Elizabeth Belding

University of California, Santa Barbara

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Kevin C. Almeroth

University of California, Santa Barbara

Mai ElSherief

IT University of Copenhagen

Udit Paul

Seattle University

Ellen Zegura

Georgia Institute of Technology

Michael Nekrasov

University of California, Santa Barbara

Arpit Gupta

University of California, Santa Barbara

Morgan Vigil-Hayes

Northern Arizona University

Mariya Zheleva

University at Albany, State University of New York

Veljko Pejović

University of Ljubljana

Paul Schmitt

University of Hawaiʻi at Mānoa

Cooperative Institutions

University of California, Santa Barbara

University of Bristol

North Carolina State University

ETH Zurich

National Technical University of Athens

TU Dresden

University of Houston

Institute of Electrical and Electronics Engineers

Georgia Institute of Technology

University of California, Berkeley

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Malware in IEEE 802.11 Wireless Networks

Passive and Active Network Measurement (2008)

Brett Stone-Gross Christo Wilson Kevin C. Almeroth Elizabeth Belding Heather Zheng

Malicious software (malware) is one of the largest threats facing the Internet today. In recent years, malware has proliferated into wireless LANs as these networks have grown in popularity and prevalence. Yet the actual effects of malware-related network traffic in open wireless networks has never been examined. In this paper, we provide the first study to quantify the characteristics of malware on wireless LANs. We use data collected from the large wireless LAN deployment at the 67 th IETF meeting in San Diego, California as a case study. The measurements in this paper demonstrate that even a single infected host can have a dramatic impact on the performance of a wireless network.

Wireless WAN

10.1007/978-3-540-79232-1_23

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Citations (12)

Cell-Share: Opportunistic Use of Cellular Uplink to Augment Rural WiFi Mesh Networks

Ashish Sharma Elizabeth Belding Charles E. Perkins

The Internet has revolutionized communication, education, commerce and information access for its users worldwide. Unfortunately, the lack of copper/fiber infrastructure in the rural areas of the developing world has prevented a large majority of the human population from reaping the benefits of the Internet. While the number of mobile subscribers in the developing world has more than quadrupled in the last five years, the adoption of the Internet has shown a slow growth pattern. Recently, there has been a growing interest in providing Internet access to rural areas by means of inexpensive long distance WiFi mesh networks. However, the expensive Internet uplink and the difficulty in troubleshooting of WiFi mesh networks has hindered their large scale deployment. In this paper, we propose Cell-Share an architecture that leverages the explosive growth in cellular network penetration in the developing world to provide rural WiFi mesh networks with an on-demand scalable Internet uplink and troubleshooting back-channel using a collaborative mobile phone framework. We implement Cell-Share on Windows Mobile and Android platforms to demonstrate the feasibility of using the infrastructure of cellular data networks to provide a back-channel for network troubleshooting as well as capacity enhancement for rural mesh networks.

Trouble shooting

Mesh networking

10.1109/vetecf.2009.5379029

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Citations (4)

Resource estimation on wireless backhaul networks

International Wireless Internet Conference (2007)

Irfan Sheriff Prashanth Aravinda Kumar Acharya Elizabeth Belding

The increased usage of IEEE 802.11 wireless backhaul networks and the growing popularity of real time applications, such as VoIP, presents a challenging resource management problem due to the limited capacity of wireless networks. At high traffic volumes, measurements have shown that packet collisions and interference in 802.11 networks can lead to degraded performance to the extent that users experience unacceptably low throughput, which can ultimately lead to complete network breakdown [1]. A resource management framework that limits network flows can prevent network breakdown and improve the performance of throughput and delay-sensitive multimedia applications. To address this problem, we present a measurement-driven framework that leverages wireless characteristics for intelligent admission control in a static wireless network. Experiments on a 25 node wireless testbed show that the proposed scheme can enhance network performance such that the QoS requirements of real time applications, such as VoIP, can be met.

Backhaul (telecommunications)

Testbed

Wireless WAN

10.5555/1460047.1460061

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Citations (2)

Learning to Decipher Hate Symbols

arXiv (Cornell University) (2019)

Jing Qian Mai ElSherief Elizabeth Belding William Yang Wang

Existing computational models to understand hate speech typically frame the problem as a simple classification task, bypassing the understanding of hate symbols (e.g., 14 words, kigy) and their secret connotations. In this paper, we propose a novel task of deciphering hate symbols. To do this, we leverage the Urban Dictionary and collected a new, symbol-rich Twitter corpus of hate speech. We investigate neural network latent context models for deciphering hate symbols. More specifically, we study Sequence-to-Sequence models and show how they are able to crack the ciphers based on context. Furthermore, we propose a novel Variational Decipher and show how it can generalize better to unseen hate symbols in a more challenging testing setting.

