arXiv subjects

Sruti Bhagavatula

Publications and source records attributed to Sruti Bhagavatula.

5 recordsLinked to original sources

arXiv2026

Echoes in the Digital Abyss: Examining the Bubble Surrounding Security and Privacy Discourse in Social Networks

The dissemination of security and privacy education and guidance has been and still remains a challenge today. Social networks represent a potential avenue for sharing best practices, and experimentally they have been found to be effective at this task. While this appears promising, in the real world, security and privacy discussions would need to reach a wide range of people to be effective, avoiding the "interest bubbles" that commonly occur. We sought to understand how the communities surrounding security and privacy discourse operate, with a focus on what challenges need to be overcome to enable security and privacy discourse and advice to reach a wider audience. Indeed, we found that in-the-wild security and privacy discussions in social networks portray quite a different picture than in experimental settings. We built and analyzed the structure of a graph containing over 13 million users on the "X" platform (formerly "Twitter"), including 10,159 users who posted about security and privacy and their followers. Prior work has shown that users are more likely to consider information within social media if their like-minded social ties have visibly engaged with it. Our findings indicate that the users generating or participating in security discussions largely already belong to highly clustered technology and security- and privacy-related interest communities, which suggests that the people who are not already in the "inner circle" of relevant interests are likely not exposed effectively to these discussions. We conclude with reflections and ideas on increasing the reach of security and privacy guidance in social networks.

cs.CY↗

arXiv2021

What breach? Measuring online awareness of security incidents by studying real-world browsing behavior

Awareness about security and privacy risks is important for developing good security habits. Learning about real-world security incidents and data breaches can alert people to the ways in which their information is vulnerable online, thus playing a significant role in encouraging safe security behavior. This paper examines 1) how often people read about security incidents online, 2) of those people, whether and to what extent they follow up with an action, e.g., by trying to read more about the incident, and 3) what influences the likelihood that they will read about an incident and take some action. We study this by quantitatively examining real-world internet-browsing data from 303 participants. Our findings present a bleak view of awareness of security incidents. Only 16% of participants visited any web pages related to six widely publicized large-scale security incidents; few read about one even when an incident was likely to have affected them (e.g., the Equifax breach almost universally affected people with Equifax credit reports). We further found that more severe incidents as well as articles that constructively spoke about the incident inspired more action. We conclude with recommendations for specific future research and for enabling useful security incident information to reach more people.

cs.CR↗

arXiv2020

(How) Do people change their passwords after a breach?

To protect against misuse of passwords compromised in a breach, consumers should promptly change affected passwords and any similar passwords on other accounts. Ideally, affected companies should strongly encourage this behavior and have mechanisms in place to mitigate harm. In order to make recommendations to companies about how to help their users perform these and other security-enhancing actions after breaches, we must first have some understanding of the current effectiveness of companies' post-breach practices. To study the effectiveness of password-related breach notifications and practices enforced after a breach, we examine---based on real-world password data from 249 participants---whether and how constructively participants changed their passwords after a breach announcement. Of the 249 participants, 63 had accounts on breached domains; only 33% of the 63 changed their passwords and only 13% (of 63) did so within three months of the announcement. New passwords were on average 1.3x stronger than old passwords (when comparing log10-transformed strength), though most were weaker or of equal strength. Concerningly, new passwords were overall more similar to participants' other passwords, and participants rarely changed passwords on other sites even when these were the same or similar to their password on the breached domain. Our results highlight the need for more rigorous password-changing requirements following a breach and more effective breach notifications that deliver comprehensive advice.

cs.CR↗

arXiv2019

By the user, for the user: A user-centric approach to quantifying the privacy of websites

Third-party tracking is common on almost all commercially operated websites. Prior work has studied in detail the extent of third-party tracking on the web, detection of third-party trackers, and defending against third-party tracking. Existing research and tools have also attempted to inform web users of trackers and the extent of their privacy violations. However, existing tools do not take into account users' perceptions of and understanding of the extent of trackers on the web. Taking these factors into account is important for the usability of such tools so that users can be aware and protect themselves to a reasonable and necessary extent that aligns with their overall comfort with trackers. In this paper, we elicit user perceptions and preferences about different trackers on various websites through an online survey of 43 users. We use this data to bootstrap a privacy scoring system. This scoring system weights the usage of trackers and the dispersion of user data within a page to third parties, with the type of website being visited. Our work presents a proof-of-concept methodology and tool to calculate a user-centric privacy score with preliminary bootstrap user data. We conclude with concrete future directions.

cs.CY↗

arXiv2019

A General Framework for Adversarial Examples with Objectives

Images perturbed subtly to be misclassified by neural networks, called adversarial examples, have emerged as a technically deep challenge and an important concern for several application domains. Most research on adversarial examples takes as its only constraint that the perturbed images are similar to the originals. However, real-world application of these ideas often requires the examples to satisfy additional objectives, which are typically enforced through custom modifications of the perturbation process. In this paper, we propose adversarial generative nets (AGNs), a general methodology to train a generator neural network to emit adversarial examples satisfying desired objectives. We demonstrate the ability of AGNs to accommodate a wide range of objectives, including imprecise ones difficult to model, in two application domains. In particular, we demonstrate physical adversarial examples---eyeglass frames designed to fool face recognition---with better robustness, inconspicuousness, and scalability than previous approaches, as well as a new attack to fool a handwritten-digit classifier.

cs.CV↗