arXiv subjects

Florian Tschorsch

Publications and source records attributed to Florian Tschorsch.

33 records · Page 2Linked to original sources

arXiv2022

Passively Measuring IPFS Churn and Network Size

The InterPlanetary File System~(IPFS) is a popular decentralized peer-to-peer network for exchanging data. While there are many use cases for IPFS, the success of these use cases depends on the network. In this paper, we provide a passive measurement study of the IPFS network, investigating peer dynamics and curiosities of the network. With the help of our measurement, we estimate the network size and confirm the results of previous active measurement studies.

cs.NI↗

arXiv2022

On the Routing Convergence Delay in the Lightning Network

Nodes in the Lightning Network synchronise routing information through a gossip protocol that makes use of a staggered broadcast mechanism. In this work, we show that the convergence delay in the network is larger than what would be expected from the protocol's specification and that payment attempt failures caused by the delay are more frequent, the larger the delay is. To this end, we measure the convergence delay incurred in the network and analyse what its primary causes are. Moreover, we further investigate and confirm our findings through a time-discrete simulation of the Lightning Network gossip protocol. We explore the use of alternative gossip protocols as well as parameter variations of the current protocol and evaluate them by the resulting bandwidth usage and convergence delay. Our research shows that there are multiple ways of lowering the convergence delay, ranging from simple parameter changes to overhauling the entire protocol.

cs.NI↗

arXiv2022

IPFS and Friends: A Qualitative Comparison of Next Generation Peer-to-Peer Data Networks

Decentralized, distributed storage offers a way to reduce the impact of data silos as often fostered by centralized cloud storage. While the intentions of this trend are not new, the topic gained traction due to technological advancements, most notably blockchain networks. As a consequence, we observe that a new generation of peer-to-peer data networks emerges. In this survey paper, we therefore provide a technical overview of the next generation data networks. We use select data networks to introduce general concepts and to emphasize new developments. Specifically, we provide a deeper outline of the Interplanetary File System and a general overview of Swarm, the Hypercore Protocol, SAFE, Storj, and Arweave. We identify common building blocks and provide a qualitative comparison. From the overview, we derive future challenges and research goals concerning data networks.

cs.NI↗

arXiv2021

A QUIC(K) Way Through Your Firewall?

The QUIC protocol is a new approach to combine encryption and transport layer stream abstraction into one protocol to lower latency and improve security. However, the decision to encrypt transport layer functionality may limit the capabilities of firewalls to protect networks. To identify these limitations we created a test environment and analyzed generated QUIC traffic from the viewpoint of a middlebox. This paper shows that QUIC indeed exposes traditional stateful firewalls to UDP hole punching bypass attacks. On the contrary we show the robustness against censorship of QUIC through the encrypted transport layer design and analyze the capabilities to re-gain stateful tracking capabilities by deep packet inspection of the few exposed QUIC header fields.

cs.CR↗

arXiv2021

Towards Verifiable Mutability for Blockchains

Due to their immutable log of information, blockchains can be considered as a transparency-enhancing technology. The immutability, however, also introduces threats and challenges with respect to privacy laws and illegal content. Introducing a certain degree of mutability, which enables the possibility to store and remove information, can therefore increase the opportunities for blockchains. In this paper, we present a concept for a mutable blockchain structure. Our approach enables the removal of certain blocks, while maintaining the blockchain's verifiability property. Since our concept is agnostic to any consensus algorithms, it can be implemented with permissioned and permissionless blockchains.

cs.CR↗

arXiv2021

Modeling the Block Verification Time of Zcash

An important aspect of the propagation delay in blockchain networks is the block verification time, which is also responsible for the so-called verifier's dilemma. Models for the block verification time can help to understand and improve the verification process. Moreover, modeling the verification time is necessary for blockchain network simulations. In this paper, we present JOIST, a new model for the block verification time of Zcash. We identify computationally complex operations in the verification process of Zcash, and derive our model based on characteristic transaction features. We evaluate JOIST and show that the model is consistently more accurate than existing models, which consider the block size only.

cs.CR↗

arXiv2021

Operating Tor Relays at Universities: Experiences and Considerations

In today's digital society, the Tor network has become an indispensable tool for individuals to protect their privacy on the Internet. Operated by volunteers, relay servers constitute the core component of Tor and are used to geographically escape surveillance. It is therefore essential to have a large, yet diverse set of relays. In this work, we analyze the contribution of educational institutions to the Tor network and report on our experience of operating exit relays at a university. Taking Germany as an example (but arguing that the global situation is similar), we carry out a quantitative study and find that universities contribute negligible amounts of relays and bandwidth. Since many universities all over the world have excellent conditions that render them perfect places to host Tor (exit) relays, we encourage other interested people and institutions to join. To this end, we discuss and resolve common concerns and provide lessons learned.

cs.NI↗

arXiv2021

On the Impact of Attachment Strategies for Payment Channel Networks

Payment channel networks, such as Bitcoin's Lightning Network, promise to improve the scalability of blockchain systems by processing the majority of transactions off-chain. Due to the design, the positioning of nodes in the network topology is a highly influential factor regarding the experienced performance, costs, and fee revenue of network participants. As a consequence, today's Lightning Network is built around a small number of highly-connected hubs. Recent literature shows the centralizing tendencies to be incentive-compatible and at the same time detrimental to security and privacy. The choice of attachment strategies therefore becomes a crucial factor for the future of such systems. In this paper, we provide an empirical study on the (local and global) impact of various attachment strategies for payment channel networks. To this end, we introduce candidate strategies from the field of graph theory and analyze them with respect to their computational complexity as well as their repercussions for end users and service providers. Moreover, we evaluate their long-term impact on the network topology.

