A Study of Packet Sampling Methods for Protecting Sensors Deployed on Darknet

Countermeasures against darknet localisation attacks with packet sampling

Indonesian Journal of Electrical Engineering and Computer Science ◽

10.11591/ijeecs.v19.i2.pp1036-1047 ◽

2020 ◽

Vol 19 (2) ◽

pp. 1036

Author(s):

Masaki Narita ◽

Keisuke Kamada ◽

Kanayo Ogura ◽

Bhed Bahadur Bista ◽

Toyoo Takata

Keyword(s):

Sampling Method ◽

Sampling Methods ◽

The Internet ◽

Quality Of Information ◽

Internet Users ◽

Advanced Sampling ◽

Packet Sampling ◽

Improved Methods ◽

Actual Location

<p>The darknet monitoring system consists of network sensors widely deployed on the Internet to capture incoming unsolicited packets. A goal of this system is to analyse captured malicious packets and provide effective information to protect regular nonmalicious Internet users from malicious activities. To provide effective and reliable information, the location of sensors must be concealed. However, attackers launch localisation attacks to detect sensors in order to evade them. If the actual location of sensors is revealed, it is almost impossible to identify the latest tactics used by attackers. Thus, in a previous study, we proposed a packet sampling method, which samples incoming packets based on an attribute of the packet sender, to increase tolerance to a localisation attack and maintain the quality of information publicised by the system. We were successful in countering localisation attacks, which generate spikes on the publicised graph to detect a sensor. However, in some cases, with the previously proposed sampling method, spikes were clearly evident on the graph. Therefore, in this paper, we propose advanced sampling methods such that incoming packets are sampled based on multiple attributes of the packet sender. We present our improved methods and show promising evaluation results obtained via a simulation.</p>

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Estimating Network Flow Length Distributions via Bayesian Nonnegative Tensor Factorization

Wireless Communications and Mobile Computing ◽

10.1155/2019/8458016 ◽

2019 ◽

Vol 2019 ◽

pp. 1-17

Author(s):

Barış Kurt ◽

Ali Taylan Cemgil ◽

Güneş Karabulut Kurt ◽

Engin Zeydan

Keyword(s):

Network Flow ◽

High Speed ◽

Sampling Methods ◽

Matrix Multiplication ◽

Tensor Factorization ◽

Real World Data ◽

Data Set ◽

Flow Length ◽

Packet Sampling ◽

True Flow

In this paper, we develop a framework to estimate network flow length distributions in terms of the number of packets. We model the network flow length data as a three-way array with day-of-week, hour-of-day, and flow length as entities where we observe a count. In a high-speed network, only a sampled version of such an array can be observed and reconstructing the true flow statistics from fewer observations becomes a computational problem. We formulate the sampling process as matrix multiplication so that any sampling method can be used in our framework as long as its sampling probabilities are written in matrix form. We demonstrate our framework on a high-volume real-world data set collected from a mobile network provider with a random packet sampling and a flow-based packet sampling methods. We show that modeling the network data as a tensor improves estimations of the true flow length histogram in both sampling methods.

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Going Beyond 3-D Imaging: Automated 3-D Montaged image Analysis of Cytological Specimens

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100163873 ◽

1996 ◽

Vol 54 ◽

pp. 282-283

Author(s):

Badrinath Roysam ◽

Hakan Ancin ◽

Douglas E. Becker ◽

Robert W. Mackin ◽

Matthew M. Chestnut ◽

...

Keyword(s):

Image Analysis ◽

Structural Changes ◽

Sampling Methods ◽

Spatial Clustering ◽

Three Dimensional ◽

Field Of View ◽

Cell Counting ◽

Depth Of Field ◽

Tissue Cell ◽

Tissue Organization

This paper summarizes recent advances made by this group in the automated three-dimensional (3-D) image analysis of cytological specimens that are much thicker than the depth of field, and much wider than the field of view of the microscope. The imaging of thick samples is motivated by the need to sample large volumes of tissue rapidly, make more accurate measurements than possible with 2-D sampling, and also to perform analysis in a manner that preserves the relative locations and 3-D structures of the cells. The motivation to study specimens much wider than the field of view arises when measurements and insights at the tissue, rather than the cell level are needed.The term “analysis” indicates a activities ranging from cell counting, neuron tracing, cell morphometry, measurement of tracers, through characterization of large populations of cells with regard to higher-level tissue organization by detecting patterns such as 3-D spatial clustering, the presence of subpopulations, and their relationships to each other. Of even more interest are changes in these parameters as a function of development, and as a reaction to external stimuli. There is a widespread need to measure structural changes in tissue caused by toxins, physiologic states, biochemicals, aging, development, and electrochemical or physical stimuli. These agents could affect the number of cells per unit volume of tissue, cell volume and shape, and cause structural changes in individual cells, inter-connections, or subtle changes in higher-level tissue architecture. It is important to process large intact volumes of tissue to achieve adequate sampling and sensitivity to subtle changes. It is desirable to perform such studies rapidly, with utmost automation, and at minimal cost. Automated 3-D image analysis methods offer unique advantages and opportunities, without making simplifying assumptions of tissue uniformity, unlike random sampling methods such as stereology.12 Although stereological methods are known to be statistically unbiased, they may not be statistically efficient. Another disadvantage of sampling methods is the lack of full visual confirmation - an attractive feature of image analysis based methods.

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Pengaruh Tekanan Waktu, Locus Of Control , Tindakan Supervisi, Dan Materialitas Terhadap Penghentian Prematur Atas Prosedur Audit Studi Kasus Pada Kantor Akuntan Publik Daerah Istimewa Yogyakarta Tahun 2015

Kajian Bisnis STIE Widya Wiwaha ◽

10.32477/jkb.v24i1.216 ◽

2017 ◽

Vol 24 (1) ◽

pp. 35-53

Author(s):

Sulastiningsih Sulastiningsih ◽

Intan Ayu Candra

Keyword(s):

Locus Of Control ◽

Premature Termination ◽

Sampling Methods ◽

Time Pressure ◽

Linear Regression Analysis ◽

Multiple Linear Regression Analysis ◽

Test Reliability ◽

Friedman Test ◽

Independent Variables ◽

Public Accountant

The purpose of this study is to prove: (1) Time pressure, locus of control, the action of supervision and materiality partially affect the premature termination of the audit procedures (2) Time pressure, locus of control, supervision and materiality simultaneously affect the premature termination on the audit procedures. This research was conducted in Public Accountant firm in Yogyakarta region of which total 12 samples of KAP, by distributing 105 questionnaires, and 57 questionnaires were returned (54%). 34 of the returned questionnaires can be processed (34%). The samples in this study were determined by using non-probability sampling, one of purposive sampling methods. Data analysis consisted of: (1) validity test, reliability test and classical assumption. The result showed that the instruments used are quite reliable and valid (2) multiple linear regression analysis. The results are (a) Some of independent variables partially affect premature termination of the audit procedure, while the action of supervision does not influence premature termination of audit procedures (b) All independent variables influence simultaneously to the premature termination of the audit procedures (c) All independent variables showed that as much as 55% it affects on premature termination of the audit procedures, the rest of it are influenced by other variables. (3) Friedman Test. The result shows that there are order of priority of audit procedures being terminated.

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