A Mobile Botnet Model Based on Android System

Design of Mobile Botnet Based on Open Service

International Journal of Digital Crime and Forensics ◽

10.4018/ijdcf.2016070101 ◽

2016 ◽

Vol 8 (3) ◽

pp. 1-10 ◽

Cited By ~ 1

Author(s):

Fenggang Sun ◽

Lidong Zhai ◽

Yuejin Du ◽

Peng Wang ◽

Jun Li

Keyword(s):

Privacy Protection ◽

Rapid Development ◽

Communication Channels ◽

Mobile Network ◽

Security Threats ◽

Defense Strategy ◽

The Past ◽

Model Based ◽

Mobile Botnet ◽

Open Service

In recent years, botnet has become one of the most serious security threats to Internet. With the rapid development of mobile network and the popularity of smartphones, botnet began to spread to mobile platform. In order to counter mobile botnet, it is meaningful to study its constructive mechanism and reproduce it. In the past studies, researchers have designed several kinds of mobile botnet model based on various communication channels, such as SMS, Bluetooth, etc. This paper proposed a general mobile botnet model based on open service, and verified its feasibility by implementing it on Android platform. This paper also analyzed this model, and then proposed potential defense strategy in terms of its characteristic, which may provide reliable theoretical and technical support for future prevention and privacy protection.

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A Mobile Botnet Model Based on P2P Grid

Communications in Computer and Information Science - Creativity in Intelligent Technologies and Data Science ◽

10.1007/978-3-319-65551-2_44 ◽

2017 ◽

pp. 604-615 ◽

Cited By ~ 1

Author(s):

Marek Šimon ◽

Ladislav Huraj ◽

Marián Hosťovecký

Keyword(s):

Model Based ◽

Mobile Botnet

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Mobile Botnet Detection Model based on Retrospective Pattern Recognition

International Journal of Security and Its Applications ◽

10.14257/ijsia.2016.10.9.05 ◽

2016 ◽

Vol 10 (9) ◽

pp. 39-44 ◽

Cited By ~ 2

Author(s):

Meisam Eslahi ◽

Moslem Yousefi ◽

Maryam Var Naseri ◽

Y.M. Yussof ◽

N.M. Tahir ◽

...

Keyword(s):

Pattern Recognition ◽

Botnet Detection ◽

Detection Model ◽

Model Based ◽

Mobile Botnet

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Representation, abstraction, and simple-minded sophisticates

Behavioral and Brain Sciences ◽

10.1017/s0140525x19002942 ◽

2020 ◽

Vol 43 ◽

Author(s):

Peter Dayan

Keyword(s):

Decision Theory ◽

Predictive Coding ◽

Bayesian Decision Theory ◽

Bayesian Decision ◽

Model Based ◽

Model Free

Abstract Bayesian decision theory provides a simple formal elucidation of some of the ways that representation and representational abstraction are involved with, and exploit, both prediction and its rather distant cousin, predictive coding. Both model-free and model-based methods are involved.

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Quantitative Model-Based Image Analysis of NuMa Distribution Links Nuclear Organization with Cell Phenotype

Microscopy and Microanalysis ◽

10.1017/s1431927600028968 ◽

2001 ◽

Vol 7 (S2) ◽

pp. 578-579

Author(s):

David W. Knowles ◽

Sophie A. Lelièvre ◽

Carlos Ortiz de Solόrzano ◽

Stephen J. Lockett ◽

Mina J. Bissell ◽

...

Keyword(s):

Image Analysis ◽

Mammary Epithelial Cells ◽

Nuclear Organization ◽

Critical Role ◽

Quantitative Model ◽

Mammary Epithelial ◽

Cell Phenotype ◽

Proliferating Cells ◽

Mitotic Apparatus ◽

Model Based

The extracellular matrix (ECM) plays a critical role in directing cell behaviour and morphogenesis by regulating gene expression and nuclear organization. Using non-malignant (S1) human mammary epithelial cells (HMECs), it was previously shown that ECM-induced morphogenesis is accompanied by the redistribution of nuclear mitotic apparatus (NuMA) protein from a diffuse pattern in proliferating cells, to a multi-focal pattern as HMECs growth arrested and completed morphogenesis . A process taking 10 to 14 days.To further investigate the link between NuMA distribution and the growth stage of HMECs, we have investigated the distribution of NuMA in non-malignant S1 cells and their malignant, T4, counter-part using a novel model-based image analysis technique. This technique, based on a multi-scale Gaussian blur analysis (Figure 1), quantifies the size of punctate features in an image. Cells were cultured in the presence and absence of a reconstituted basement membrane (rBM) and imaged in 3D using confocal microscopy, for fluorescently labeled monoclonal antibodies to NuMA (fαNuMA) and fluorescently labeled total DNA.

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