the application models and operational procedures of the JDBC API implemented in Java database applications. The JDBC API supports both two-tier and three-tier models for database accesses. In a two-tier model, a Java application or an applet can communicate directly with the database. In a two-tier client-server model, a Java application can directly communicate with the database. A client-server configuration is a special case of the two-tier model, where the database is located on another machine called the database server. In a three-tier client-server model, a data action request comes from an application GUI and is sent to the application server that can be considered a middle tier, and the application server that contains the JDBC API then sends Oracle statements to the database located on a database server.

We propose a personalized mobile search engine (PMSE) that captures the users' preferences in the form of concepts by mining their clickthrough data. Due to the importance of location information in mobile search, PMSE classifies these concepts into content concepts and location concepts. In addition, users' locations (positioned by GPS) are used to supplement the location concepts in PMSE. The user preferences are organized in an ontology-based, multifacet user profile, which are used to adapt a personalized ranking function for rank adaptation of future search results. To characterize the diversity of the concepts associated with a query and their relevances to the user's need, four entropies are introduced to balance the weights between the content and location facets. Based on the client-server model, we also present a detailed architecture and design for implementation of PMSE. In our design, the client collects and stores locally the clickthrough data to protect privacy, whereas heavy tasks such as concept extraction, training, and reranking are performed at the PMSE server. Moreover, we address the privacy issue by restricting the information in the user profile exposed to the PMSE server with two privacy parameters. We prototype PMSE on the Google Android platform. Experimental results show that PMSE significantly improves the precision comparing to the baseline.

This paper presents the design of an information- sharing based or server-assisted anti-phishing system. The system follows a client-server architecture and makes decision based on not only client side heuristics but also collective information from multiple clients. When visiting a web site, a client side proxy, installed as a plug-in to a browser, decides on the legitimacy of the web site based on a combination of white list, black list and heuristics. In case the client side proxy does not have sufficient information to make a clear judgment, it reports the suspicious site to a central server which has access to more complete and up to date information and is in a much better position than individual clients to make informed decisions. Our system is designed to counter against deceptive phishing as well as DNS-hijack attack.

Key-value stores (KVS) are a critical component of current data center infrastructure. They help address the extreme demand on data centers for high bandwidth, low latency access to large amounts of data. Due to their importance, many efforts have been made to improve their performance, which includes using FPGAs to offload some functionality. These efforts have been focused on improving the performance of the key-value store itself and reducing the load on the server running the KVS. However, with more FPGAs being deployed in the data centers by many cloud service providers, some use models that were not previously practical are becoming more realistic. In this work, we explore one such use case where we attempt to cache key-value entries at the network interface of the client server. We propose an FPGA design that is capable of caching the KVS data transparently to the KVS client application. The proposed solution is able to improve the application throughput while also reducing the network traffic generated by the KVS client. Also, as the proposed solution targets client servers that are typically shared by multiple clients, we discuss the importance of, and present our vision for, an FPGA design supporting multiple tenants.

In the last few years, the Message Queueing Telemetry Transport (MQTT) publish/subscribe protocol emerged as the de facto standard communication protocol for IoT, M2M and wireless sensor networks applications. Such popularity is mainly due to the extreme simplicity of the protocol at the client side, appropriate for low-cost and resource-constrained edge devices. Other nice features include a very low protocol overhead, ideal for limited bandwidth scenarios, the support of different Quality of Services (QoS) and many others. However, when an edge device is interested in performing processing operations over the data published by multiple clients, the use of MQTT may result in high network bandwidth usage and high energy consumption for the end devices, which is unacceptable in resource constrained scenarios. To overcome these issues, we propose in this paper MQTT+, which provides an enhanced protocol syntax and enrich the pub/sub broker with data filtering, processing and aggregation functionalities. MQTT+ is implemented starting from an open source MQTT broker and evaluated in different application scenarios.

Often clients (e.g., sensors, organizations) need to outsource joint computations that are based on some joint inputs to external untrusted servers. These computations often rely on the aggregation of data collected from multiple clients, while the clients want to guarantee that the results are correct and, thus, an output that can be publicly verified is required. However, important security and privacy challenges are raised, since clients may hold sensitive information. In this paper, we propose an approach, called verifiable additive homomorphic secret sharing (VAHSS), to achieve practical and provably secure aggregation of data, while allowing for the clients to protect their secret data and providing public verifiability i.e., everyone should be able to verify the correctness of the computed result. We propose three VAHSS constructions by combining an additive homomorphic secret sharing (HSS) scheme, for computing the sum of the clients’ secret inputs, and three different methods for achieving public verifiability, namely: (i) homomorphic collision-resistant hash functions; (ii) linear homomorphic signatures; as well as (iii) a threshold RSA signature scheme. In all three constructions, we provide a detailed correctness, security, and verifiability analysis and detailed experimental evaluations. Our results demonstrate the efficiency of our proposed constructions, especially from the client side.

The database server is a crucial bottleneck in traditional inference control architecture, as it enforces highly computation-intensive auditing for all users who query the protected database. As a result, most auditing methods, though rigorously studied, can never be implemented in practice for protecting largescale real-world database systems. To shift this paradigm, we propose a new inference control architecture that will entrust inference control to each users platform, provided that the platform is equipped with trusted computing technology. The trusted computing technology is designed to attest the state of a users platform to the database server, so as to assure the server that inference control could be enforced as expected. A generic protocol is proposed to formalize the interactions between the users platform and database server. Any existing inference control technique can work with our protocol, for which the security properties are formally proven. Since each user's platform enforces inference control for its own queries, our solution avoids the bottleneck.

