Paper Abstract and Keywords |
Presentation |
2019-10-03 14:05
[Invited Lecture]
Traffic Analysis Empowered by Machine Learning for Estimating Context of IoT Application Anan Sawabe, Takanori Iwai (NEC) |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
We have observed the emergence of various Internet of Things (IoT) use cases, such as remote robot control, over the last few years. Wireless network devices need to assign network resources to massive IoT devices connected to cloud/edge servers via the resource-constrained wireless networks. In order to provide stable IoT services, we assume that context aware traffic control at edge components will be used as an effective method to accommodate massive IoT devices. On the other hand, such traffic control requires estimating context from communication traffic in real time and accurately. In this lecture, we introduce a traffic analysis method empowered by machine learning, which enables the edge components to estimate context in the application layer by observing only traffic patterns in the network layer. First, we constructed multi-level probabilistic state transition model for modelling traffic patterns in each context. In addition, the model is trained regularly by computing state transition probabilities from observed traffic patterns. Finally, we show experimental results through two experimentation: state estimation of networked camera and activity estimation of smartphone user. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Encrypted traffic / Traffic analysis / States transition model / Estimation of application / / / / |
Reference Info. |
IEICE Tech. Rep. |
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Conference Information |
Committee |
MIKA |
Conference Date |
2019-10-02 - 2019-10-04 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Hokkaido Univ. |
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
Wireless Communication System, etc. |
Paper Information |
Registration To |
MIKA |
Conference Code |
2019-10-MIKA |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Traffic Analysis Empowered by Machine Learning for Estimating Context of IoT Application |
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Encrypted traffic |
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Traffic analysis |
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States transition model |
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Estimation of application |
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1st Author's Name |
Anan Sawabe |
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NEC Corporation (NEC) |
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Takanori Iwai |
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NEC Corporation (NEC) |
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Date Time |
2019-10-03 14:05:00 |
Presentation Time |
30 minutes |
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MIKA |
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