Article
Computer Science, Information Systems
Mahei Manhai Li, Philipp Reinhard, Christoph Peters, Sarah Oeste-Reiss, Jan Marco Leimeister
Summary: This article introduces a novel human-in-the-loop (HIL) design for ITSM support ticket recommendations by incorporating a value co-creation perspective. The design incentivizes ITSM agents to provide labels during their everyday ticket-handling procedures, and the evaluation shows that recommendations after label improvement have increased user ratings.
INFORMATION SYSTEMS
(2024)
Article
Computer Science, Information Systems
Sergey Kitaev, Artem Pyatkin
Summary: This article discusses the properties of semi-transitive directed graphs and split graphs, pointing out that recognizing the semi-transitive orientability is an NP-complete problem. It also proves that the recognition of semi-transitive orientability of split graphs can be done in polynomial time.
INFORMATION PROCESSING LETTERS
(2024)
Article
Computer Science, Information Systems
Lijing Zheng, Haibin Kan, Jie Peng, Yanjun Li, Yanbin Zheng
Summary: In this brief note, we introduce a new class of GAPN power functions of the form xk2p2i+k1pi+k0 over finite fields Fpn, with p being odd and gcd(n, i) = 1 (up to EA-equivalence).
INFORMATION PROCESSING LETTERS
(2024)
Article
Computer Science, Information Systems
Eduardo Sany Laber
Summary: This study examines the problem of partitioning a set of points X into k groups using an axis-aligned decision tree, aiming to obtain easily explainable partitions. The computational complexity of this problem for k-means, k-medians, and the k-center cost-functions is investigated, and it is proven that the optimization problems induced by these cost-functions are hard to approximate.
INFORMATION PROCESSING LETTERS
(2024)
Article
Computer Science, Information Systems
Shideh Yavary Mehr, Byrav Ramamurthy
Summary: This paper focuses on the issue of link failures in optical networks and proposes an improved recovery strategy by combining resource delayed release (RDR) with protection strategies. Four different protection methods are evaluated, and it is found that the PPP method performs the best in terms of reducing blocking probability, bandwidth blocking probability, and service provisioning time when utilizing RDR.
OPTICAL SWITCHING AND NETWORKING
(2024)
Article
Computer Science, Information Systems
Sebastian Maneth, Helmut Seidl
Summary: It is well known that the existence of an equivalent deterministic top-down tree automaton can be determined for a given bottom-up tree automaton. However, a recent claim of polynomial time decision-making for this has been proven wrong. In this paper, we address this mistake and present a correct property that allows for the determination of whether or not a given tree language can be recognized by a deterministic top-down tree automaton in polynomial time. Furthermore, our new property is applicable to arbitrary deterministic bottom-up tree automata, not just minimal ones as previously believed.
INFORMATION PROCESSING LETTERS
(2024)
Article
Computer Science, Information Systems
Iris Reinhartz-Berger, Alan Hartman, Doron Kliger
Summary: Many IT departments provide solutions that partially meet the needs of business units. This research aims to develop a data-driven analysis method to support the selection of solutions with higher prospects of adoption and identify design gaps and barriers.
INFORMATION SYSTEMS
(2024)
Article
Computer Science, Information Systems
Roberto Doriguzzi-Corin, Domenico Siracusa
Summary: This paper discusses the application of federated learning in the field of cybersecurity and proposes an adaptive mechanism-based federated learning solution for DDoS attack detection in dynamic cybersecurity scenarios. Through experiments, it is demonstrated that the proposed solution outperforms state-of-the-art federated learning algorithms in terms of convergence time and accuracy.
COMPUTERS & SECURITY
(2024)
Article
Computer Science, Information Systems
Domna Bilika, Nikoletta Michopoulou, Efthimios Alepis, Constantinos Patsakis
Summary: Voice Assistants (VAs) are widely used in smart devices, but are vulnerable to attacks, as shown by experiments with popular VAs revealing successful attack rates exceeding 30% and statistical variations among vendors, calling for additional countermeasures to protect user information.
COMPUTERS & SECURITY
(2024)
Article
Computer Science, Information Systems
Pedro Miguel Sanchez, Alberto Huertas Celdran, Gerome Bovet, Gregorio Martinez Perez
Summary: This research proposes an individual IoT device authentication framework based on hardware behavior fingerprinting and Transformer autoencoders. By monitoring and analyzing the behavior of key hardware components, unique fingerprints for each device are created. Experimental results demonstrate the effectiveness of this approach in enhancing authentication, security, and trust in crowdsensing applications.
COMPUTERS & SECURITY
(2024)
Article
Computer Science, Information Systems
Xiaoyu Wang, Xiaobo Yang, Xueping Liang, Xiu Zhang, Wei Zhang, Xiaorui Gong
Summary: The problem of alert fatigue can have significant consequences for enterprise security. This paper introduces the AlertPro framework, which prioritizes alerts based on severity and provides real-time updates, mitigating alert fatigue and enabling security analysts to focus on high-priority threats.
