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bib
--- Timezone: CEST
Creation date: 2024-09-09
Creation time: 06-31-43
--- Number of references
4
inproceedings
2022_pennekamp_cumul
CUMUL & Co: High-Impact Artifacts for Website Fingerprinting Research
2022
12
8
RWTH-2022-10811
Anonymous communication on the Internet is about hiding the relationship between communicating parties. At NDSS '16, we presented a new website fingerprinting approach, CUMUL, that utilizes novel features and a simple yet powerful algorithm to attack anonymization networks such as Tor. Based on pattern observation of data flows, this attack aims at identifying the content of encrypted and anonymized connections. Apart from the feature generation and the used classifier, we also provided a large dataset to the research community to study the attack at Internet scale. In this paper, we emphasize the impact of our artifacts by analyzing publications referring to our work with respect to the dataset, feature extraction method, and source code of the implementation. Based on this data, we draw conclusions about the impact of our artifacts on the research field and discuss their influence on related cybersecurity topics. Overall, from 393 unique citations, we discover more than 130 academic references that utilize our artifacts, 61 among them are highly influential (according to SemanticScholar), and at least 35 are from top-ranked security venues. This data underlines the significant relevance and impact of our work as well as of our artifacts in the community and beyond.
https://www.comsys.rwth-aachen.de/fileadmin/papers/2022/2022-pennekamp-cumul-artifacts.pdf
https://www.acsac.org/2022/program/artifacts_competition/
ACSA
Cybersecurity Artifacts Competition and Impact Award at 38th Annual Computer Security Applications Conference (ACSAC '22), December 5-9, 2022, Austin, TX, USA
Austin, TX, USA
38th Annual Computer Security Applications Conference (ACSAC '22)
December 5-9, 2022
10.18154/RWTH-2022-10811
1
JanPennekamp
MartinHenze
AndreasZinnen
FabianLanze
KlausWehrle
AndriyPanchenko
article
2022-henze-tii-prada
Complying with Data Handling Requirements in Cloud Storage Systems
IEEE Transactions on Cloud Computing
2022
9
10
3
1661-1674
In past years, cloud storage systems saw an enormous rise in usage. However, despite their popularity and importance as underlying infrastructure for more complex cloud services, today’s cloud storage systems do not account for compliance with regulatory, organizational, or contractual data handling requirements by design. Since legislation increasingly responds to rising data protection and privacy concerns, complying with data handling requirements becomes a crucial property for cloud storage systems. We present Prada , a practical approach to account for compliance with data handling requirements in key-value based cloud storage systems. To achieve this goal, Prada introduces a transparent data handling layer, which empowers clients to request specific data handling requirements and enables operators of cloud storage systems to comply with them. We implement Prada on top of the distributed database Cassandra and show in our evaluation that complying with data handling requirements in cloud storage systems is practical in real-world cloud deployments as used for microblogging, data sharing in the Internet of Things, and distributed email storage.
https://www.comsys.rwth-aachen.de/fileadmin/papers/2022/2022-henze-tii-prada.pdf
Online
en
2168-7161
10.1109/TCC.2020.3000336
1
MartinHenze
RomanMatzutt
JensHiller
ErikMühmer
Jan HenrikZiegeldorf
Johannesvan der Giet
KlausWehrle
proceedings
2022-serror-cset
PowerDuck: A GOOSE Data Set of Cyberattacks in Substations
2022
8
8
5
data sets, network traffic, smart grid security, IDS
https://www.comsys.rwth-aachen.de/fileadmin/papers/2022/2022-serror-cset-powerduck.pdf
ACM
New York, NY, USA
online
Virtual
Cyber Security Experimentation and Test Workshop (CSET 2022)
August 8, 2022
978-1-4503-9684-4/22/08
10.1145/3546096.3546102
1
SvenZemanek
ImmanuelHacker
KonradWolsing
EricWagner
MartinHenze
MartinSerror
article
2022_brauner_iop
A Computer Science Perspective on Digital Transformation in Production
ACM Transactions on Internet of Things
2022
5
1
3
2
The Industrial Internet-of-Things (IIoT) promises significant improvements for the manufacturing industry by facilitating the integration of manufacturing systems by Digital Twins. However, ecological and economic demands also require a cross-domain linkage of multiple scientific perspectives from material sciences, engineering, operations, business, and ergonomics, as optimization opportunities can be derived from any of these perspectives. To extend the IIoT to a true Internet of Production, two concepts are required: first, a complex, interrelated network of Digital Shadows which combine domain-specific models with data-driven AI methods; and second, the integration of a large number of research labs, engineering, and production sites as a World Wide Lab which offers controlled exchange of selected, innovation-relevant data even across company boundaries. In this article, we define the underlying Computer Science challenges implied by these novel concepts in four layers: Smart human interfaces provide access to information that has been generated by model-integrated AI. Given the large variety of manufacturing data, new data modeling techniques should enable efficient management of Digital Shadows, which is supported by an interconnected infrastructure. Based on a detailed analysis of these challenges, we derive a systematized research roadmap to make the vision of the Internet of Production a reality.
Internet of Production; World Wide Lab; Digital Shadows; Industrial Internet of Things
internet-of-production
https://www.comsys.rwth-aachen.de/fileadmin/papers/2022/2022-brauner-digital-transformation.pdf
ACM
2691-1914
10.1145/3502265
1
PhilippBrauner
ManuelaDalibor
MatthiasJarke
IkeKunze
IstvánKoren
GerhardLakemeyer
MartinLiebenberg
JudithMichael
JanPennekamp
ChristophQuix
BernhardRumpe
Wilvan der Aalst
KlausWehrle
AndreasWortmann
MartinaZiefle