Extending Complex Event Processing for Advanced Applications

Recently numerous emerging applications, ranging from on-line financial transactions, RFID based supply chain management, traffic monitoring to real-time object monitoring, generate high-volume event streams. To meet the needs of processing event data streams in real-time, Complex Event Processing technology (CEP) has been developed with the focus on detecting occurrences of particular composite patterns of events. By analyzing and constructing several real-world CEP applications, we found that CEP needs to be extended with advanced services beyond detecting pattern queries. We summarize these emerging needs in three orthogonal directions. First, for applications which require access to both streaming and stored data, we need to provide a clear semantics and efficient schedulers in the face of concurrent access and failures. Second, when a CEP system is deployed in a sensitive environment such as health care, we wish to mitigate possible privacy leaks. Third, when input events do not carry the identification of the object being monitored, we need to infer the probabilistic identification of events before feed them to a CEP engine. Therefore this dissertation discusses the construction of a framework for extending CEP to support these critical services. First, existing CEP technology is limited in its capability of reacting to opportunities and risks detected by pattern queries. We propose to tackle this unsolved problem by embedding active rule support within the CEP engine. The main challenge is to handle interactions between queries and reactions to queries in the high-volume stream execution. We hence introduce a novel stream-oriented transactional model along with a family of stream transaction scheduling algorithms that ensure the correctness of concurrent stream execution. And then we demonstrate the proposed technology by applying it to a real-world healthcare system and evaluate the stream transaction scheduling algorithms extensively using real-world workload. Second, we are the first to study the privacy implications of CEP systems. Specifically we consider how to suppress events on a stream to reduce the disclosure of sensitive patterns, while ensuring that nonsensitive patterns continue to be reported by the CEP engine. We formally define the problem of utility-maximizing event suppression for privacy preservation. We then design a suite of real-time solutions that eliminate private pattern matches while maximizing the overall utility. Our first solution optimally solves the problem at the event-type level. The second solution, at event-instance level, further optimizes the event-type level solution by exploiting runtime event distributions using advanced pattern match cardinality estimation techniques. Our experimental evaluation over both real-world and synthetic event streams shows that our algorithms are effective in maximizing utility yet still efficient enough to offer near real time system responsiveness. Third, we observe that in many real-world object monitoring applications where the CEP technology is adopted, not all sensed events carry the identification of the object whose action they report on, so called €œnon-ID-ed€� events. Such non-ID-ed events prevent us from performing object-based analytics, such as tracking, alerting and pattern matching. We propose a probabilistic inference framework to tackle this problem by inferring the missing object identification associated with an event. Specifically, as a foundation we design a time-varying graphic model to capture correspondences between sensed events and objects. Upon this model, we elaborate how to adapt the state-of-the-art Forward-backward inference algorithm to continuously infer probabilistic identifications for non-ID-ed events. More important, we propose a suite of strategies for optimizing the performance of inference. Our experimental results, using large-volume streams of a real-world health care application, demonstrate the accuracy, efficiency, and scalability of the proposed technology

Copyright norms and the problem of private censorship

This chapter "Copyright norms and the problem of private censorship" was originally published in Copyright and Free Speech: Comparative and International Analyses edited by Jonathan Griffiths and Uma Suthersanen, 2005, pp. 67-96. Link to OUP Catalog: https://global.oup.com/academic/product/copyright-and-free-speech-978019927604

Edge analytics in the internet of things

High-data-rate sensors are becoming ubiquitous in the Internet of Things. GigaSight is an Internet-scale repository of crowd-sourced video content that enforces privacy preferences and access controls. The architecture is a federated system of VM-based cloudlets that perform video analytics at the edge of the Internet

A Critical Review of Strategic Conflict Theory and Socio-political Instability Models

This paper provides a critical general overview of two strands of recent vast economic literature on social conflicts, namely strategic conflict theory and socio-political instability models. The first strand can be traced back to Haavelmo (1954) and has been further developed in a variety of ways by game theoretical models of rational conflict (Boulding, 1962; Schelling, 1963, Hirshleifer, 2001). Their goal is to understand threat power. A second version of conflict theory has been developed by the founders of the Public Choice School (Olson 1965, 1982; Tullock 1974, 1980; Stringham, 2005, 2007) in order to tackle genuine political violence. The main finding of this paper is that both strands of recent economic literature have not yet come to grips with social conflicts. The application of standard microeconomic assumptions to the field of "social conflicts" has resulted in reducing conflicts either to "rational conflicts"- a threat of conflict without any real clash - or "real self-interested private conflicts". In other words, economic theory has considered social protesters either as looters or lunatics, but never as a group of people struggling for a common cause.Strategic Conflict Theory, Socio-political instability models, Coase theorem, Appropriative activity, Social Conflicts

On the complexity of privacy-preserving complex event processing

Complex Event Processing (CEP) Systems are stream processing systems that monitor incoming event streams in search of user-specified event patterns. While CEP systems have been adopted in a variety of applications, the privacy implications of event pattern reporting mechanisms have yet to be studied — a stark contrast to the significant amount of attention that has been devoted to privacy for relational systems. In this paper we present a privacy problem that arises when the system must support desired patterns (those that should be reported if detected) and private patterns (those that should not be revealed). We formalize this problem, which we term privacy-preserving, utility maximizing CEP (PP-CEP), and analyze its complexity under various assumptions. Our results show that this is a rich problem to study and shed some light on the difficulty of developing algorithms that preserve utility without compromis-ing privacy

A thrips vector of tomato spotted wilt virus responds to tomato acylsugar chemical diversity with reduced oviposition and virus inoculation.

There is increasing evidence that acylsugars deter insect pests and plant virus vectors, including the western flower thrips (WFT), Frankliniella occidentalis (Pergande), vector of tomato spotted wilt virus (TSWV). Acylsugars are sugar-polyesters composed of saturated, un-saturated, and variously branched short and long chain fatty acids (FAs) esterified to a glucose (acylglucose) or sucrose (acylsucrose) moiety. We sought to understand how acylsucrose amount and composition of associated FA profiles interacted to mediate resistance to WFT oviposition and TSWV inoculation on tomato leaves. Towards this goal, we examined WFT oviposition and TSWV inoculation behavior on tomato lines bred to exude varying amounts of acylsucrose in association with diverse FA profiles. Our data show that as acylsucrose amounts increased, WFT egg-laying (oviposition) decreased and TSWV inoculation was suppressed. Western flower thrips also responded to FA profiles that included iC4, iC11, nC12 and nC10 FA. These findings support improving acylsugar-mediated resistance against WFT by breeding tomatoes exuding greater amounts of acylsucrose associated with specific FA profiles. We show that increasing acylsucrose amount output by type IV trichomes and selecting for particular FA profiles through advanced breeding profoundly affects WFT behavior in ways that benefit management of WFT as direct pests and as TSWV vectors

Towards trajectory anonymization: a generalization-based approach

Trajectory datasets are becoming popular due to the massive usage of GPS and locationbased services. In this paper, we address privacy issues regarding the identification of individuals in static trajectory datasets. We first adopt the notion of k-anonymity to trajectories and propose a novel generalization-based approach for anonymization of trajectories. We further show that releasing anonymized trajectories may still have some privacy leaks. Therefore we propose a randomization based reconstruction algorithm for releasing anonymized trajectory data and also present how the underlying techniques can be adapted to other anonymity standards. The experimental results on real and synthetic trajectory datasets show the effectiveness of the proposed techniques