ppxscal/embedding_network huggingface dataset:
Backtracking Algorithmic Complexity Attacks against a NIDS
Authors: Randy Smith, Cristian Estan, Somesh Jha
Venue: Proceedings of the 22nd Annual Computer Security Applications Conference (2006)

Network Intrusion Detection Systems (NIDS) have become crucial to securing modern networks. To be effective, a NIDS must be able to counter evasion attempts and operate at or near wire-speed. Failure to do so allows malicious packets to slip through a NIDS undetected. In this paper, we explore NIDS evasion through algorithmic complexity attacks. We present a highly effective attack against the Snort NIDS, and we provide a practical algorithmic solution that successfully thwarts the attack. This attack exploits the behavior of rule matching, yielding inspection times that are up to 1.5 million times slower than that of benign packets. Our analysis shows that this attack is applicable to many rules in Snort's ruleset, rendering vulnerable the thousands of networks protected by it. Our countermeasure confines the inspection time to within one order of magnitude of benign packets. Experimental results using a live system show that an attacker needs only 4.0 kbps of bandwidth to perpetually disable an unmodified NIDS, whereas all intrusions are detected when our countermeasure is used.
How to wring a table dry: entropy compression of relations and querying of compressed relations
Authors: Vijayshankar Raman, Garret Swart
Venue: Proceedings of the 32nd international conference on Very large data bases (2006)

We present a method to compress relations close to their entropy while still allowing efficient queries. Column values are encoded into variable length codes to exploit skew in their frequencies. The codes in each tuple are concatenated and the resulting tuplecodes are sorted and delta-coded to exploit the lack of ordering in a relation. Correlation is exploited either by co-coding correlated columns, or by using a sort order that leverages the correlation. We prove that this method leads to near-optimal compression (within 4.3 bits/tuple of entropy), and in practice, we obtain up to a 40 fold compression ratio on vertical partitions tuned for TPC-H queries.We also describe initial investigations into efficient querying over compressed data. We present a novel Huffman coding scheme, called segregated coding, that allows range and equality predicates on compressed data, without accessing the full dictionary. We also exploit the delta coding to speed up scans, by reusing computations performed on nearly identical records. Initial results from a prototype suggest that with these optimizations, we can efficiently scan, tokenize and apply predicates on compressed relations.
Sensor Fusion Using Dynamic Bayesian Networks in Livestock Production Buildings
Authors: Jens A. Hansen, Thomas D. Nielsen, Henrik Schioler
Venue: Proceedings of the International Conference on Computational Inteligence for Modelling Control and Automation and International Conference on Intelligent Agents Web Technologies and International Commerce (2006)

The climate in modern livestock production buildings is controlled using a simple state controller. State controllers are typically not equipped to handle abnormal situations, e.g. sensors providing false or no readings, and they may therefore produce malformed climate control signals which may have severe consequences for the livestock. To make the system more robust, a sensor fusion system can be used to combine the different sensor readings and thereby pro- duce a more reliable estimate of the climate state. A dy- namic Bayesian network (DBN) model is constructed for this purpose. The model is tested in an online setup in a climate laboratory, where realtime behavior is archived by using the Boyen & Koller approximate inference algorithm. Preliminary experimental results show that the proposed model provides a promising framework for sensor fusion in livestock buildings.
Centralized Modular Diagnosis and the Phenomenon of Coupling
Authors: E. García Moreno, A. Correcher Salvador, F. Morant Anglada, E. Quiles Cucarella, R. Blasco Giménez
Venue: Discrete Event Dynamic Systems (2006)

This paper studies modular decomposition as an approach for failure diagnosis based on Discrete Event Systems. This paper also analyses the problem of coupling produced in the implementation of centralized modular diagnosers, as coupled diagnosers cannot carry out their own diagnosis task, when there is a failure in another subsystem sharing a common energy or material flow. In addition, we propose a method to avoid diagnoser coupling, by means of decoupling functions using non-local information with respect to the coupled diagnoser and generated in the diagnoser where the failure has been isolated.
Trouble in Paradise: the Open Source Project PyPy, EU-Funding and Agile Practices
Authors: Beatrice During
Venue: Proceedings of the conference on AGILE 2006 (2006)