COMPUTERS & SECURITY
(2024)
Article
Computer Science, Information Systems
Hongsong Chen, Xingyu Li, Wenmao Liu
Summary: Multivariate time-series anomaly detection is crucial for maintaining normal operation of physical equipment. Recent advances have been made in this field, but two challenges have limited the model's ability to generalize. To address these challenges, a multivariate time-series anomaly detection model consisting of a characterization network and a forecasting network is proposed. Experimental results demonstrate that this method outperforms baseline methods in terms of detection performance and robustness.
COMPUTERS & SECURITY
(2024)
Article
Computer Science, Information Systems
Junhao Li, Junjiang He, Wenshan Li, Wenbo Fang, Geying Yang, Tao Li
Summary: Android mobile phones dominate the market and bring challenges of malware issues. Traditional machine learning and deep learning methods are not effective in detecting Android malware due to imbalanced data and high-dimension features. To address this, a new Android malware classification model called SynDroid is proposed, which uses CTGAN-SVM to generate qualified high-dimension samples and adaptively discards bad results.
COMPUTERS & SECURITY
(2024)
Article
Computer Science, Information Systems
Susanne Durst, Christoph Hinteregger, Malgorzata Zieba
Summary: This study investigates the impact of technological and market turbulence on organizational cyber security risk management and resilience, and reveals their different effects on different aspects.
COMPUTERS & SECURITY
(2024)
Article
Computer Science, Information Systems
Martin Stancek, Ivan Polasek, Tibor Zalabai, Juraj Vincur, Rodi Jolak, Michel Chaudron
Summary: The aim of this research is to support distributed software design activities in Virtual Reality (VR). Using design science research methodology, a tool for collaborative design in VR is designed and evaluated. The efficiency of collaboration and recall of design information when using VR software design environment compared to non-VR environment are evaluated. Furthermore, the perceptions and preferences of users are collected to explore the opportunities and challenges of using VR software design environment.
INFORMATION AND SOFTWARE TECHNOLOGY
(2024)
Article
Computer Science, Information Systems
Dimitri Van Landuyt, Vincent Wijshoff, Wouter Joosen
Summary: This article investigates the injection-related risks in Neo4j graph database and its ecosystem and finds that the query parameterization mechanism promoted by Neo4j is effective in mitigating traditional query injection threats. However, traditional query injection attacks can still occur in applications that involve dynamic, run-time query construction without adopting the query parameterization mechanism.
COMPUTERS & SECURITY
(2024)
Article
Computer Science, Information Systems
Juanjuan Weng, Zhiming Luo, Dazhen Lin, Shaozi Li
Summary: In this study, we aim to learn targeted universal adversarial perturbations (UAPs) with higher transferability by ensembling multiple models. We propose a normalized logit loss to narrow the margin of the targeted class's logits among different models and introduce a novel sequential meta-learning optimization strategy to further increase transferability. Experimental results demonstrate the superiority of our approach over existing ensemble attacks in both white box and black-box settings.
COMPUTERS & SECURITY
(2024)
Article
Computer Science, Information Systems
Jiayi Chen, Urs Hengartner, Hassan Khan
Summary: This article discusses the challenges of designing multi-user, multi-modal implicit authentication systems and proposes an evaluation framework called SHRIMPS to support researchers in design and comparison. By using SHRIMPS, researchers can evaluate authentication schemes with multiple modalities and automatically label and update models, enhancing accuracy and security.
COMPUTERS & SECURITY
(2024)
Article
Computer Science, Information Systems
Raghunathan Krishankumar, Sundararajan Dhruva, Kattur S. Ravichandran, Samarjit Kar
Summary: Health 4.0 is gaining global attention for better healthcare through digital technologies. This study proposes a new decision-making framework for selecting viable blockchain service providers in the Internet of Medical Things (IoMT). The framework addresses the limitations in previous studies and demonstrates its applicability in the Indian healthcare sector. The results show the top ranking BSPs, the importance of various criteria, and the effectiveness of the developed model.
INFORMATION SCIENCES
(2024)
Article
Computer Science, Information Systems
Sumana Maiti, Sudip Misra, Ayan Mondal
Summary: The broadcast proxy re-encryption methods extend traditional proxy re-encryption mechanisms and propose a scheme called MBP for IoT applications. MBP calculates a single re-encryption key for all user groups and uses multi-channel broadcast encryption to reduce security element size. However, it increases computation time for receiver IoT devices. The use of Rubinstein-Stahl bargaining game approach addresses this issue and MBP is secure against selective group chosen-ciphertext attack in the random oracle model.
COMPUTER COMMUNICATIONS
(2024)
