arXiv subjects

Oliver Hohlfeld

Publications and source records attributed to Oliver Hohlfeld.

At least 19 recordsLinked to original sources

arXiv2025

The (C)omprehensive (A)rchitecture (P)attern (I)ntegration method: Navigating the sea of technology

The technological landscape changes daily, making it nearly impossible for a single person to be aware of all trends or available tools that may or may not be suitable for their software project. This makes tool selection and architectural design decisions a complex problem, especially for large-scale software systems. To tackle this issue, we introduce CAPI, the Comprehensive Architecture Pattern Integration method that uses a diagnostic decision tree to suggest architectural patterns depending on user needs. By suggesting patterns instead of tools, the overall complexity for further decisions is lower as there are fewer architectural patterns than tools due to the abstract nature of patterns. Moreover, since tools implement patterns, each non-proposed pattern reduces the number of tools to choose from, reducing complexity. We iteratively developed CAPI, evaluating its understandability and usability in small studies with academic participants. When satisfied with the outcome, we performed a user-study with industry representatives to investigate the state-of-the-art in technology selection and the effectiveness of our proposed method. We find that technology selection is largely performed via trial and error, that CAPI is uniformly perceived as helpful, and that CAPI is able to reproduce the productive architectural environments of our participants.

cs.SE↗

arXiv2024

The Age of DDoScovery: An Empirical Comparison of Industry and Academic DDoS Assessments

Motivated by the impressive but diffuse scope of DDoS research and reporting, we undertake a multistakeholder (joint industry-academic) analysis to seek convergence across the best available macroscopic views of the relative trends in two dominant classes of attacks - direct-path attacks and reflection-amplification attacks. We first analyze 24 industry reports to extract trends and (in)consistencies across observations by commercial stakeholders in 2022. We then analyze ten data sets spanning industry and academic sources, across four years (2019-2023), to find and explain discrepancies based on data sources, vantage points, methods, and parameters. Our method includes a new approach: we share an aggregated list of DDoS targets with industry players who return the results of joining this list with their proprietary data sources to reveal gaps in visibility of the academic data sources. We use academic data sources to explore an industry-reported relative drop in spoofed reflection-amplification attacks in 2021-2022. Our study illustrates the value, but also the challenge, in independent validation of security-related properties of Internet infrastructure. Finally, we reflect on opportunities to facilitate greater common understanding of the DDoS landscape. We hope our results inform not only future academic and industry pursuits but also emerging policy efforts to reduce systemic Internet security vulnerabilities.

cs.CR↗

arXiv2023

An Overview of Analysis Methods and Evaluation Results for Caching Strategies

We survey analytical methods and evaluation results for the performance assessment of caching strategies. Knapsack solutions are derived, which provide static caching bounds for independent requests and general bounds for dynamic caching under arbitrary request pattern. We summarize Markov- and time-to-live-based solutions, which assume specific stochastic processes for capturing web request streams and timing. We compare the performance of caching strategies with different knowledge about the properties of data objects regarding a broad set of caching demands. The efficiency of web caching must regard benefits for network wide traffic load, energy consumption and quality-of-service aspects in a tradeoff with costs for updating and storage overheads.

cs.DS↗

arXiv2023

Reviewing War: Unconventional User Reviews as a Side Channel to Circumvent Information Controls

During the first days of the 2022 Russian invasion of Ukraine, Russia's media regulator blocked access to many global social media platforms and news sites, including Twitter, Facebook, and the BBC. To bypass the information controls set by Russian authorities, pro-Ukrainian groups explored unconventional ways to reach out to the Russian population, such as posting war-related content in the user reviews of Russian business available on Google Maps or Tripadvisor. This paper provides a first analysis of this new phenomenon by analyzing the creative strategies to avoid state censorship. Specifically, we analyze reviews posted on these platforms from the beginning of the conflict to September 2022. We measure the channeling of war messages through user reviews in Tripadvisor and Google Maps, as well as in VK, a popular Russian social network. Our analysis of the content posted on these services reveals that users leveraged these platforms to seek and exchange humanitarian and travel advice, but also to disseminate disinformation and polarized messages. Finally, we analyze the response of platforms in terms of content moderation and their impact.