DECIPHER

Leverage (statistics)

Symbol (formal)

Sequence (biology)

10.48550/arxiv.1904.02418

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Peer to Peer Hate: Hate Speech Instigators and Their Targets

arXiv (Cornell University) (2018)

Mai ElSherief Shirin Nilizadeh Dana Nguyen Giovanni Vigna Elizabeth Belding

While social media has become an empowering agent to individual voices and freedom of expression, it also facilitates anti-social behaviors including online harassment, cyberbullying, and hate speech. In this paper, we present the first comparative study of hate speech instigators and target users on Twitter. Through a multi-step classification process, we curate a comprehensive hate speech dataset capturing various types of hate. We study the distinctive characteristics of hate instigators and targets in terms of their profile self-presentation, activities, and online visibility. We find that hate instigators target more popular and high profile Twitter users, and that participating in hate speech can result in greater online visibility. We conduct a personality analysis of hate instigators and targets and show that both groups have eccentric personality facets that differ from the general Twitter population. Our results advance the state of the art of understanding online hate speech engagement.

Visibility

Harassment

10.48550/arxiv.1804.04649

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Citations (32)

Integrated Data Location in Multihop Wireless Networks

Irfan Sheriff Prashanth Aravinda Kumar Acharya Ashwin Sampath Ben Y. Zhao Elizabeth Belding

Multihop wireless networks are ideal as infrastructures for location-aware network applications, particularly for disaster recovery operations. However, one missing component is an efficient and scalable distributed data location service. Existing approaches impose significant communication overhead on the underlying wireless layer and generally limit the total number of locatable objects in a network. To address this problem, we present the integrated data location protocol (IDLP), which provides scalable location of a large number of objects by integrating compressed summaries of object signatures into the routing layer. We evaluate our approach using extensive simulations in Qualnet, as well as detailed measurements from a deployed AODV-implementation on the UCSB MeshNet testbed. Results show that IDLP maintains low communication overhead while efficiently locating up to a hundred objects per node.

Testbed

10.1109/comswa.2007.382588

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Citations (3)

The Bandwidth Divide: Obstacles to Efficient Broadband Adoption in Rural Sub-Saharan Africa

Veljko Pejović David L. Johnson Mariya Zheleva Elizabeth Belding Lisa Parks

International Journal of Communication 6 (2012), 2467–2491 1932–8036/20120005 Copyright © 2012 (Veljko Pejovic, David L. Johnson, Mariya Zheleva, Elizabeth Belding, Lisa Parks, Gertjan van Stam). Licensed under the Creative Commons Attribution Non-commercial No Derivatives (by-nc-nd). Available at http://ijoc.org.

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Citations (22)

A Study of MVNO Data Paths and Performance

Lecture notes in computer science (2016)

Paul Schmitt Morgan Vigil Elizabeth Belding

10.1007/978-3-319-30505-9_7

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Citations (14)

Characterizing Internet Access and Quality Inequities in California M-Lab Measurements

Udit Paul Jiamo Liu David Farias-llerenas Vivek Adarsh Arpit Gupta

It is well documented that, in the United States (U.S.), the availability of Internet access is related to several demographic attributes. Data collected through end user network diagnostic tools, such as the one provided by the Measurement Lab (M-Lab) Speed Test, allows the extension of prior work by exploring the relationship between the quality, as opposed to only the availability, of Internet access and demographic attributes of users of the platform. In this study, we use network measurements collected from the users of Speed Test by M-Lab and demographic data to characterize the relationship between the quality-of-service (QoS) metric download speed, and various critical demographic attributes, such as income, education level, and poverty. For brevity, we limit our focus to the state of California. For users of the M-Lab Speed Test, our study has the following key takeaways: (1) geographic type (urban/rural) and income level in an area have the most significant relationship to download speed; (2) average download speed in rural areas is 2.5 times lower than urban areas; (3) the COVID-19 pandemic had a varied impact on download speeds for different demographic attributes; and (4) the U.S. Federal Communication Commission’s (FCC’s) broadband speed data significantly over-represents the download speed for rural and low-income communities compared to what is recorded through Speed Test.

Download

10.1145/3530190.3534813

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Citations (9)

ICCCN 2021 Technical Program

Eleni Stai L. L. Narayana Mohit Agarwala Nikhil Karamchandani Chunmeng Zhong

10.1109/icccn52240.2021.9522177

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Citations (0)