The advancement in deep learning and edge computing has enabled intelligent mobile augmented reality (MAR) on resource limited mobile devices. However, today very few deep learning based MAR applications are applied in mobile devices because they are significantly energy-guzzling. In this paper, we design a user preference based energy-aware edge-based MAR system that enables MAR clients to dynamically change their configuration parameters, such as CPU frequency and computation model size, based on their user preferences, camera sampling rates, and available radio resources at the edge server. Our proposed dynamic MAR configuration adaptations can minimize the per frame energy consumption of multiple MAR clients without degrading their preferred MAR performance metrics, such as service latency and detection accuracy. To thoroughly analyze the interactions among MAR configuration parameters, user preferences, camera sampling rate, and per frame energy consumption, we propose, to the best of our knowledge, the first comprehensive analytical energy model for MAR clients. Based on the proposed analytical model, we develop a LEAF optimization algorithm to guide the MAR configuration adaptation and server radio resource allocation. Extensive evaluations are conducted to validate the performance of the proposed analytical model and LEAF algorithm.

Over the past decade, the Web has been transformed from a collection of static HTML pages to a complex, distributed computing platform, as evidenced of the success are sites such as Facebook and YouTube. This transformation has been enabled primarily by the continuous development of Web applications. Inevitably-due to the Internet architecture-Web applications must rely on the servers so as to process and store confidential or user sensitive information. However, anyone who gains access to the server whether is a curious administrator, an attacker or even the government may obtain the data stored on the server or the server's database. This paper investigates ways to improve client-side security, through encryption, to keep user data private in the face of threats of various Web server compromises. A Web Application for online-note taking named Note Locker has been developed for this purpose by combining not only multiple security mechanisms but also modern Web development techniques to achieve confidentiality, integrity and a high level of user experience. The application is developed using open source products and eliminates possible attacks such as eavesdropping, sniffing, wiretapping, man-in-the-middle, and session hijacking of sensitive data by encrypting the data on the client side before sent for storage on the server.

Provisioning of applications and value-added services for mobile (remote) monitoring and access to measurements data is supported by advanced communication models such as Internet of Things (IoT). IoT provides ubiquitous connectivity anytime and with anything. IoT applications are able to communicate with the environment, to receive information about its status, to exchange and use the information. Identification of generic functions for monitoring management, data acquisition, and access to information provides capabilities to define abstraction of transport technology and control protocols. This chapter presents an approach to design Web Services Application Programming Interfaces (API) for mobile monitoring and database access. Aspects of the Web Services implementation are discussed. A traffic model of Web Services application server is described formally. The Web Services application server handles traffic of different priorities generated by third party applications and by processes at the database server's side. The traffic model takes into account the distributed structure of the Web Services application server and applies mechanisms for adaptive admission control and load balancing to prevent overload. The utilization of Web Services application server is evaluated through simulation.

The paper covers heterogeneous multi-tier environments based on CORBA and Java. On the client side there is a Web browser that connects to the middle tier through CORBA-based Java applets. The business logic is decoupled from the database server on the third tier. Access to the databases is made through a JDBC interface or with embedded SQL. We present considerations about the use of different browsers and multiple ORBs, concentrating on interoperability issues. We explore the problems that have to be faced and give practical advice on how to make things work.

The increased use of location-aware devices, such as smartphones, generates a large amount of trajectory data. These data can be useful in several domains, like marketing, path modeling, localization of an epidemic focus, and so on. Nevertheless, since trajectory information contains personal mobility data, improper use or publication of trajectory data can threaten users’ privacy. It may reveal sensitive details like habits of behavior, religious beliefs, and sexual preferences. Therefore, many users might be unwilling to share their trajectory data without a previous anonymization process. Currently, several proposals to address this problem can be found in the literature. These solutions focus on anonymizing data before its publication, i.e., when they are already stored in the server database. Nevertheless, we argue that this approach gives the user no control about the information she shares. For this reason, we propose anonymizing data in the users’ mobile devices, before they are sent to a third party. This article extends our previous work which was, to the best of our knowledge, the first one to anonymize data at the client side, allowing users to select the amount and accuracy of shared data. In this article, we describe an improved version of the protocol, and we include the implementation together with an analysis of the results obtained after the simulation with real trajectory data.

We present SlicedPIR, a distributed Private Information Retrieval (PIR) protocol. SlicedPIR efficiently alleviates the server's compute bottleneck by offloading its load across multiple untrusted client machines. In contrast to prior work, SlicedPIR induces only a modest network overhead when the server offloads its work. It achieves those communication savings by exploiting the polynomial encoding of homomorphic encryption schemes typically used in PIR protocols. This encoding lets the server make novel use of the Number Theoretic Transform (NTT) to distribute points on the polynomials as ''slices'' of its data rather than the polynomials themselves. Using NTT allows the clients to process recursive PIR queries on their slices and return a succinct result to the server. The server efficiently verifies the clients' results by leveraging the Schwartz-Zippel lemma, which we adapt to the PIR use case. We show how to integrate SlicedPIR into a private messaging system, where clients write messages to the server's database and then use PIR to secretly query for messages from their friends. We implement a prototype of SlicedPIR and run experiments to show that it scales well with the number of clients and database size. Concretely, SlicedPIR achieves better performance and cuts network usage by over 95% compared to the state-of-the-art.