cs.SI↗

arXiv2022

Reviewing Best Practices in Online Conferencing

The COVID-19 pandemic disrupted the usual ways the networking research community operates. This article reviews experiences organising and participating in virtual conferences during the COVID-19 pandemic between 2020-2021. Thanks to the broader scope of the Dagstuhl seminar on 'Climate Friendly Internet Research' held in July 2021, here we focus the discussion on state-of-the-art in technologies and practices applied in online events such as conferences, teaching, and other meetings and identify approaches that are successful as well as others that need improvement. We also present a set of best practices and recommendations for the community.

cs.NI↗

arXiv2022

Characterizing the country-wide adoption and evolution of the Jodel messaging app in Saudi Arabia

Social media is subject to constant growth and evolution, yet little is known about their early phases of adoption. To shed light on this aspect, this paper empirically characterizes the initial and country-wide adoption of a new type of social media in Saudi Arabia that happened in 2017. Unlike established social media, the studied network Jodel is anonymous and location-based to form hundreds of independent communities country-wide whose adoption pattern we compare. We take a detailed and full view from the operators perspective on the temporal and geographical dimension on the evolution of these different communities -- from their very first the first months of establishment to saturation. This way, we make the early adoption of a new type of social media visible, a process that is often invisible due to the lack of data covering the first days of a new network.

cs.SI↗

arXiv2022

Anonymous Hyperlocal Communities: What do they talk about?

In this paper, we study what users talk about in a plethora of independent hyperlocal and anonymous online communities in a single country: Saudi Arabia (KSA). We base this perspective on performing a content classification of the Jodel network in the KSA. To do so, we first contribute a content classification schema that assesses both the intent (why) and the topic (what) of posts. We use the schema to label 15k randomly sampled posts and further classify the top 1k hashtags. We observe a rich set of benign (yet at times controversial in conservative regimes) intents and topics that dominantly address information requests, entertainment, or dating/flirting. By comparing two large cities (Riyadh and Jeddah), we further show that hyperlocality leads to shifts in topic popularity between local communities. By evaluating votes (content appreciation) and replies (reactions), we show that the communities react differently to different topics; e.g., entertaining posts are much appreciated through votes, receiving the least replies, while beliefs & politics receive similarly few replies but are controversially voted.

cs.SI↗

arXiv2022

Differences in Social Media Usage Exist Between Western and Middle-East Countries

In this paper, we empirically analyze two examples of a Western (DE) versus Middle-East (SA) Online Social Messaging App. By focusing on the system interactions over time in comparison, we identify inherent differences in user engagement. We take a deep dive and shed light onto differences in user attention shifts and showcase their structural implications to the user experience. Our main findings show that in comparison to the German counterparts, the Saudi communities prefer creating content in longer conversations, while voting more conservative.

cs.SI↗

arXiv2021

CyberBunker 2.0 -- A Domain and Traffic Perspective on a Bulletproof Hoster

In September 2019, 600 armed German cops seized the physical premise of a Bulletproof Hoster (BPH) referred to as CyberBunker 2.0. The hoster resided in a decommissioned NATO bunker and advertised to host everything but child porn and anything related to terrorism while keeping servers online no matter what. While the anatomy, economics and interconnection-level characteristics of BPHs are studied, their traffic characteristics are unknown. In this poster, we present the first analysis of domains, web pages, and traffic captured at a major tier-1 ISP and a large IXP at the time when the CyberBunker was in operation. Our study sheds light on traffic characteristics of a BPH in operation. We show that a traditional BGP-based BPH identification approach cannot detect the CyberBunker, but find characteristics from a domain and traffic perspective that can add to future identification approaches.

