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POSTER: Revisiting anomaly detection system design philosophy
2013
Proceedings of the 2013 ACM SIGSAC conference on Computer & communications security - CCS '13
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We propose to randomize the feature space of an ADS such that it acts as a cryptographic key for the ADS and hence this randomized feature space is used by the ADS logic for detection of anomalies. ...
In information security e.g. cryptographic algorithms (such as DES), security is inherently dependent upon the key and not the algorithm, which makes these systems very robust by rendering evasion computationally ...
The detector uses maximum entropy estimation to develop the baseline distribution for the traffic classes. ...
doi:10.1145/2508859.2512529
dblp:conf/ccs/AshfaqAAK13
fatcat:vkigz7x2jfel5kochxyw7biubm
Variational Pedestrian Detection
[article]
2021
arXiv
pre-print
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assignment procedure in classical object detection methods. ...
In this paper, we develop a unique perspective of pedestrian detection as a variational inference problem. ...
Such variational pedestrian detector can learn to adaptively adjust the exploration strategy in matching space by itself, thus can handle heavy occlusion for pedestrian detection when only training with ...
arXiv:2104.12389v1
fatcat:2xkpxpp5dnbshkka65xpvf646m
Transmission and detection techniques for Internet of Bio-Nano Things applications with static and mobile molecular communication: A survey
2021
ITU Journal
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Furthermore, some experimental works in MC are presented to show realistic transmission and detection procedures available in practice. ...
Various transmission schemes, channel models, and detection techniques have been proposed for MC in recent years. ...
For decoding, maximum likelihood sequence detection with reduced channel memory was used in [62] . ...
doi:10.52953/gxez7259
fatcat:ngxeejwlpna4nonxbup2xyiqia
Flood damage assessment for cultivated lands: BVDA based adaptive thresholding and local statistics
2013
2013 6th International Conference on Recent Advances in Space Technologies (RAST)
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A total of six different SPOT 5 Panchromatic scenes acquired from May to July in 2011 over six different farming regions in Alberta and Saskatchewan, Canada were used in excess moisture damage assessment ...
The preliminary results show that using BVDA as a dynamic threshold method resulted in more consistent and accurate results than CFAR. ...
Gausian Maximum Likelihood Classifier as a CFAR detector A conventional method for target detection problems or binary classification problems is using CFAR detectors. ...
doi:10.1109/rast.2013.6581355
fatcat:ul6k4swbrjc3tfpdxpeb3up7xy
Blind adaptation of zero forcing projections and oblique pseudo-inverses for subspace detection and estimation when interference dominates noise
2002
IEEE Transactions on Signal Processing
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The results of this paper form a foundation for the rapid adaptation of receivers that are then used for detection and estimation. ...
When the strict identities of the theorem are approximated, then the detectors, estimators, and beamformers of this paper take on the form of adaptive subspace estimators, detectors, and Capon beamformers ...
In particular Dr. McWhorter helped us with the writing of Section VIII and suggested the normalization procedure used to obtain (44). ...
doi:10.1109/tsp.2002.805245
fatcat:mtb3ldumenguzg3a2axar37234
Accuracy improving guidelines for network anomaly detection systems
2009
Journal in Computer Virology
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Due to the rapidly evolving nature of network attacks, a considerable paradigm shift has taken place in the intrusion detection community. ...
Thus, in this paper, we firstly evaluate the performance of eight prominent network-based anomaly detectors under malicious portscan attacks to identify which NADSs perform better than others and why. ...
Maximum Entropy [21] Detector estimates the benign traffic distribution using maximum entropy estimation. ...
doi:10.1007/s11416-009-0133-5
fatcat:b2r6iv5hn5b2nlfcrj4quhd7y4
Specialization of a Generic Pedestrian Detector to a Specific Traffic Scene by the Sequential Monte-Carlo Filter and the Faster R-CNN
2017
Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications
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The main idea is to consider a deep detector as a function that generates realizations from the probability distribution of the pedestrian to be detected in the target. ...
Our contribution is to approximate this target probability distribution with a set of samples and an associated specialized deep detector estimated in a sequential Monte Carlo filter framework. ...
By using both region-proposal network for localization task and detector network together into one large network. ...
doi:10.5220/0006097900170023
dblp:conf/visapp/MhallaCGA17
fatcat:w24qp3ixhbcrrf74vsczm3bmo4
Characterization of Network Traffic Processes Under Adaptive Traffic Control Systems
2015
Transportation Research Procedia
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In such states the green time is not fully used. ...
on congested paths on the network, where paths are described as a sequence of detectors. ...
