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Horst Lichter

Publications and source records attributed to Horst Lichter.

10 recordsLinked to original sources

A Catalog of User Authentication Patterns

Security patterns are intended to support the design and development of secure software systems. However, although established catalogs of security patterns exist, their practical application remains limited. In particular, despite these catalogs, concrete patterns for common security controls such as user authentication (authentication for short) are lacking. This paper aims to make an initial contribution toward closing this gap, as exemplified by authentication. It presents a novel authentication pattern catalog, comprising 14 user authentication patterns. To support the catalog's practical application, it classifies patterns by the well-known concept of authentication factors and by the usual role each pattern fulfills in practice. By cataloging common authentication techniques through authentication patterns, we aim to make an important contribution to supporting software engineers and architects in designing and developing secure software systems.

cs.CR

A Faceted Classification of Authenticator-Centric Authentication Techniques

Authentication is a fundamental security means for protecting system resources. Authenticator-centric authentication techniques (AuthN Techniques) address how mechanisms and credentials are used via Authenticators. There are many AuthN Techniques that differ in many ways and there exist classification approaches that aim to structure them. However, they are limited in the aspects they classify and are not flexible enough to accommodate the diverse nature of AuthN Techniques. This paper presents two contributions. First, novel, faceted classification schemes for AuthN Techniques and Authenticators are presented. The schemes were developed based on 345 papers identified through a targeted LLM-assisted literature review and semantic clustering. The classification schemes were applied to build a catalog of Authenticators and AuthN Techniques; the second contribution of this paper. This paper presents our methodology, the classification schemes with example applications, the list of AuthN Techniques from the catalog, and discussions on future work.

cs.CR

Can ChatGPT Generate Realistic Synthetic System Requirement Specifications? Results of a Case Study

System requirement specifications (SyRSs) are central, natural-language (NL) artifacts. Access to real SyRS for research purposes is highly valuable but limited by proprietary restrictions or confidentiality concerns. Generating synthetic SyRSs (SSyRSs) can address this scarcity. Black-box large language models (LLMs) such as ChatGPT offer compelling generation capabilities by providing easy access to NL generation functions without requiring access to real data. However, LLMs suffer from hallucinations and overconfidence, which pose major challenges in their use. We designed an exploratory study to investigate whether, despite these challenges, we can generate realistic SSyRSs with ChatGPT without having access to real SyRSs. Using a systematic approach that leverages prompt patterns, LLM-based quality assessments, and iterative prompt refinements, we generated 300 SSyRSs across 10 industries with ChatGPT. The results were evaluated using cross-model checks and an expert study, with n=87 submitted surveys. 62\% of experts considered the SSyRSs to be realistic. However, in-depth examination revealed contradictory statements and deficiencies. Overall, we were able to generate realistic SSyRSs to a certain extent with ChatGPT, but LLM-based quality assessments cannot fully replace thorough expert evaluations. This paper presents the methodology and results of our study and discusses the key insights we obtained.

cs.SE

Proto-ML: An IDE for ML Solution Prototyping

Prototyping plays a critical role in the development of machine learning (ML) solutions, yet existing tools often provide limited support for effective collaboration and knowledge reuse among stakeholders. This paper introduces Proto-ML, an IDE designed to strengthen ML prototyping workflows. By addressing key deficiencies such as insufficient stakeholder involvement, limited cross-project knowledge reuse, and fragmented tool support, Proto-ML offers a unified framework that enables structured documentation of prototyping activities and promotes knowledge sharing across projects. The Proto-ML IDE consists of three extension bundles: prototype implementation, analysis, and knowledge management. These extensions support tasks ranging from evaluating prototype quality against defined criteria to incorporating stakeholder perspectives throughout the development process. Preliminary user feedback suggests that Proto-ML can increase prototyping efficiency and foster more transparent and reusable ML solution development.

cs.SE

Challenges in Developing Secure Software -- Results of an Interview Study in the German Software Industry

