Aaditeshwar Seth

Practical security for disconnected nodes

Endpoints in a delay tolerant network (DTN) [K. Fall, 2003] must deal with long periods of disconnection, large end-to-end communication delays, and opportunistic communication over intermittent links. This makes traditional security mechanisms inefficient and sometimes unsuitable. We study three specific problems that arise naturally in this context: initiation of a secure channel by a disconnected user using an opportunistic connection, mutual authentication over an opportunistic link, and protection of disconnected users from attacks initiated by compromised identities. We propose a security architecture for DTN based on hierarchical identity based cryptography (HIBC) that provides efficient and practical solutions to these problems.

Design and implementation of the KioskNet system

Rural Internet kiosks in developing countries can cost-effectively provide communication and e-governance services to the poorest sections of society. Unfortunately, a variety of technical and non-technical issues have caused most kiosk deployments to be unsustainable. KioskNet addresses the key technical problems underlying kiosk failure by using robust dasiamechanical backhaulpsila for connectivity, and by using low-cost and reliable kiosk controllers to support services delivered from one or more recycled PCs. KioskNet also addresses related issues such as security, user management, and log collection. In this paper, we describe the KioskNet system and outline its hardware, software, and security architectures. We describe a pilot deployment, and how we used lessons from this deployment to re-design our initial prototype.

Spatio-temporal and events based analysis of topic popularity in twitter

We present the first comprehensive characterization of the diffusion of ideas on Twitter, studying more than 5.96 million topics that include both popular and less popular topics. On a data set containing approximately 10 million users and a comprehensive scraping of 196 million tweets, we perform a rigorous temporal and spatial analysis, investigating the time-evolving properties of the subgraphs formed by the users discussing each topic. We focus on two different notions of the spatial: the network topology formed by follower-following links on Twitter, and the geospatial location of the users. We investigate the effect of initiators on the popularity of topics and find that users with a high number of followers have a strong impact on topic popularity. We deduce that topics become popular when disjoint clusters of users discussing them begin to merge and form one giant component that grows to cover a significant fraction of the network. Our geospatial analysis shows that highly popular topics are those that cross regional boundaries aggressively.

First impressions on the state of cellular data connectivity in India

Cellular penetration in India has grown tremendously in recent years and provides an opportunity to bridge the digital divide. However, there is little understanding of the state of cellular data connectivity in India. In this paper, we present first impressions on cellular data network performance in India. We present a measurement framework designed specifically for remote deployments and intermittent connectivity. Using this framework we evaluate three GSM based and one CDMA based cellular service providers through active measurements conducted at five rural, one semi-urban, and one urban locations. Through analysis of about 450 hours of measurement data collected over a 3-month period, we present the throughput and latency performance of cellular service providers and provide insights into the architecture of the service provider networks. Our analysis reveals aspects in cellular network design that interfere with standard protocols such as TCP, and suggests ways to improve performance.

Geolocating IP addresses in cellular data networks

Smartphones connected to cellular networks are increasingly being used to access Internet-based services. Using data collected from smartphones running a popular location-based application, we examine IP address allocation in cellular data networks, with emphasis on understanding the applicability of IP-based geolocation techniques. Our dataset has GPS-based location data for approximately 29,000 cellular network assigned IP addresses in 50 different countries. Using this dataset, we provide insights into the global deployment of cellular networks. For instance, we find that Network Address Translation (NAT) is commonplace in cellular networks. We also find several instances of service differentiation with operators assigning public IP addresses to some devices and private IP addresses to other devices. We also evaluate the error of geolocation databases when determining the position of the smartphones, and find that the error is 100km or more for approximately 70% of our measurements. Further, there is potential for errors at the scale of inter-country and inter-continent distances. We believe this dataset may be of value to the research community, and provide a subset of the dataset to the community.