A subset of data used in this paper is available via Dublin's open data initiative at http: //www.dublinked.ie/. ...
doi:10.1016/j.trpro.2015.07.012
fatcat:ye5s6bpeoncu5ms4jh74de6ifq
Randomized data selection in detection with applications to distributed signal processing
2003
Proceedings of the IEEE
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Additionally, we suggest an adaptive detector that accounts for fluctuations in the selected data subset. ...
As an example of detection algorithms based upon randomized selection, we analyze a binary hypothesis testing problem, and determine several useful properties of detectors derived from the likelihood ratio ...
Any node in the network sees a random number of packets from an individual time slot. Thus, if necessary, any node in the network can use the detection algorithms we describe. ...
doi:10.1109/jproc.2003.814922
fatcat:i7simjardvaidndsl7toln6ioa
Maximum likelihood detection with intermittent observations
2009
2009 43rd Annual Conference on Information Sciences and Systems
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Finally, we present a simple scheme for adaptive detector design, to restore the original detection performance, with the cost of increasing the delay for detection. ...
In this paper, we formulate the decentralized detection problem with passive sensors and show that the optimal decision rule with packet loss is the likelihood ratio test. ...
ACKNOWLEDGMENT This work was supported in part by the National Science Foundation under Grant CNS-06152140, and NASA NRA NNX07AD12A. ...
doi:10.1109/ciss.2009.5054761
dblp:conf/ciss/TantawyKB09
fatcat:6bmfbe2z5rh4noe5sjmvpci76i
Real-Time Dynamic Network Anomaly Detection
2018
IEEE Intelligent Systems
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In this paper we introduce ReTiNA: a framework for streaming network anomaly detection. This procedure first detects anomalies in the correlation processes on individual edges of the network graph. ...
Methodology for statistical analysis of enterprise network data is becoming increasingly important in cyber-security. ...
We are grateful to Andy Thomas and ICT for providing the ICL Netflow data analysed in this paper. We are grateful for insightful reviews from the anonymous referees. ...
doi:10.1109/mis.2018.022441346
fatcat:7uo25pjeojdtjgat4k27uwnhzq
Robust multiuser detection in non-Gaussian channels
1999
IEEE Transactions on Signal Processing
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We also develop a subspace-based technique for blind adaptive implementation of the robust multiuser detectors, which requires only the signature waveform and the timing of the desired user in order to ...
The robust multiuser detection technique and its blind adaptive version can be applied to both synchronous and asynchronous CDMA channels. ...
The name "estimator" comes from "maximum likelihood type estimator" [13] since the choice of gives the ordinary maximum likelihood estimate. ...
doi:10.1109/78.740103
fatcat:hsop32gbrfeq5jbkvlkabmsoiq
Multiple changepoint detection in categorical data streams
2019
Statistics and computing
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The detector relies on the ability to adaptively monitor the category probabilities of a multinomial distribution, where temporal adaptivity is introduced using forgetting factors. ...
This method is then compared to sequential and nonsequential change detectors in a large simulation study which verifies the usefulness of our approach. ...
Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecomm ons.org/licenses/by/4.0/), which permits unrestricted use, distribution ...
doi:10.1007/s11222-019-09858-0
fatcat:icvjcsr4wndrniyrvz6r26wewm
Optimal performance for detection systems in wireless passive sensor networks
2009
2009 17th Mediterranean Conference on Control and Automation
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We design an optimal adaptive Neyman-Pearson detector, given the channel probabilistic model, by formulating and solving a constrained optimization problem. ...
In this paper, we formulate the detection performance, with non-ideal channels, in a probabilistic way, and compare with classical detection performance. ...
ACKNOWLEDGMENT This work was supported in part by the National Science Foundation under Grant CNS-06152140, and NASA NRA NNX07AD12A. ...
doi:10.1109/med.2009.5164671
fatcat:4fn4ug7ncrf75jqh4wmi57xv5a
Muon energy reconstruction in the ANTARES detector
2013
Nuclear Instruments and Methods in Physics Research Section A : Accelerators, Spectrometers, Detectors and Associated Equipment
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based on probability density functions and Artificial Neural Networks. ...
Currently, four energy reconstruction methods are implemented in the ANTARES data analysis framework, ranging from estimates based on photon counting and the total charge deposited in the detector to methods ...
In the Maximum Likelihood approach, these effects are described by an analytical PDF, which is used to derive the probability of photon detection P OM (E) at a certain OM. ...
doi:10.1016/j.nima.2012.12.109
fatcat:x5ujz7zjt5ebzkjwosqzn5xeca
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