Mr. Jin Feng Lin Profile

Jin Feng Lin

at Univ of Massachusetts Dartmouth

SPIE Involvement:

Author

Publications (1)

This will count as one of your downloads.

You will have access to both the presentation and article (if available).

DOWNLOAD NOW

This content is available for download via your institution's subscription. To access this item, please sign in to your personal account.

Email or Username Forgot your username?

Password Forgot your password?

Show

Keep me signed in

No SPIE account? Create an account

Proceedings Article | 12 April 2021 Poster + Presentation + Paper

Incremental learning-based jammer classification

Todd Morehouse, Charles Montes, Michael Bisbano, Jin Feng Lin, Ming Shao, Ruolin Zhou

Proceedings Volume 11746, 117462E (2021) https://doi.org/10.1117/12.2588003

KEYWORDS: Wireless communications, Software development, New and emerging technologies, Machine learning, Defense technologies, Defense and security

Read Abstract +

Jamming, whether intentional or not, threatens stable wireless communications by impeding a transmitted signal. New jamming technologies are regularly developed and deployed for use, which behave differently from their predecessors in order to bypass defense mechanisms. This makes existing jammer classifiers difficult to implement in fast changing dynamic environments, since human intervention is needed every time a new jamming technology is introduced. Improper maintenance will result in misclassification of the technology or allow jammers to pass through defenses. These scenarios will greatly reduce the performance of wireless networks and increase the response time for recovering from these attacks. As 5G continues to become more widespread, and other faster networks are released, wireless data rates will continue to grow. This furthers the need for a faster and more reliable jammer classifier, as shorter interruptions in service will cause even more data loss to occur. Incremental learning (IL) is a technique in machine learning that allows the introduction of new information to a previously trained network. Using IL, it is possible to create classifiers that can grow in number of classes without the need to retrain a new network from nothing. This allows remote devices to learn to adapt in dynamic environments with far lower memory cost. In this paper, we developed an IL-based jammer classifier using software defined radio (SDR) to detect when a jammer is present and classify the type and learn to classify new technologies when the type has not been encountered before.

My Library

You currently do not have any folders to save your paper to! Create a new folder below.

Folder Name

Folder Description

View contact details

UPDATE YOUR PROFILE

Is this your profile? Update it now.

Sign into your SPIE.org account

Don’t have a profile and want one?

Create an account on SPIE.org

Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks. You are receiving this notice because your organization may not have SPIE eBooks access.*

*Shibboleth/Open Athens users─please sign in to access your institution's subscriptions.

To obtain this item, you may purchase the complete book in print or electronic format on SPIE.org.

ORGANIZATIONAL
Sign in with credentials provided by your organization.

Organizational Username

Organizational Password

Show/Hide Password

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members:

Non-members: ADD TO CART

Keywords/Phrases

Search In:

Publication Years