PyPy is an Open Source project, partly funded by the European Union, employing agile techniques evolved within the Python Community such as "sprint-driven development".The project started as a grass-root F/OSS effort in late 2002 and received EU-funding from December 2004 until November 2006. In this paper we will present the various influencing factors that creates the hybrid project process that is PyPy. These influencing factors are the F/OSS Python Community (climate of the community from which PyPy grew from), agile practices (such as the Python community evolved technique of "sprinting") and the EU funding practices (resource tracking and reporting) impacting the project. These influencing factors laid the foundation for the custommade project process that makes this unique hybrid project work. The main factor for driving this process is the skills of the team of core developers instigating the project. PyPy, with its open and transparent communication and collaborative work style, is again a proof that the best agile practice is the people factor.
Adaptive decision-making frameworks for dynamic multi-agent organizational change
Authors: Cheryl Martin, K. Suzanne Barber
Venue: Autonomous Agents and Multi-Agent Systems (2006)

This article presents a capability called Adaptive Decision-Making Frameworks (ADMF) and shows that it can result in significantly improved system performance across run-time situation changes in a multi-agent system. Specifically, ADMF can result in improved and more robust performance compared to the use of a single static decision-making framework (DMF). The ADMF capability allows agents to dynamically adapt the DMF in which they participate to fit their run-time situation as it changes. A DMF identifies a set of agents and specifies the distribution of decision-making control and the authority to assign subtasks among these agents as they determine how a goal or set of goals should be achieved. The ADMF capability is a form of organizational adaptation and differs from previous approaches to organizational adaptation and dynamic coordination in that it is the first to allow dynamic and explicit manipulation of these DMF characteristics at run-time as variables controlling agent behavior. The approach proposed for selecting DMFs at run-time parameterizes all domain-specific knowledge as characteristics of the agents' situation, so the approach is application-independent. The presented evaluation empirically shows that, for at least one multi-agent system, there is no one best DMF for multiple agents across run-time situational changes. Next, it motivates the further exploration of ADMF by showing that adapting DMFs to run-time variations in situation can result in improved overall system performance compared to static or random DMFs.
Replacing the Whois Protocol: IRIS and the IETF's CRISP Working Group
Authors: Andrew Newton
Venue: IEEE Internet Computing (2006)

The Nicname/Whois protocol has served well, but it remains unchanged since it was first published in the early 1980s, despite great change in the infrastructure and administration of the Internet. There is now more diversity with domain names and IP networks and associated contacts, as well as among the users submitting queries via Whois. The protocol is now so fragmented in terms of information flow and output that queries yield inconsistent results under current conditions. To address the needs of today's Internet, the IETF Cross Registry Internet Service Protocol (CRISP) working group is developing a new protocol, the Internet Registry Information Service (IRIS), to replace Whois.
A semi-definite programming approach to spatial decorrelation of independently polarized signals: Research Articles
Authors: Sven Nordebo, Abbas Mohammed
Venue: Wireless Communications Mobile Computing (2007)

A MIMO channel spatial decorrelation scheme based on semi-definite programming is introduced. As a particular application example, the paper addresses the potential gain of using multiple antennas and MIMO&ndash;OFDM techniques in order to increase the bandwidth efficiency in satellite communication systems. In particular, we consider the increase in channel capacity that is possible by exploiting satellite and polarization diversity. A fundamental case is studied with three satellite branches, and where each transmit&#x002F;receive antenna unit consists of six elemental electric and magnetic dipoles yielding six distinguishable parallel polarization channels per frequency. The numerical examples show that capacity increases linearly on a logarithmic signal-to-noise ratio scale where the constant of proportionality is the number of active parallel channels. In this respect, the simultaneous use of triple electric and triple magnetic dipoles has the potential to triple the capacity of an antenna system based on antenna units of single dipoles. Copyright &copy; 2006 John Wiley & Sons, Ltd.
Learning about and through Empirical Modelling
Authors: Russell Boyatt, Antony Harfield, Meurig Beynon
Venue: Proceedings of the Sixth IEEE International Conference on Advanced Learning Technologies (2006)

Empirical Modelling is a body of principles and tools that has been developed for the construction of interactive environments. Our previous research has indicated respects in which Empirical Modelling is intimately linked with learning activity of many different varieties. In this paper, we recount informal evidence in support of this claim that can be drawn from the assessment exercise attached to the "Introduction to Empirical Modelling" module offered in Computer Science at the University of Warwick. This assessment takes the form of an open-ended modelling and paper-writing exercise. Such an exercise is shown to be effective for learning about Empirical Modelling. It also promotes self-motivated exploration in unknown domains that is one of the key skills for life-long learning. The extent to which students not only learnt about Empirical Modelling, but also about the domain which they chose to model was unexpected. This leads us to suggest that Empirical Modelling could be effective in facilitating learning in other domains.
Tree amalgamation of graphs and tessellations of the Cantor sphere
Authors: Bojan Mohar
Venue: Journal of Combinatorial Theory Series B (2006)

