Emergent faithfulness to morphological and semantic heads in lexical blends

In many languages, sounds in certain "privileged" positions preserve marked structure which is eliminated elsewhere (Positional Faithfulness, Beckman 1998).  This paper presents new corpus and experimental evidence that faithfulness to main-stress location and segmental content of morpho-semantic heads emerges in English blends. The study compared right-headed (subordinating) blends, like motor + hotel -> motel (a kind of hotel) with coordinating blends like spoon + fork -> spork (equally spoon and fork).Stress: Analysis of 1095 blends from Thurner (1993) found that right-headed blends were more faithful to stress location of the second source word than were coordinating blends.  Given source words with conflicting stress (e.g., FLOUNder + sarDINE), participants preferentially matched the blend that preserved second-word stress (flounDINE) to a right-headed definition.Segmental content: When source-word length was controlled, segments from right-headed blends were more likely to survive than those from coordinating blends.  Given source words that could be spliced at two points (e.g., flaMiNGo + MoNGoose), participants preferentially matched the one that preserved more of the second word (flamongoose) to a right-headed definition.These results support the hypotheses that Positional Faithfulness constraints are universally available, that heads are a privileged position, and that blend phonology is sensitive to headedness

Taming the Devil: Techniques for Evaluating Anonymized Network Data

Anonymization plays a key role in enabling the public release of network datasets, and yet there are few, if any, techniques for evaluating the efficacy of network data anonymization techniques with respect to the privacy they afford. In fact, recent work suggests that many state-of-the-art anonymization techniques may leak more information than first thought. In this paper, we propose techniques for evaluating the anonymity of network data. Specifically, we simulate the behavior of an adversary whose goal is to deanonymize objects, such as hosts or web pages, within the network data. By doing so, we are able to quantify the anonymity of the data using information theoretic metrics, objectively compare the efficacy of anonymization techniques, and examine the impact of selective deanonymization on the anonymity of the data. Moreover, we provide several concrete applications of our approach on real network data in the hope of underscoring its usefulness to data publishers

Authentication via Keystroke Dynamics

In an effort to confront the challenges brought forward by the networking revolution of the past few years, we present improved techniques for authorized access to computer system resources and data. More than ever before, the Internet is changing computing as we know it. The possibilities of this global network seem limitless; unfortunately, with this global access comes increased chances of malicious attack and intrusion. Alternatives to traditional access control measures are in high demand. In what follows we present one such alternative : computer access via keystroke dynamics. A database of 42 profiles was constructed based on keystrokes patterns gathered from various users performing structured and unstructured tasks. We study the performance of a system for recognition of these users, and present a toolkit for analyzing system performance under varying criteria. Keywords: Biometrics, keystroke dynamics, pattern recognition, computer security. 1 Introduction Todays' society de..