the proceedings contain 11 papers. the topics discussed include: a new taxonomy of physical-layer network coding techniques in two way relay channel model with single antenna;an efficient convolution method to compute...
ISBN:
(纸本)9783903176416
the proceedings contain 11 papers. the topics discussed include: a new taxonomy of physical-layer network coding techniques in two way relay channel model with single antenna;an efficient convolution method to compute the stationary transition probabilities of the G/M/c model and its variants;surveying and analyzing privacy issues in contact tracing apps;multi-attribute monitoring for anomaly detection: a reinforcement learning approach based on unsupervised reward;ANGELA: HTTP adaptive streaming and edge computing simulator;an analytical model for a class of receiver-initiated mac protocols for energy harvesting wireless sensor networks;and impact analysis of greedy behavior attacks in vehicular ad hoc networks.
Video identification in encrypted network traffic has become a trending field in the research area for user behavior and Quality of Experience (QoE) analysis. However, the traditional methods of video identification h...
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ISBN:
(纸本)9798400702341
Video identification in encrypted network traffic has become a trending field in the research area for user behavior and Quality of Experience (QoE) analysis. However, the traditional methods of video identification have become ineffective withthe usage of Hypertext Transfer Protocol Secure (HTTPS). this paper presents a video identification method in encrypted network traffic using the number of packets received at the user's end in a second. For this purpose, video streams are captured, and feature is extracted from the video streams in the form of a series of Packets per Seconds (PPS). this feature is provided as input to a Convolutional Neural Network (CNN), which learns the pattern from the network traffic feature and successfully identifies the video even if the pattern differs from the training sample. the results show that PPS outperforms the other video identification techniques with a high accuracy of 90%. Moreover, the results show that CNN outperforms its counterpart regarding video identification with a 25% performance increase.
Web technologies are framed for the purpose of catering the need of ubiquitousness. there is no doubt that web applications are providing number of advantages to the masses, but everything comes with certain vulnerabi...
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As the need of investigative information is increasing at an exponential rate, extraction of relevant patterns out of huge amount of forensic data becomes more complex. Forensic pattern mining is a technique that deal...
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ISBN:
(纸本)9789811046032;9789811046025
As the need of investigative information is increasing at an exponential rate, extraction of relevant patterns out of huge amount of forensic data becomes more complex. Forensic pattern mining is a technique that deals with mining of the forensic patterns from forensic pattern warehouse in support of forensic investigation and analysis of the causes of occurrence of an event. But, sometimes those patterns do not provide certain analytical results and also may contain some noisy information withthem. An approach through which optimal patterns or reliable patterns are extracted from forensic pattern warehouse which strengthen the decisions-making process during investigations has been proposed in the paper.
Stock prediction is one of the exciting solutions in the world of computing. A stock prediction has a vital role in determining the pattern of stock movements over time. A successful price prediction model is profitab...
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Semantic trajectory pattern mining is becoming more and more important withthe efficient semantic enrichment process methods, which is the process of semantic annotation for spatiotemporal trajectories. Existing work...
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Facial expressions are part of human non-verbal communication. Automatically discriminating between genuine and acted emotion can help psychologists, judges, human-machine interface, and so on. the problems for resear...
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We explore the problem of learning and predicting popularity of articles from online news media. the only available information we exploit is the textual content of the articles and the information whether they became...
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ISBN:
(纸本)9783642202667
We explore the problem of learning and predicting popularity of articles from online news media. the only available information we exploit is the textual content of the articles and the information whether they became popular by users clicking on them or not. First we show that this problem cannot be solved satisfactorily in a naive way by modelling it as a binary classification problem. Next, we cast this problem as a ranking task of pairs of popular and non-popular articles and show that this approach can reach accuracy of up to 76%. Finally we show that prediction performance can improve if more content-based features are used. For all experiments, Support Vector Machines approaches are used.
this paper presents a systematic Differential Fault Analysis (DFA) method on Feistel ciphers, the outcome of which closely links to that of the theoretical cryptanalysis with provable security. For this purpose, we in...
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the proceedings contain 9 papers. the topics discussed include: DeltaFS: exascale file systems scale better without dedicated servers;taming the cloud object storage with MOS;experiences in using OS-level virtualizati...
ISBN:
(纸本)9781450340083
the proceedings contain 9 papers. the topics discussed include: DeltaFS: exascale file systems scale better without dedicated servers;taming the cloud object storage with MOS;experiences in using OS-level virtualization for block I/O;BAD-Check: bulk asynchronous distributed checkpointing;tackling the reproducibility problem in storage systems research with declarative experiment specifications;comparative I/O workload characterization of two leadership class storage clusters;heavy-tailed distribution of parallel I/O system response;pattern-driven parallel I/O tuning;and automatic and transparent I/O optimization with storage integrated application runtime support.
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