Ph.D. Dissertation Proposal

User Identification in Wireless Networks

Christopher Swartz

9:00-11:00pm Friday, 27 February 2015, ITE 325B

Wireless communication using the 802.11 specifications is almost ubiquitous in daily life through an increasing variety of platforms. Traditional identification and authentication mechanisms employed for wireless communication commonly mimic physically connected devices and do not account for the broadcast nature of the medium. Both stationary and mobile devices that users interact with are regularly authenticated using a passphrase, pre-shared key, or an authentication server. Current research requires unfettered access to the user’s platform or information that is not normally volunteered.

We propose a mechanism to verify and validate the identity of 802.11 device users by applying machine learning algorithms. Existing work substantiates the application of machine learning for device identification using Commercial Off-The-Shelf (COTS) hardware and algorithms. This research seeks the refinement of and investigation of features relevant to identifying users. The approach is segmented into three main areas: a data ingest platform, processing, and classification.

Initial research proved that we can properly classify target devices with high precision, recall, and ROC using a sufficiently large real-world data set and a limited set of features. The primary contribution of this work is exploring the development of user identification through data observation. A combination of identifying new features, creating an online system, and limiting user interaction is the objective. We will create a prototype system and test the effectiveness and accuracy of it’s ability to properly identify users.

Committee: Drs. Joshi (Chair/Advisor), Nicholas, Younis, Finin, Pearce, Banerjee

Sign-up to Volunteer for URCAD Monday, April 20 - Thursday, April 23, 2015. Whether you have an hour or a day to give, we can use your help for a variety of tasks.

Please complete the form at the website provided below and direct any questions regarding volunteering to Janet McGlynn at mcglynn@umbc.edu.

Visual understanding of human actions

Dr. Hamed Pirsiavash

Postdoctoral Research Associate
Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology

12:00-1:00pm Friday, 27 February, 2015, ITE 325B

The aim in computer vision is to develop algorithms for computers to “see” the world as humans do. Central to this goal is understanding human behavior as an intelligent agent functioning in the visual world. For instance, in order for a robot to interact with us, it should understand our actions to produce the proper response. My work explores several directions towards computationally representing and understanding human actions.

In this talk, I will focus on detecting actions and judging their quality. First, I will describe simple grammars for modeling long-scale temporal structure in human actions. Real-world videos are typically composed of multiple action instances, where each instance is itself composed of sub-actions with variable durations and orderings. Our grammar models capture such hierarchical structure while admitting efficient, linear-time parsing algorithms for action detection. The second part of the talk will describe our algorithms for going beyond detecting actions to judging how well they are performed. Our learning-based framework provides feedback to the performer to improve the quality of his/her actions.

Host: Mohamed Younis

I am reclaiming my blackness. It’s been taken, twisted, and transformed into something I no longer recognized. It was deemed less than by the black kids, less than by the white kids, and left me navigating a space with an identity invalid.

My mom and I had a long “discussion” about the term Blackish. This began in reference to the popular TV show, but quickly went down a road that is still painful for me to revisit. In my mom’s opinion, she is black and I am blackish. I understood what she meant. I did not fit the stereotypical “black” mold. In fact, I fit the one she built for me. Predominantly white schools, a two parent household, sports, instruments, pets, private school, a car… the list goes on. These things were and continue to be my normal. Unfortunately, these things simultaneously made me “less than black”. How could that be?

My mom’s lived experiences are different. Her relationship with her dad is virtually nonexistent, she grew up in the inner city, her childhood was a low-income one. Is that what blackness is? Absentee dads? Poverty? The hood?

I’ve been ruminating on these thoughts this Black History Month. I’ve been thinking of my great-grandparents who didn’t establish themselves in a hood, but a neighborhood, with a car and a home they called their own. There were two parents and they worked hard to give their children a taste of middle-class life. They wore furs and diamonds, suits and church hats. They endured overt racism in ways I will never truly understand. Were they blackish too?

I am lost. I am exhausted at the thought of having to prove an identity that was handed to me. It covers every inch of my skin in a fantastic bronze hue. It dictates how strangers react to my face, my resume, my voice, my name. I am black. I am black first. I cannot be anything less.

“What do you say to the white kids when even the black kids say you’re not black enough for them?”

This post is an expansion of my statement in the I’m Not portion of the UMBC Women of Color Coalition’s campaign, “Telling Our Stories” project. For more information about the project and other stories, visit us on Facebook here.