cs.CR↗

arXiv2021

DDoS Never Dies? An IXP Perspective on DDoS Amplification Attacks

DDoS attacks remain a major security threat to the continuous operation of Internet edge infrastructures, web services, and cloud platforms. While a large body of research focuses on DDoS detection and protection, to date we ultimately failed to eradicate DDoS altogether. Yet, the landscape of DDoS attack mechanisms is even evolving, demanding an updated perspective on DDoS attacks in the wild. In this paper, we identify up to 2608 DDoS amplification attacks at a single day by analyzing multiple Tbps of traffic flows at a major IXP with a rich ecosystem of different networks. We observe the prevalence of well-known amplification attack protocols (e.g., NTP, CLDAP), which should no longer exist given the established mitigation strategies. Nevertheless, they pose the largest fraction on DDoS amplification attacks within our observation and we witness the emergence of DDoS attacks using recently discovered amplification protocols (e.g., OpenVPN, ARMS, Ubiquity Discovery Protocol). By analyzing the impact of DDoS on core Internet infrastructure, we show that DDoS can overload backbone-capacity and that filtering approaches in prior work omit 97% of the attack traffic.

cs.CR↗

arXiv2021

Understanding & Predicting User Lifetime with Machine Learning in an Anonymous Location-Based Social Network

In this work, we predict the user lifetime within the anonymous and location-based social network Jodel in the Kingdom of Saudi Arabia. Jodel's location-based nature yields to the establishment of disjoint communities country-wide and enables for the first time the study of user lifetime in the case of a large set of disjoint communities. A user's lifetime is an important measurement for evaluating and steering customer bases as it can be leveraged to predict churn and possibly apply suitable methods to circumvent potential user losses. We train and test off the shelf machine learning techniques with 5-fold crossvalidation to predict user lifetime as a regression and classification problem; identifying the Random Forest to provide very strong results. Discussing model complexity and quality trade-offs, we also dive deep into a time-dependent feature subset analysis, which does not work very well; Easing up the classification problem into a binary decision (lifetime longer than timespan $x$) enables a practical lifetime predictor with very good performance. We identify implicit similarities across community models according to strong correlations in feature importance. A single countrywide model generalizes the problem and works equally well for any tested community; the overall model internally works similar to others also indicated by its feature importances.

cs.SI↗

arXiv2020

The Lockdown Effect: Implications of the COVID-19 Pandemic on Internet Traffic

Due to the COVID-19 pandemic, many governments imposed lock downs that forced hundreds of millions of citizens to stay at home. The implementation of confinement measures increased Internet traffic demands of residential users, in particular, for remote working, entertainment, commerce, and education, which, as a result, caused traffic shifts in the Internet core. In this paper, using data from a diverse set of vantage points (one ISP, three IXPs, and one metropolitan educational network), we examine the effect of these lockdowns on traffic shifts. We find that the traffic volume increased by 15-20% almost within a week--while overall still modest, this constitutes a large increase within this short time period. However, despite this surge, we observe that the Internet infrastructure is able to handle the new volume, as most traffic shifts occur outside of traditional peak hours. When looking directly at the traffic sources, it turns out that, while hypergiants still contribute a significant fraction of traffic, we see (1) a higher increase in traffic of non-hypergiants, and (2) traffic increases in applications that people use when at home, such as Web conferencing, VPN, and gaming. While many networks see increased traffic demands, in particular, those providing services to residential users, academic networks experience major overall decreases. Yet, in these networks, we can observe substantial increases when considering applications associated to remote working and lecturing.

cs.NI↗

arXiv2020

The Boon and Bane of Cross-Signing: Shedding Light on a Common Practice in Public Key Infrastructures

Public Key Infrastructures (PKIs) with their trusted Certificate Authorities (CAs) provide the trust backbone for the Internet: CAs sign certificates which prove the identity of servers, applications, or users. To be trusted by operating systems and browsers, a CA has to undergo lengthy and costly validation processes. Alternatively, trusted CAs can cross-sign other CAs to extend their trust to them. In this paper, we systematically analyze the present and past state of cross-signing in the Web PKI. Our dataset (derived from passive TLS monitors and public CT logs) encompasses more than 7 years and 225 million certificates with 9.3 billion trust paths. We show benefits and risks of cross-signing. We discuss the difficulty of revoking trusted CA certificates where, worrisome, cross-signing can result in valid trust paths to remain after revocation; a problem for non-browser software that often blindly trusts all CA certificates and ignores revocations. However, cross-signing also enables fast bootstrapping of new CAs, e.g., Let's Encrypt, and achieves a non-disruptive user experience by providing backward compatibility. In this paper, we propose new rules and guidance for cross-signing to preserve its positive potential while mitigating its risks.