Characterization of social media response to natural disasters

Online social networking websites such as Twitter and Facebook often serve a breaking-news role for natural disasters: these websites are among the first ones to mention the news, and because they are visited by millions of users regularly the websites also help communicate the news to a large mass of people. In this paper, we examine how news about these disasters spreads on the social network. In addition to this, we also examine the countries of the Tweeting users. We examine Twitter logs from the 2010 Philippines typhoon, the 2011 Brazil flood and the 2011 Japan earthquake. We find that although news about the disaster may be initiated in multiple places in the social network, it quickly finds a core community that is interested in the disaster, and has little chance to escape the community via social network links alone. We also find evidence that the world at large expresses concern about such largescale disasters, and not just countries geographically proximate to the epicenter of the disaster. Our analysis has implications for the design of fund raising campaigns through social networking websites.

Gurgaon idol: a singing competition over community radio and IVRS

In this paper, we describe several IVR usage and learnability insights that emerged from a singing competition held by a community radio station located in an urban community of low-income migrant workers. Our community radio station partner, Gurgaon Ki Awaaz, relies heavily on folk songs to build its content repository and develop a close rapport with its community; the station organized a competition called Gurgaon Idol, in which community members could call into an IVR system to record their songs, and vote to select the best songs. Our research yielded several insightful results on how to best solicit audio recordings on IVR, methods for crowdsourced voting on IVR, cultural preferences towards certain voting methods, how to help first-time IVR users learn the system, and practical tips to keep in mind when running such a competition. To the best of our knowledge, we are the first to explore usability of voice user interfaces for recording audio and for crowdsourced voting over IVR systems.

Towards the use of online social networks for efficient Internet content distribution

A large contributor to the growing Internet traffic is user generated content shared via online social networking websites. Our insight is that these websites can reveal valuable information that can be used in content delivery networks for better caching and pre-fetching performance. In this paper, we combine five different datasets from Twitter and other sources, and make several observations that can lead to helpful heuristics for better content placement. In particular, we study the temporal growth and decay, the geographical spread, and the social spread, of topics on the social network. We also describe in detail our methodologies for data collection, that can be useful for other researchers working in this space as well. In the future, we will use these observations to design heuristics for improved CDN performance.

PhonePeti: exploring the role of an answering machine system in a community radio station in India

Community Radio (CR) stations are short range radio stations that serve the local media needs of their surrounding communities. Community participation by way of helping set the station agenda, airing of peoples voices, and providing them with a local communication medium, is the defining feature of CR. But this philosophy has been hard to execute in practice because of logistical difficulties, with station staff not being able to reach out to a listenership-base spread across several hundreds of square kilometers. In todays context though, the high penetration of mobile phones has made it easier for listeners to participate in the running of radio stations, but the potential of telephony and radio integration has been exploited only minimally. In this paper, we explore the use of PhonePeti, an automated answering machine system in a community radio station based in Gurgaon, India. Answering machines are one of several ways to bring together the radio and telephony mediums. We show that this alone has the potential to considerably improve community engagement, but it also opens up many interesting issues on usability. Through quantitative and content analysis of 758 calls from 411 callers over two iterations of PhonePeti, combined with telephonic interviews of several callers, we show that significant challenges arise in being able to explain the concept of an answering machine to people who have not been exposed to a similar system in the past. We then show, through call statistics, that PhonePeti has increased community engagement by enabling more listeners to reach the station. Finally, we show that an answering machine system can be used to collect useful information from the callers.

Bayesian credibility modeling for personalized recommendation in participatory media

In this paper, we focus on the challenge that users face in processing messages on the web posted in participatory media settings, such as blogs It is desirable to recommend to users a restricted set of messages that may be most valuable to them Credibility of a message is an important criteria to judge its value In our approach, theories developed in sociology, political science and information science are used to design a model for evaluating the credibility of messages that is user-specific and that is sensitive to the social network in which the user resides To recommend new messages to users, we employ Bayesian learning, built on past user behaviour, integrating new concepts of context and completeness of messages inspired from the strength of weak ties hypothesis, from social network theory We are able to demonstrate that our method is effective in providing the most credible messages to users and significantly enhances the performance of collaborative filtering recommendation, through a user study on the digg.com dataset.