The damage caused by cybercrime makes the development of secure software inevitable. Although many tools and frameworks exist to support the development of secure software, statistics on cybercrime show no improvement in recent years. To understand the challenges software companies face in developing secure software, we conducted an interview study with 19 industry experts from 12 cross-industry companies. The results of our study show that the challenges are mainly due to high complexity, a lack of security awareness, and unsuitable processes, which are further exacerbated by an immediate lack of skilled personnel. This article presents our study and the challenges we identified, and derives potential research directions from them.

cs.SE

SecuRe -- An Approach to Recommending Security Design Patterns

Security is an important quality of software systems, but there is a huge lack of security experts. To overcome this gap, we aim to make security design knowledge reusable for architects by proposing the SecuRe recommendation approach to secure software design. It lifts design patterns and knowledge engineering concepts to security-related design recommendations for software architectures. This paper presents the central concepts of this approach, the overall recommendation process, and the first results from an initial case study.

cs.SE

A Flexible Cell Classification for ML Projects in Jupyter Notebooks

Jupyter Notebook is an interactive development environment commonly used for rapid experimentation of machine learning (ML) solutions. Describing the ML activities performed along code cells improves the readability and understanding of Notebooks. Manual annotation of code cells is time-consuming and error-prone. Therefore, tools have been developed that classify the cells of a notebook concerning the ML activity performed in them. However, the current tools are not flexible, as they work based on look-up tables that have been created, which map function calls of commonly used ML libraries to ML activities. These tables must be manually adjusted to account for new or changed libraries. This paper presents a more flexible approach to cell classification based on a hybrid classification approach that combines a rule-based and a decision tree classifier. We discuss the design rationales and describe the developed classifiers in detail. We implemented the new flexible cell classification approach in a tool called JupyLabel. Its evaluation and the obtained metric scores regarding precision, recall, and F1-score are discussed. Additionally, we compared JupyLabel with HeaderGen, an existing cell classification tool. We were able to show that the presented flexible cell classification approach outperforms this tool significantly.

cs.SE

Towards the Definition of Enterprise Architecture Debts

In the software development industry, technical debt is regarded as a critical issue in term of the negative consequences such as increased software development cost, low product quality, decreased maintainability, and slowed progress to the long-term success of developing software. However, despite the vast research contributions in technical debt management for software engineering, the idea of technical debt fails to provide a holistic consideration to include both IT and business aspects. Further, implementing an enterprise architecture (EA) project might not always be a success due to uncertainty and unavailability of resources. Therefore, we relate the consequences of EA implementation failure with a new metaphor --Enterprise Architecture Debt (EA Debt). We anticipate that the accumulation of EA Debt will negatively influence EA quality, also expose the business into risk.

cs.SE

Staged Evolution with Quality Gates for Model Libraries

Model evolution is widely considered as a subject under research. Despite its role in research, common purpose concepts, approaches, solutions, and methodologies are missing. Limiting the scope to model libraries makes model evolution and related quality concerns manageable, as we show below. In this paper, we put forward our quality staged model evolution theory for model libraries. It is founded on evolution graphs, which offer a structure for model evolution in model libraries through evolution steps. These evolution steps eventually form a sequence, which can be partitioned into stages by quality gates. Each quality gate is defined by a lightweight quality model and respective characteristics fostering reusability.

cs.SE

Proactive Quality Guidance for Model Evolution in Model Libraries

Model evolution in model libraries differs from general model evolution. It limits the scope to the manageable and allows to develop clear concepts, approaches, solutions, and methodologies. Looking at model quality in evolving model libraries, we focus on quality concerns related to reusability. In this paper, we put forward our proactive quality guidance approach for model evolution in model libraries. It uses an editing-time assessment linked to a lightweight quality model, corresponding metrics, and simplified reviews. All of which help to guide model evolution by means of quality gates fostering model reusability.

cs.SE