cs.CR↗

arXiv2020

Corona-Warn-App: Tracing the Start of the Official COVID-19 Exposure Notification App for Germany

On June 16, 2020, Germany launched an open-source smartphone contact tracing app ("Corona-Warn-App") to help tracing SARS-CoV-2 (coronavirus) infection chains. It uses a decentralized, privacy-preserving design based on the Exposure Notification APIs in which a centralized server is only used to distribute a list of keys of SARS-CoV-2 infected users that is fetched by the app once per day. Its success, however, depends on its adoption. In this poster, we characterize the early adoption of the app using Netflow traces captured directly at its hosting infrastructure. We show that the app generated traffic from allover Germany---already on the first day. We further observe that local COVID-19 outbreaks do not result in noticeable traffic increases.

cs.CY↗

arXiv2020

Word-Emoji Embeddings from large scale Messaging Data reflect real-world Semantic Associations of Expressive Icons

We train word-emoji embeddings on large scale messaging data obtained from the Jodel online social network. Our data set contains more than 40 million sentences, of which 11 million sentences are annotated with a subset of the Unicode 13.0 standard Emoji list. We explore semantic emoji associations contained in this embedding by analyzing associations between emojis, between emojis and text, and between text and emojis. Our investigations demonstrate anecdotally that word-emoji embeddings trained on large scale messaging data can reflect real-world semantic associations. To enable further research we release the Jodel Emoji Embedding Dataset (JEED1488) containing 1488 emojis and their embeddings along 300 dimensions.

cs.CL↗

arXiv2020

Multi-episodic Perceived Quality of an Audio-on-Demand Service

QoE is traditionally evaluated by using short stimuli usually representing parts or single usage episodes. This opens the question on how the overall service perception involving multiple} usage episodes can be evaluated---a question of high practical relevance to service operators. Despite initial research on this challenging aspect of multi-episodic perceived quality, the question of the underlying quality formation processes and its factors are still to be discovered. We present a multi-episodic experiment of an Audio on Demand service over a usage period of 6~days with 93 participants. Our work directly extends prior work investigating the impact of time between usage episodes. The results show similar effects---also the recency effect is not statistically significant. In addition, we extend prediction of multi-episodic judgments by accounting for the observed saturation.

cs.HC↗

arXiv2020

MUST, SHOULD, DON'T CARE: TCP Conformance in the Wild

Standards govern the SHOULD and MUST requirements for protocol implementers for interoperability. In case of TCP that carries the bulk of the Internets' traffic, these requirements are defined in RFCs. While it is known that not all optional features are implemented and nonconformance exists, one would assume that TCP implementations at least conform to the minimum set of MUST requirements. In this paper, we use Internet-wide scans to show how Internet hosts and paths conform to these basic requirements. We uncover a non-negligible set of hosts and paths that do not adhere to even basic requirements. For example, we observe hosts that do not correctly handle checksums and cases of middlebox interference for TCP options. We identify hosts that drop packets when the urgent pointer is set or simply crash. Our publicly available results highlight that conformance to even fundamental protocol requirements should not be taken for granted but instead checked regularly.

cs.NI↗

arXiv2019

Perceiving QUIC: Do Users Notice or Even Care?

QUIC, as the foundation for HTTP/3, is becoming an Internet reality. A plethora of studies already show that QUIC excels beyond TCP+TLS+HTTP/2. Yet, these studies compare a highly optimized QUIC Web stack against an unoptimized TCP-based stack. In this paper, we bring TCP up to speed to perform an eye-level comparison. Instead of relying on technical metrics, we perform two extensive user studies to investigate QUIC's impact on the quality of experience. First, we investigate if users can distinguish two protocol versions in a direct comparison, and we find that QUIC is indeed rated faster than TCP and even a tuned TCP. Yet, our second study shows that this perceived performance increase does mostly not matter to the users, and they rate QUIC and TCP indistinguishable.

cs.NI↗