cs.NI↗

arXiv2020

Bernoulli Meets PBFT: Modeling BFT Protocols in the Presence of Dynamic Failures

The publication of the pivotal state machine replication protocol PBFT laid the foundation for a large body of BFT protocols. While many successors to PBFT have been developed, there is no general technique to compare these protocols under realistic network conditions such as unreliable links. In this paper, we introduce a probabilistic model for evaluating BFT protocols in the presence of dynamic link and crash failures. Based on modeling techniques from communication theory, the network state of replicas is captured and used to derive the success probability of the protocol execution. To this end, we examine the influence of link and crash failure rates as well as the number of replicas. The model is derived from the communication pattern, making it implementation-independent and facilitating an adaptation to other BFT protocols. The model is validated with a simulation of PBFT and BFT-SMaRt. Further, a comparison in protocol behavior of PBFT, Zyzzyva and SBFT is performed and critical failure thresholds are identified.e thresholds are identified.

cs.DC↗

arXiv2020

Every Query Counts: Analyzing the Privacy Loss of Exploratory Data Analyses

An exploratory data analysis is an essential step for every data analyst to gain insights, evaluate data quality and (if required) select a machine learning model for further processing. While privacy-preserving machine learning is on the rise, more often than not this initial analysis is not counted towards the privacy budget. In this paper, we quantify the privacy loss for basic statistical functions and highlight the importance of taking it into account when calculating the privacy-loss budget of a machine learning approach.

cs.LG↗

arXiv2020

Counting Down Thunder: Timing Attacks on Privacy in Payment Channel Networks

The Lightning Network is a scaling solution for Bitcoin that promises to enable rapid and private payment processing. In Lightning, multi-hop payments are secured by utilizing Hashed Time-Locked Contracts (HTLCs) and encrypted on the network layer by an onion routing scheme to avoid information leakage to intermediate nodes. In this work, we however show that the privacy guarantees of the Lightning Network may be subverted by an on-path adversary conducting timing attacks on the HTLC state negotiation messages. To this end, we provide estimators that enable an adversary to reduce the anonymity set and infer the likeliest payment endpoints. We developed a proof-of-concept measurement node that shows the feasibility of attaining time differences and evaluate the adversarial success in model-based network simulations. We find that controlling a small number malicious nodes is sufficient to observe a large share of all payments, emphasizing the relevance of the on-path adversary model. Moreover, we show that adversaries of different magnitudes could employ timing-based attacks to deanonymize payment endpoints with high precision and recall.

cs.NI↗

arXiv2020

PredicTor: Predictive Congestion Control for the Tor Network

In the Tor network, anonymity is achieved through a multi-layered architecture, which comes at the cost of a complex network. Scheduling data in this network is a challenging task and the current approach shows to be incapable of avoiding network congestion and allocating fair data rates. We propose PredicTor, a distributed model predictive control approach, to tackle these challenges. PredicTor is designed to schedule incoming and outgoing data rates on individual nodes of the Tor architecture, leading to a scalable approach. We successfully avoid congestion through exchanging information of predicted behavior with adjacent nodes. Furthermore, we formulate PredicTor with a focus on fair allocation of resources, for which we present and proof a novel optimization-based fairness approach. Our proposed controller is evaluated with the popular network simulator ns-3, where we compare it with the current Tor scheduler as well as with another recently proposed enhancement. PredicTor shows significant improvements over the previous approaches, especially with respect to latency.

cs.NI↗

arXiv2019

Map-Z: Exposing the Zcash Network in Times of Transition

Zcash is a privacy-preserving cryptocurrency that provides anonymous monetary transactions. While Zcash's anonymity is part of a rigorous scientific discussion, information on the underlying peer-to-peer network are missing. In this paper, we provide the first long-term measurement study of the Zcash network to capture key metrics such as the network size and node distribution as well as deeper insights on the centralization of the network. Furthermore, we present an inference method based on a timing analysis of block arrivals that we use to determine interconnections of nodes. We evaluate and verify our method through simulations and real-world experiments, yielding a precision of 50 % with a recall of 82 % in the real-world scenario. By adjusting the parameters, the topology inference model is adaptable to the conditions found in other cryptocurrencies and therefore also contributes to the broader discussion of topology hiding in general.

cs.CR↗

arXiv2019

Discharged Payment Channels: Quantifying the Lightning Network's Resilience to Topology-Based Attacks

The Lightning Network is the most widely used payment channel network (PCN) to date, making it an attractive attack surface for adversaries. In this paper, we analyze the Lightning Network's PCN topology and investigate its resilience towards random failures and targeted attacks. In particular, we introduce the notions of channel exhaustion and node isolation attacks and show that the Lightning Network is susceptible to these attacks. In a preliminary analysis, we confirm that the Lightning Network can be classified as a small-world and scale-free network. Based on these findings, we develop a series of strategies for targeted attacks and introduce metrics that allow us to quantify the adversary's advantage. Our results indicate that an attacker who is able to remove a certain number of nodes should follow a centrality-based strategy, while a resource-limited attacker who aims for high efficiency should employ a highest ranked minimum cut strategy.

cs.NI↗

arXiv2017

Towards a Concurrent and Distributed Route Selection for Payment Channel Networks

Payment channel networks use off-chain transactions to provide virtually arbitrary transaction rates. In this paper, we provide a new perspective on payment channels and consider them as a flow network. We propose an extended push-relabel algorithm to find payment flows in a payment channel network. Our algorithm enables a distributed and concurrent execution without violating capacity constraints. To this end, we introduce the concept of capacity locking. We prove that flows are valid and present first results.

cs.NI↗