A general method is described which gives rise to highly symmetric tessellations of the Cantor sphere, i.e., the 2-sphere with the Cantor set removed and endowed with the hyperbolic geometry with constant negative curvature. These tessellations correspond to almost vertex-transitive planar graphs with infinitely many ends. Their isometry groups have infinitely many ends and are free products with amalgamation of other planar groups, possibly one or two-ended or finite. It is conjectured that all vertex-transitive tessellations of the Cantor sphere can be obtained in this way.Although our amalgamation construction is rather simple, it gives rise to some extraordinary examples with properties that are far beyond expected. For example, for every integer k, there exists a k-connected vertex-transitive planar graph such that each vertex of this graph lies on at least k infinite faces. These examples disprove a conjecture of Bonnington and Watkins that there are no 5-connected vertex-transitive planargraphs with infinite faces. This also disproves another conjecture that in a 4-connected vertex-transitive planar graph each vertex lies on the boundary of at most one infinite face. Further examples give rise to counterexamples of some other conjectures of similar flavor.
Semiotics: mediation tools that can fill ELearning gaps
Authors: Ruth Gannon Cook
Venue: Proceedings of the 7th international conference on Learning sciences (2006)

ELearning is particularly susceptible to the transference of print documents to the web which often only provides text and information tidbits to students. But researchers in the learning sciences are finding dramatic improvements in student knowledge acquisition in web-based courses that include semiotic tools. The knowledge gaps that can exist between what students know and need to learn can be filled through the use of semiotic mediation tools. The research of this study looks at why these tools can provide an important bridge between the sociocultural knowledge already existent in students and instructional content and discusses lessons learned in the compilation of the research for this study.
Spreadsheet functional programming
Authors: David Wakeling
Venue: Journal of Functional Programming (2007)

The functional programming community has shown some interest in spreadsheets, but surprisingly no one seems to have considered making a standard spreadsheet, such as Excel, work with a standard functional programming language, such as Haskell. In this paper, we show one way that this can be done. Our hope is that by doing so, we might get spreadsheet programmers to give functional programming a try.
The Time Course of Visual Processing: From Early Perception to Decision-Making
Authors: Rufin Vanrullen, Simon J. Thorpe
Venue: Journal of Cognitive Neuroscience (2001)

Experiments investigating the mechanisms involved in visual processing often fail to separate low-level encoding mechanisms from higher-level behaviorally relevant ones. Using an alternating dual-task event-related potential (ERP) experimental paradigm (animals or vehicles categorization) where targets of one task are intermixed among distractors of the other, we show that visual categorization of a natural scene involves different mechanisms with different time courses: a perceptual, task-independent mechanism, followed by a task-related, category-independent process. Although average ERP responses reflect the visual category of the stimulus shortly after visual processing has begun (e.g. 75&ndash;80 msec), this difference is not correlated with the subject's behavior until 150 msec poststimulus.
Multi-Resolution Patch Tensor for Facial Expression Hallucination
Authors: Kui Jia, Shaogang Gong
Venue: Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1 (2006)

In this paper, we propose a sequential approach to hallucinate/ synthesize high-resolution images of multiple facial expressions. We propose an idea of multi-resolution tensor for super-resolution, and decompose facial expression images into small local patches. We build a multi-resolution patch tensor across different facial expressions. By unifying the identity parameters and learning the subspace mappings across different resolutions and expressions, we simplify the facial expression hallucination as a problem of parameter recovery in a patch tensor space. We further add a high-frequency component residue using nonparametric patch learning from high-resolution training data. We integrate the sequential statistical modelling into a Bayesian framework, so that given any low-resolution facial image of a single expression, we are able to synthesize multiple facial expression images in high-resolution. We show promising experimental results from both facial expression database and live video sequences.
Adaptive cleaning for RFID data streams
Authors: Shawn R. Jeffery, Minos Garofalakis, Michael J. Franklin
Venue: Proceedings of the 32nd international conference on Very large data bases (2006)

To compensate for the inherent unreliability of RFID data streams, most RFID middleware systems employ a "smoothing filter", a sliding-window aggregate that interpolates for lost readings. In this paper, we propose SMURF, the first declarative, adaptive smoothing filter for RFID data cleaning. SMURF models the unreliability of RFID readings by viewing RFID streams as a statistical sample of tags in the physical world, and exploits techniques grounded in sampling theory to drive its cleaning processes. Through the use of tools such as binomial sampling and π-estimators, SMURF continuously adapts the smoothing window size in a principled manner to provide accurate RFID data to applications.
Schema summarization
Authors: Cong Yu, H. V. Jagadish
Venue: Proceedings of the 32nd international conference on Very large data bases (2006)

