Demo Data from SIGIR 2026 / reviewers in the wild / expert
Mohammed Rashed
dblp:241/5097
· DBLP profile ↗
2ranked-venue papers
1as first author
0since 2021 · last 2020
0000-0002-0119-0796ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 first-authorSecurity and privacy · 1Databases, data management, data science and information retrieval · 1 · 1 first-authorHuman-computer interaction and ubiquitous computing · 1 · 1 first-author
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Network and information security
1 paper |
Web and mobile security · 67% Privacy and data protection · 33% | |
| Software engineering, system software, and programming languages
1 paper |
Empirical software engineering · 50% Program analysis · 50% |
Topics — the 5 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Web and mobile security › mobile security
android security |
0.4 | 1 | 2020 | An Analysis of Pre-installed Android Software · SP 2020 |
Privacy and data protection
mobile privacy |
0.4 | 1 | 2020 | An Analysis of Pre-installed Android Software · SP 2020 |
Web and mobile security › mobile security
pre-installed app analysis |
0.4 | 1 | 2020 | An Analysis of Pre-installed Android Software · SP 2020 |
Program analysis › binary analysis
firmware analysis |
0.1 | 1 | 2020 | An Analysis of Pre-installed Android Software · SP 2020 |
Empirical software engineering
mining software repositories |
0.1 | 1 | 2020 | An Analysis of Pre-installed Android Software · SP 2020 |
Methods — techniques the papers use, named apart from their topics
large-scale measurement · 0.9crowdsourcing · 0.9
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2020 | An Analysis of Pre-installed Android SoftwareabstractThe open-source nature of the Android OS makes it possible for manufacturers to ship custom versions of the OS along with a set of pre-installed apps, often for product differentiation. Some device vendors have recently come under scrutiny for potentially invasive private data collection practices and other potentially harmful or unwanted behavior of the preinstalled apps on their devices. Yet, the landscape of preinstalled software in Android has largely remained unexplored, particularly in terms of the security and privacy implications of such customizations. In this paper, we present the first large- scale study of pre-installed software on Android devices from more than 200 vendors. Our work relies on a large dataset of real-world Android firmware acquired worldwide using crowd-sourcing methods. This allows us to answer questions related to the stakeholders involved in the supply chain, from device manufacturers and mobile network operators to third- party organizations like advertising and tracking services, and social network platforms. Our study allows us to also uncover relationships between these actors, which seem to revolve primarily around advertising and data-driven services. Overall, the supply chain around Android's open source model lacks transparency and has facilitated potentially harmful behaviors and backdoored access to sensitive data and services without user consent or awareness. We conclude the paper with recommendations to improve transparency, attribution, and accountability in the Android ecosystem. Julien Gamba, Mohammed Rashed, Abbas Razaghpanah, Juan Tapiador, Narseo Vallina-Rodriguez |
SP | 2 |
| 2019 | Evaluation of extremist cohesion in a darknet forum using ERGM and LDAabstractISIS and similar extremist communities are increasingly using forums in the darknet to connect with each other and spread news and propaganda. In this paper, we attempt to understand their network in an online forum by using descriptive statistics, an exponential random graph model (ERGM) and Topic Modeling. Our analysis shows how the cohesion between active members forms and grows over time and under certain thread topics. We find that the top attendants of the forum have high centrality measures and other attributes of influencers. Mohammed Rashed, John Piorkowski, Ian McCulloh |
ASONAM | 1 |