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Balanced Hop-Constrained Path Enumeration in Signed Directed Graphs
Hop-constrained path enumeration, which aims to output all the paths from two distinct vertices within the given hops, is one of the fundamental...
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Probabilistic Reverse Top-k Query on Probabilistic Data
Reverse top-k queries have received much attention from research communities. The result of reverse top-k queries is a set of objects, which had the...
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Device Characterization for Opportunistic Networks
When implementing opportunistic networks in real applications, not only connectivity problems need to be addressed, but also device restrictions....
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Simulation Tools for Opportunistic Networks
In this chapter, we start with an introduction to network simulators and especially to discrete event simulators. We explain how they work and what...
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Security in Opportunistic Networks
Security is of paramount importance in Opportunistic Networks (OppNets) due to its unique characteristics and operational challenges. OppNets are...
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Connectivity Technologies for Opportunistic Networks
This chapter explores the question of how to implement opportunistic networks in practice. The main part of this question considers the connectivity...
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Theoretical Models for Opportunistic Networks
In this chapter, we detail how to use theoretical modeling in opportunistic networks (OppNets) using mathematical and computational methods to...
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Data Dissemination in Opportunistic Networks
Data dissemination is the main research and implementation challenge in opportunistic networks. It addresses the question of how to forward data in a...
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Complexity-Approximation Trade-Offs in Exchange Mechanisms: AMMs vs. LOBs
This paper presents a general framework for the design and analysis of exchange mechanisms between two assets that unifies and enables comparisons...
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Eagle: Efficient Privacy Preserving Smart Contracts
The proliferation of Decentralised Finance (DeFi) and Decentralised Autonomous Organisations (DAO), which in current form are exposed to...
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Provably Avoiding Geographic Regions for Tor’s Onion Services
Tor, a peer-to-peer anonymous communication system, is one of the most effective tools in providing free and open communication online. Many of the...
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Smart Noise Detection for Statistical Disclosure Attacks
While anonymization systems like mix networks can provide privacy to their users by, e.g., hiding their communication relationships, several traffic...
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Synchronous Perfectly Secure Message Transmission with Optimal Asynchronous Fallback Guarantees
Secure message transmission (SMT) constitutes a fundamental network-layer building block for distributed protocols over incomplete networks. More...
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To Possess or Not to Possess - WhatsApp for Android Revisited with a Focus on Stickers
WhatsApp stickers are a popular hybrid of images and emoticons that can contain user-created content. Stickers are mostly sent for legitimate...
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On the Correlation Complexity of MPC with Cheater Identification
Composable protocols for Multi-Party Computation that provide security with Identifiable Abort against a dishonest majority require some form of...
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IFGNN: An Individual Fairness Awareness Model for Missing Sensitive Information Graphs
Graph neural networks (GNNs) provide an approach for analyzing complicated graph data for node, edge, and graph-level prediction tasks. However, due...
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Discovering Densest Subgraph over Heterogeneous Information Networks
Densest Subgraph Discovery (DSD) is a fundamental and challenging problem in the field of graph mining in recent years. The DSD aims to determine,...
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Influence Maximization Revisited
Influence Maximization (IM) has been extensively studied, which is to select a set of k seed users from a social network to maximize the expected...
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Maximum Fairness-Aware (k, r)-Core Identification in Large Graphs
Cohesive subgraph mining is a fundamental problem in attributed graph analysis. The k-core model has been widely used in many studies to measure the...
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Spatial Shrinkage Prior: A Probabilistic Approach to Model for Categorical Variables with Many Levels
One of the most commonly used methods to prevent overfitting and select relevant variables in regression models with many predictors is the penalized...