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Computer Science, Information Systems
Reynaldo Gil-Pons, Max Ward, Loic Miller
Summary: This study considers the problem of computing an (s, d)-hypernetwork in an acyclic F-hypergraph. Previous research has explored this problem in general directed hypergraphs with cycles and acyclic B-hypergraphs, yielding insights into the complexity in these scenarios. However, this study finds that the problem is NP-hard in acyclic F-hypergraphs, which presents a striking complexity contrast with acyclic B-hypergraphs.
INFORMATION PROCESSING LETTERS
(2024)
Article
Computer Science, Information Systems
Xiaowei Li, Xiwen Lu
Summary: The facility location problem with maximum distance constraint is investigated and a (3,1)-approximation algorithm is proposed. The algorithm is compared with the previous one and is found to have lower memory requirements and is suitable for large-scale problems.
INFORMATION PROCESSING LETTERS
(2024)
Article
Computer Science, Information Systems
Tanguy Gernot, Christophe Rosenberger
Summary: This paper proposes an original method for generating one-time biometric templates for user authentication applications. The method involves deep learning for feature extraction and biohashing for protection against replay attacks. The efficiency and robustness of the method are confirmed through testing on common biometric databases.
COMPUTERS & SECURITY
(2024)
Article
Computer Science, Information Systems
Benyuan Yang, Lili Luo, Zhimeng Wang
Summary: Interoperation is widely used in practical industrial applications, but merging local access control policies may lead to security violations. Dealing with these issues in a multidomain environment is critical, but finding the maximum secure interoperation among individual systems poses a challenge due to the large number of entities and access involved.
COMPUTERS & SECURITY
(2024)
Article
Computer Science, Information Systems
Rafal Kozik, Massimo Ficco, Aleksandra Pawlicka, Marek Pawlicki, Francesco Palmieri, Michal Choras
Summary: The inclusion of Explainability of Artificial Intelligence (xAI) has become a mandatory requirement for designing and implementing reliable, interpretable, and ethical AI solutions. However, it has been shown that xAI can enable successful adversarial attacks in the domain of fake news detection, leading to a decrease in AI security. This paper presents an attack scheme that uses an explainable solution to reshape the structure of the original message, allowing the adversary to manipulate the model's prediction while keeping the message's meaning intact.
COMPUTERS & SECURITY
(2024)
Article
Computer Science, Information Systems
Jyoti Prakash Meher, Sourav Biswas, Rajib Mall
Summary: Accurate bug classification is important for speeding up bug triage, code inspection, and repair tasks. To improve classification, this study proposes a novel bug classification approach based on deep learning. The approach includes building a bug taxonomy with eight bug classes using keywords, annotating a large set of bug resolution reports, and utilizing attention-based classification techniques. Experimental results show that the proposed technique outperforms existing methods in terms of F1-Score by an average of 16.88% on the considered dataset.
INFORMATION AND SOFTWARE TECHNOLOGY
(2024)
Article
Computer Science, Information Systems
Md. Shamsujjoha, John Grundy, Hourieh Khalajzadeh, Qinghua Lu, Li Li
Summary: This paper investigates the challenges and benefits of incorporating human aspects into eHealth app development and usage from the perspectives of developers and end-users. The study used a mixed-method approach and gathered data from online surveys and interviews. The findings suggest that addressing human aspects throughout the app development life-cycle is beneficial for more effective eHealth apps.
INFORMATION AND SOFTWARE TECHNOLOGY
(2024)
Article
Computer Science, Information Systems
Anton Yeshchenko, Jan Mendling
Summary: This paper presents the development of event sequence data analysis techniques in different fields and proposes an integrated framework to facilitate collaboration and research synergy across various domains.
INFORMATION SYSTEMS
(2024)
Article
Computer Science, Information Systems
Chao Liu, Runfeng Cai, Yiqun Zhou, Xin Chen, Haibo Hu, Meng Yan
Summary: This paper conducts an empirical study on the implementation issues of deep learning frameworks, focusing on relevant questions on Stack Overflow. The study identifies various implementation issues and constructs a taxonomy, revealing that data processing, model setting, model training, and model prediction are the most common categories. The paper also provides suggestions for future research and aims to help developers and researchers understand these issues better.
INFORMATION AND SOFTWARE TECHNOLOGY
(2024)
Article
Computer Science, Information Systems
Pilsu Jung, Seonah Lee, Uicheon Lee
Summary: This study proposes an automated code-based approach (ActSPL) for reusing SPL test cases by utilizing source code and test cases. The results show that ActSPL achieves high precision and recall, and significantly reduces the time required for testing a new product.
