Towards Informative Statistical Flow Inversion

This is the accepted version of 'Towards Informative Statistical Flow Inversion', archived originally at arXiv:0705.1939v1 [cs.NI] 14 May 2007.A problem which has recently attracted research attention is that of estimating the distribution of flow sizes in internet traffic. On high traffic links it is sometimes impossible to record every packet. Researchers have approached the problem of estimating flow lengths from sampled packet data in two separate ways. Firstly, different sampling methodologies can be tried to more accurately measure the desired system parameters. One such method is the sample-and-hold method where, if a packet is sampled, all subsequent packets in that flow are sampled. Secondly, statistical methods can be used to ``invert'' the sampled data and produce an estimate of flow lengths from a sample. In this paper we propose, implement and test two variants on the sample-and-hold method. In addition we show how the sample-and-hold method can be inverted to get an estimation of the genuine distribution of flow sizes. Experiments are carried out on real network traces to compare standard packet sampling with three variants of sample-and-hold. The methods are compared for their ability to reconstruct the genuine distribution of flow sizes in the traffic

Configurable privacy-preserving automatic speech recognition

Voice assistive technologies have given rise to far-reaching privacy and security concerns. In this paper we investigate whether modular automatic speech recognition (ASR) can improve privacy in voice assistive systems by combining independently trained separation, recognition, and discretization modules to design configurable privacy-preserving ASR systems. We evaluate privacy concerns and the effects of applying various state-of-the-art techniques at each stage of the system, and report results using task-specific metrics (i.e. WER, ABX, and accuracy). We show that overlapping speech inputs to ASR systems present further privacy concerns, and how these may be mitigated using speech separation and optimization techniques. Our discretization module is shown to minimize paralinguistics privacy leakage from ASR acoustic models to levels commensurate with random guessing. We show that voice privacy can be configurable, and argue this presents new opportunities for privacy-preserving applications incorporating ASR

Beyond Node Degree: Evaluating AS Topology Models

This is the accepted version of 'Beyond Node Degree: Evaluating AS Topology Models', archived originally at arXiv:0807.2023v1 [cs.NI] 13 July 2008.Many models have been proposed to generate Internet Autonomous System (AS) topologies, most of which make structural assumptions about the AS graph. In this paper we compare AS topology generation models with several observed AS topologies. In contrast to most previous works, we avoid making assumptions about which topological properties are important to characterize the AS topology. Our analysis shows that, although matching degree-based properties, the existing AS topology generation models fail to capture the complexity of the local interconnection structure between ASs. Furthermore, we use BGP data from multiple vantage points to show that additional measurement locations significantly affect local structure properties, such as clustering and node centrality. Degree-based properties, however, are not notably affected by additional measurements locations. These observations are particularly valid in the core. The shortcomings of AS topology generation models stems from an underestimation of the complexity of the connectivity in the core caused by inappropriate use of BGP data

Anatomy of the Third-Party Web Tracking Ecosystem

The presence of third-party tracking on websites has become customary. However, our understanding of the third-party ecosystem is still very rudimentary. We examine third-party trackers from a geographical perspective, observing the third-party tracking ecosystem from 29 countries across the globe. When examining the data by region (North America, South America, Europe, East Asia, Middle East, and Oceania), we observe significant geographical variation between regions and countries within regions. We find trackers that focus on specific regions and countries, and some that are hosted in countries outside their expected target tracking domain. Given the differences in regulatory regimes between jurisdictions, we believe this analysis sheds light on the geographical properties of this ecosystem and on the problems that these may pose to our ability to track and manage the different data silos that now store personal data about us all

Efekat tri različite hrane na rast i preživljavanje larvi persijske jesetre (acipenser persicus)

A feeding experiment was conducted to evaluate growth and survival of Persian sturgeon larvae fed with live food (Nereis diversicolor and Daphnia spp.) and artificial diet. Diets were included: Diet 1: Dafnia (Dafnia magna), Diet 2: Nereis diversicolor worm; Diet 3: Mix of Daphnia (Daphnia spp.) (50%) and Nereis diversicolor (50%), Diet 4: Mix of Nereis diversicolor (50%) and concentrate food (50%) and Nereis diversicolor (50%); Diet 5: Mix of Daphnia spp. (33.33%) and Nereis diversicolor (33.33%) and concentrate food (33.33%). Persian sturgeon larvae were distinctly transferred to 15 tanks and fed for 15 days. For each treatment, 60 larvae were stocked into tanks. The total length and body weight of the fish were determined once before initiation of the experiment and at the end of the experimental period to assess their growth performance. Water quality parameters were recorded two times a day. There was significant difference (P0.05) were not found between diets 2 and 3 and also between diets 4 and 5. The value for BWI, PBWI, GR, DGI, SGR was higher in larvae fed mix of Nereis diversicolor and Daphnia spp. (diet 3) (p<0.05) and there was significant difference between all of groups. Except diet 3 there was no significant difference in the CF of fish fed the survey diets