VTechWorks
VTechWorks provides global access to Virginia Tech scholarship, including journal articles, books, theses, dissertations, conference papers, slide presentations, technical reports, working papers, administrative documents, videos, images, and more by faculty, students, and staff. Faculty can deposit items to VTechWorks from Elements, including journal articles covered by the University open access policy. Email vtechworks@vt.edu for help.
Open Access Policy
Virginia Tech's open access policy enables researchers to deposit the accepted version of scholarly articles with no embargo.
Theses and Dissertations
Virginia Tech was first in the world to require ETDs in 1997, and continues to add scans of older theses and dissertations.
Open Textbooks
More than 40 freely available and openly licensed textbooks are among our most downloaded items.
Communities in VTechWorks
Select a community to browse its collections.
Recent Submissions
Something that Hasn't Happened Yet
Wilson, Christopher (Virginia Tech, 2019-07-02)
Something that Hasn't Happened Yet is a collection of poems wherein the speaker traverses the world of family and relationships in an absurdist/meta-modern narrative. The collection also explores the form of poetry itself as well as creative nonfiction, recipes, and flash fiction as well. It is an attempt to assemble meaning through humor and the process of writing itself.
Someplace Else
Jernegan, Leslie Erin (Virginia Tech, 2019-07-02)
The novel Someplace Else scrutinizes spaces begging for examination—places of asphyxiation, of undiscussed power structures and violence—that do nothing to prepare those living within them to be their examiners. Through the lens of Lumi—a small-town Wisconsin adolescent on the verge of womanhood—the novel examines how childhood innocence is exemplified and threatened by the homes in which females are raised and raising themselves. Someplace Else serves as Lumi's avenue for figuring out how to put to words what exactly it is she is coming to understand, including her relationship with her hometown, how this space has affected her mother and sister, and how this space has affected these women's relationships with one another; through story, Lumi is deciphering ways to speak, to talk about her world and perhaps find a way out.
Matryoshka
Cohen, Tali Sharon (Virginia Tech, 2019-07-02)
Matryoshka is a poetry collection that inhabits the space between danger and desire. The poems are largely voice-driven and confessional, sprouting from a speaker who is somehow ruthlessly honest and deceptively evasive at the same time. She covets the domestic only to set it on fire. She runs for comfort and greets the comfortable with a knife. In the beginning of the collection, we see a speaker navigating her relationships with others. The poems in section one are seeped with intense longing and physical desire. In section two, we see the speaker turn her gaze inward and are met with a raw exploration of the self; a revelry of bad decision making, self-deception, and complicated sexuality. The collection leaves the reader curious and comfort-seeking.
Privacy-Preserving and Diversity-Aware Trust-based Team Formation in Online Social Networks
Mahajan, Yash; Cho, Jin-Hee; Chen, Ing-Ray (ACM, 2024-07)
As online social networks (OSNs) become more prevalent, a new paradigm for problem-solving through crowd-sourcing has emerged. By leveraging the OSN platforms, users can post a problem to be solved and then form a team to collaborate and solve the problem. A common concern in OSNs is how to form effective collaborative teams, as various tasks are completed through online collaborative networks. A team's diversity in expertise has received high attention to producing high team performance in developing team formation (TF) algorithms. However, the effect of team diversity on performance under different types of tasks has not been extensively studied. Another important issue is how to balance the need to preserve individuals' privacy with the need to maximize performance through active collaboration, as these two goals may conflict with each other. This research has not been actively studied in the literature. In this work, we develop a team formation (TF) algorithm in the context of OSNs that can maximize team performance and preserve team members' privacy under different types of tasks. Our proposed PRivAcy-Diversity-Aware Team Formation framework, called PRADA-TF, is based on trust relationships between users in OSNs where trust is measured based on a user's expertise and privacy preference levels. The PRADA-TF algorithm considers the team members' domain expertise, privacy preferences, and the team's expertise diversity in the process of team formation. Our approach employs game-theoretic principles Mechanism Design to motivate self-interested individuals within a team formation context, positioning the mechanism designer as the pivotal team leader responsible for assembling the team. We use two real-world datasets (i.e., Netscience and IMDb) to generate different semi-synthetic datasets for constructing trust networks using a belief model (i.e., Subjective Logic) and identifying trustworthy users as candidate team members. We evaluate the effectiveness of our proposed PRADA-TF scheme in four variants against three baseline methods in the literature. Our analysis focuses on three performance metrics for studying OSNs: social welfare, privacy loss, and team diversity.
Exploiting Update Leakage in Searchable Symmetric Encryption
Haltiwanger, Jacob; Hoang, Thang (ACM, 2024-06-19)
Dynamic Searchable Symmetric Encryption (DSSE) provides efficient techniques for securely searching and updating an encrypted database. However, efficient DSSE schemes leak some sensitive information to the server. Recent works have implemented forward and backward privacy as security properties to reduce the amount of information leaked during update operations. Many attacks have shown that leakage from search operations can be abused to compromise the privacy of client queries. However, the attack literature has not rigorously investigated techniques to abuse update leakage.
In this work, we investigate update leakage under DSSE schemes with forward and backward privacy from the perspective of a passive adversary. We propose two attacks based on a maximum likelihood estimation approach, the UFID Attack and the UF Attack, which target forward-private DSSE schemes with no backward privacy and Level II backward privacy, respectively. These are the first attacks to show that it is possible to leverage the frequency and contents of updates to recover client queries. We propose a variant of each attack which allows the update leakage to be combined with search pattern leakage to achieve higher accuracy. We evaluate our attacks against a real-world dataset and show that using update leakage can improve the accuracy of attacks against DSSE schemes, especially those without backward privacy.