INFORMATION AND SOFTWARE TECHNOLOGY
(2024)
Article
Computer Science, Information Systems
Binghui Zou, Chunjie Cao, Longjuan Wang, Sizheng Fu, Tonghua Qiao, Jingzhang Sun
Summary: The ongoing struggle between security researchers and malware has led to the exploration of using convolutional neural networks and capsule networks for classification and identification of malware. However, training these networks requires a significant amount of data and parameters, and the research on capsule networks is still in its early stages, posing challenges.
COMPUTERS & SECURITY
(2024)
Article
Computer Science, Information Systems
Shion Utsumi, Motoki Nakahashi, Kosei Sakamoto, Takanori Isobe
Summary: This paper explores the optimality of byte-based round permutation (RP) in the lightweight block cipher Piccolo from a security standpoint. The authors evaluate the security of differential, linear, impossible differential, and integral attacks for all byte-wise RPs using mixed integer linear programming (MILP). They show that the RP of Piccolo is optimal in terms of the number of rounds required to guarantee security against such attacks. Additionally, they introduce new classes of RPs that require fewer rounds for security against impossible differential attacks, but more rounds for security against differential and linear attacks.
INFORMATION PROCESSING LETTERS
(2024)
Article
Computer Science, Information Systems
Orlenys Lopez-Pintado, Marlon Dumas, Jonas Berx
Summary: Business process simulation is a versatile technique that predicts the impact of changes on process performance. However, previous approaches have limitations due to their treatment of resources as undifferentiated entities. This article addresses this issue by proposing a new simulation approach that treats each resource as an individual entity with its own performance and availability. The article also presents methods for discovering simulation models with differentiated resources and optimizing resource availability calendars. Empirical evaluation demonstrates that differentiated resource models better replicate cycle time distributions and work rhythm, and iterative optimization of resource allocations and calendars leads to improved cost-time tradeoffs.
INFORMATION SYSTEMS
(2024)
Article
Computer Science, Information Systems
Pierre Hoppenot, Zoltan Szigeti
Summary: We demonstrate that if the arc-connectivity of a directed graph, D, is at most k+1/2 and the reorientation of an arc set, F, in D results in a k-arc-connected directed graph, then we can reorient one arc of F without decreasing the arc-connectivity of D. This improvement applies to the cases when k is either 2 or 3, enhancing the corollary of previous results by Fukuda, Prodon, Sakuma and Ito et al.
INFORMATION PROCESSING LETTERS
(2024)
Article
Computer Science, Information Systems
Waheed G. Gadallah, Hosny M. Ibrahim, Nagwa M. Omar
Summary: Software-Defined Network (SDN) separates the control plane from the data plane, improving network flexibility, management, performance, and scalability. This paper proposes an effective technique using deep learning models to detect DDoS attacks in both the control and data planes of SDN. Different features are utilized for detection in the control and data planes, and the technique mitigates DDoS effects by updating user trust values and blocking suspicious senders.
COMPUTERS & SECURITY
(2024)
Article
Computer Science, Information Systems
Naomi Woods, Mikko Siponen
Summary: Users' anxiety about remembering passwords can lead to the adoption of password reuse and modification as memory strategies.
COMPUTERS & SECURITY
(2024)
Article
Computer Science, Information Systems
Nilufer Tuptuk, Stephen Hailes
Summary: In this paper, a novel methodology is proposed to identify vulnerabilities in industrial control systems. The method is evaluated on a benchmark chemical plant simulator and is shown to be effective in identifying vulnerable components and evaluating the performance of existing security mechanisms.
COMPUTERS & SECURITY
(2024)
Article
Computer Science, Information Systems
Zhen Yang, Jacky Wai Keung, Zeyu Sun, Yunfei Zhao, Ge Li, Zhi Jin, Shuo Liu, Yishu Li
Summary: This paper presents MetaCoder, a meta-learning code generation approach that efficiently extracts general-purpose knowledge from large-scale source languages and rapidly adapts to domain-specific scenarios.
INFORMATION AND SOFTWARE TECHNOLOGY
(2024)
Article
Computer Science, Information Systems
Antonio Giovanni Schiavone
Summary: The usage of HTTPS protocol is crucial for secure communication with websites, ensuring the confidentiality, integrity, and authenticity of online data transmissions. The Municipality2HTTPS research project analyzed the implementation of HTTPS in Italian municipalities' websites and identified areas for improvement.
COMPUTERS & SECURITY
(2024)
Article
Computer Science, Information Systems
Hao Ren, Yanhui Li, Lin Chen, Yuming Zhou, Changhai Nie
Summary: This study aims to explore the breakable blocking bugs (BBBs) through quantitative and qualitative analysis. The analysis reveals that BBBs have higher levels of involvement, longer fix time, and more complex source code compared to other bugs. The study also identifies four reasons for breaking blocking relationships between bugs and three measures adopted by developers to break these relationships.
INFORMATION AND SOFTWARE TECHNOLOGY
(2024)
