Zobrazeno 1 - 10
of 46
pro vyhledávání: '"Cito, Jürgen"'
Autor:
Happe, Andreas, Cito, Jürgen
Linux systems are integral to the infrastructure of modern computing environments, necessitating robust security measures to prevent unauthorized access. Privilege escalation attacks represent a significant threat, typically allowing attackers to ele
Externí odkaz:
http://arxiv.org/abs/2405.02106
Infrastructure as Code (IaC) has enabled cloud customers to have more agility in creating and modifying complex deployments of cloud-provisioned resources. By writing a configuration in IaC languages such as CloudFormation, users can declaratively sp
Externí odkaz:
http://arxiv.org/abs/2402.15632
Penetration testing, an essential component of software security testing, allows organizations to identify and remediate vulnerabilities in their systems, thus bolstering their defense mechanisms against cyberattacks. One recent advancement in the re
Externí odkaz:
http://arxiv.org/abs/2310.11409
Autor:
Happe, Andreas, Cito, Jürgen
Offensive security-tests are a common way to pro-actively discover potential vulnerabilities. They are performed by specialists, often called penetration-testers or white-hat hackers. The chronic lack of available white-hat hackers prevents sufficien
Externí odkaz:
http://arxiv.org/abs/2308.07057
Autor:
Happe, Andreas, Cito, Jürgen
The field of software security testing, more specifically penetration testing, is an activity that requires high levels of expertise and involves many manual testing and analysis steps. This paper explores the potential usage of large-language models
Externí odkaz:
http://arxiv.org/abs/2308.00121
Background: Ad hoc parsers are pieces of code that use common string functions like split, trim, or slice to effectively perform parsing. Whether it is handling command-line arguments, reading configuration files, parsing custom file formats, or any
Externí odkaz:
http://arxiv.org/abs/2304.09733
Autor:
Beller, Moritz, Li, Hongyu, Nair, Vivek, Murali, Vijayaraghavan, Ahmad, Imad, Cito, Jürgen, Carlson, Drew, Aye, Ari, Dyer, Wes
Catching and attributing code change-induced performance regressions in production is hard; predicting them beforehand, even harder. A primer on automatically learning to predict performance regressions in software, this article gives an account of t
Externí odkaz:
http://arxiv.org/abs/2208.04351
Autor:
Schröder, Michael, Cito, Jürgen
Publikováno v:
2022 IEEE/ACM 44th International Conference on Software Engineering: New Ideas and Emerging Results (ICSE-NIER)
Ad hoc parsers are everywhere: they appear any time a string is split, looped over, interpreted, transformed, or otherwise processed. Every ad hoc parser gives rise to a language: the possibly infinite set of input strings that the program accepts wi
Externí odkaz:
http://arxiv.org/abs/2202.01021
Machine learning (ML) models play an increasingly prevalent role in many software engineering tasks. However, because most models are now powered by opaque deep neural networks, it can be difficult for developers to understand why the model came to a
Externí odkaz:
http://arxiv.org/abs/2111.05711
Detecting performance issues due to suboptimal code during the development process can be a daunting task, especially when it comes to localizing them after noticing performance degradation after deployment. Static analysis has the potential to provi
Externí odkaz:
http://arxiv.org/abs/2105.02023