Real database systems can often be very complex. A person wishing to access data from an unfamiliar database has the daunting task of understanding its schema before being able to pose a correct query against it. A schema summary can be of great help, providing a succinct overview of the entire schema, and making it possible to explore in depth only the relevant schema components.In this paper we formally define a schema summary and two desirable properties (in addition to minimizing size) of a summary: presenting important schema elements and achieving broad information coverage. We develop algorithms that allow us to automatically generate schema summaries based on these two goals. We further develop an objective metric for assessing the quality of a schema summary using query information. Experimental evaluation using this metric demonstrates that the summaries produced by our algorithms can significantly reduce the amount of user effort required to formulate a query through schema exploration.
Counting Crowded Moving Objects
Authors: Vincent Rabaud, Serge Belongie
Venue: Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1 (2006)

In its full generality, motion analysis of crowded objects necessitates recognition and segmentation of each moving entity. The difficulty of these tasks increases considerably with occlusions and therefore with crowding. When the objects are constrained to be of the same kind, however, partitioning of densely crowded semi-rigid objects can be accomplished by means of clustering tracked feature points. We base our approach on a highly parallelized version of the KLT tracker in order to process the video into a set of feature trajectories. While such a set of trajectories provides a substrate for motion analysis, their unequal lengths and fragmented nature present difficulties for subsequent processing. To address this, we propose a simple means of spatially and temporally conditioning the trajectories. Given this representation, we integrate it with a learned object descriptor to achieve a segmentation of the constituent motions. We present experimental results for the problem of estimating the number of moving objects in a dense crowd as a function of time.
New Method of Probability Density Estimation with Application to Mutual Information Based Image Registration
Authors: Ajit Rajwade, Arunava Banerjee, Anand Rangarajan
Venue: Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2 (2006)

We present a new, robust and computationally efficient method for estimating the probability density of the intensity values in an image. Our approach makes use of a continuous representation of the image and develops a relation between probability density at a particular intensity value and image gradients along the level sets at that value. Unlike traditional sample-based methods such as histograms, minimum spanning trees (MSTs), Parzen windows or mixture models, our technique expressly accounts for the relative ordering of the intensity values at different image locations and exploits the geometry of the image surface. Moreover, our method avoids the histogram binning problem and requires no critical parameter tuning. We extend the method to compute the joint density between two or more images. We apply our density estimation technique to the task of affine registration of 2D images using mutual information and show good results under high noise.
Exposing digital forgeries in scientific images
Authors: Hany Farid
Venue: Proceedings of the 8th workshop on Multimedia and security (2006)

A recent case of scientific fraud, involving manipulated images in a high-profile scientific publication, has sent shock- waves through the scientific community. By some measures, however, this case is not isolated - in at least one journal, it is estimated that as many as 20% of accepted manuscripts contain figures with inappropriate manipulations, and 1% with fraudulent manipulations. Several scientific editors are considering putting safeguards in place to help reduce these numbers. While sensible policy and awareness are certainly important, there is likely to be a need for computational techniques that automatically detect common forms of tampering. We describe three such techniques for detecting traces of tampering in scientific images. Specifically, image segmentation techniques are employed to detect image deletion, "healing", and duplication.
Security Extension for IEEE Std 1149.1
Authors: Franc Novak, Anton Biasizzo
Venue: Journal of Electronic Testing: Theory and Applications (2006)

A security extension for IEEE Std 1149.1 is proposed. It provides a locking mechanism which prevents unauthorised users to interfere via test bus with the system normal operation. The security extension requires small hardware overhead and allows full conformance with IEEE Std 1149.1.
Website optimization with web metrics: a case study
Authors: Birgit Weischedel, Eelko K. R. E. Huizingh
Venue: Proceedings of the 8th international conference on Electronic commerce: The new e-commerce: innovations for conquering current barriers, obstacles and limitations to conducting successful business on the internet (2006)

Web metrics are the measures that reflect how customers are using a website. Companies use these metrics for further improvement of their website. Although most companies today are engaged in website optimization, the actual use of web metrics is a relatively unexplored area. In this paper we address this topic by first reviewing the strengths and weaknesses of the most important source of web metrics (web logs) and then conducting an extensive case study. The literature review revealed a number of serious limitations to the collection and use of web log data. In the case study we interviewed both marketing and IT managers of a major US networking solutions company to explore how they use web metrics for website optimization projects and try to overcome weaknesses.We have found that the various data sources fulfil different purposes: clickstream data enable managers to answer 'when' and 'what' questions, customer surveys 'why' and 'how' questions, and external data to make competitor comparisons. Critical issues involve the lack of industry standards, the volume of data, and the need to supplement clickstream data with qualitative information. Managers highly regard web metrics and are eager to learn how to increase the use of this underutilized data source on online customer behaviour.