Review
Computer Science, Theory & Methods
Elakkiya Ellavarason, Richard Guest, Farzin Deravi, Raul Sanchez-Riello, Barbara Corsetti
Summary: This article provides an in-depth analysis of touch-dynamics based behavioural biometrics, emphasizing the importance of usability on authentication performance. It highlights the need to focus on user acceptance and performance studies during performance evaluations, comparing accuracy and error rates across various research works.
ACM COMPUTING SURVEYS
(2021)
Article
Computer Science, Information Systems
Luis de-Marcos, Jose-Javier Martinez-Herraiz, Javier Junquera-Sanchez, Carlos Cilleruelo, Carmen Pages-Arevalo
Summary: Continuous authentication (CA) is a process of verifying user identity regularly without their active participation. By training machine learning classifiers with data like typing events, predictions of user identity can be returned with a small number of key events and measurements. Among the various classifiers tested, ensemble algorithms, particularly GBC, showed the best statistical results for the CA mobile keystroke classification problem.
Article
Chemistry, Multidisciplinary
Najwa Altwaijry
Summary: This paper investigates the influence of typing language on keystroke dynamics. The results show that keystroke dynamics is influenced by the language being used, and bilingual users need to have two profiles created.
APPLIED SCIENCES-BASEL
(2023)
Article
Computer Science, Artificial Intelligence
Zhigang Gao, Wenjie Diao, Yucai Huang, Ruichao Xu, Huijuan Lu, Jianhui Zhang
Summary: The paper proposes a new user identity authentication method named UIKI, which consists of two phases: valid user modeling and runtime user authentication. Experimental results show that UIKI has high accuracy, low overhead, and is suitable for user authentication of mobile devices.
PATTERN RECOGNITION LETTERS
(2021)
Article
Chemistry, Analytical
Xiujuan Wang, Yutong Shi, Kangfeng Zheng, Yuyang Zhang, Weijie Hong, Siwei Cao
Summary: In this article, a user authentication method called SIURUA is proposed, which utilizes scene-irrelated features and user-related features for user identification. By fusing these two types of features, the method improves the accuracy of user authentication.
Article
Computer Science, Information Systems
Yutong Shi, Xiujuan Wang, Kangfeng Zheng, Siwei Cao
Summary: This paper presents a novel method for user authentication using keystroke dynamics and mouse dynamics, which utilizes heterogeneous domain adaptation to handle complex real-environment HCI data. Experimental results demonstrate the effectiveness of the proposed method.
MULTIMEDIA SYSTEMS
(2023)
Review
Computer Science, Hardware & Architecture
Ahmad Zairi Zaidi, Chun Yong Chong, Zhe Jin, Rajendran Parthiban, Ali Safaa Sadiq
Summary: This paper discusses the development of mobile device authentication mechanisms and the limitations of traditional authentication methods such as passwords and fingerprint recognition, while highlighting the advantages of touch biometric as a continuous authentication mechanism. It also emphasizes the challenges and opportunities faced in the current touch-based continuous mobile device authentication domain.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2021)
Article
Computer Science, Information Systems
Feriel Cherifi, Kamal Amroun, Mawloud Omar
Summary: This paper presents a robust multimodal authentication system based on ear and arm gesture biometric modalities, demonstrating good equal error rate in real-world applications.
MULTIMEDIA TOOLS AND APPLICATIONS
(2021)
Article
Computer Science, Artificial Intelligence
Orcan Alpar
Summary: Investigating new intelligent solutions for user identification and authentication is vital for enhancing password security, with frequency-based solutions showing better retention of unique biometric characteristics without the risk of convergence.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Computer Science, Information Systems
Abbas Acar, Hidayet Aksu, A. Selcuk Uluagac, Kemal Akkaya
Summary: Continuous authentication, such as Wearable-Assisted Continuous Authentication (WACA), improves the reliability of user identity verification throughout a session, overcoming limitations of conventional one-time login systems. WACA utilizes sensor-based keystroke dynamics to transparently and periodically compare authentication data with the initial user profile, ensuring the current user is the same as the initially logged-in user. Empirical evaluation shows WACA's feasibility, low error rate, minimal computational overhead, and high accuracy in identifying insider threats and resisting powerful adversaries. The usability and efficiency of WACA propose potentially transformative implications in the authentication field.
IEEE TRANSACTIONS ON MOBILE COMPUTING
(2021)
Article
Automation & Control Systems
Andrea F. Abate, Lucia Cimmino, Immacolata Cuomo, Mario Di Nardo, Teresa Murino
Summary: Smart factories are crucial for the spread of Industry 4.0 and economic growth, but work accidents remain a common issue. This article proposes a novel framework using multiple sensors to monitor biometric features in order to improve safety measures in smart factories.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2022)
Article
Chemistry, Analytical
Priscila Morais Argolo Bonfim Estrela, Robson de Oliveira Albuquerque, Dino Macedo Amaral, William Ferreira Giozza, Rafael Timoteo de Sousa Junior
Summary: This study proposes an improvement to the Biotouch framework by utilizing multiple scopes to enhance reasoning models, evaluates the performance of the model in various authentication processes, and demonstrates the feasibility of the continuous multiple-scope authentication framework as an effective security measure for banking applications.
Article
Computer Science, Information Systems
Iyyakutti Iyappan Ganapathi, Syed Sadaf Ali, Uttam Sharma, Pradeep Tomar, Muhammad Owais, Naoufel Werghi
Summary: Ear biometrics is a rapidly developing field in computer vision that has advantages over existing biometric authentication methods. By combining 3D and 2D ear images and utilizing a covariance matrix for keypoint detection and description, this proposed method achieves superior performance in occlusion, noise, and pose variations. The registration error serves as the matching score. © 2023 Published by Elsevier Ltd.
COMPUTERS & SECURITY
(2023)
Article
Computer Science, Artificial Intelligence
Bayan Alharbi, Hanan S. Alshanbari
Summary: Information security has become an integral part of the information technology industry due to advancements in technology. Authentication plays a crucial role in ensuring security, with biometrics-based identification using physiological and behavioral markers. Various systems require reliable personal recognition schemes to validate the identity of users accessing services. This case study proposes an enhanced multimodal biometric authentication system using voice and face recognition, which reduces the equal error rate and achieves better accuracy than previous approaches.
PEERJ COMPUTER SCIENCE
(2023)
Article
Computer Science, Artificial Intelligence
Giuseppe Stragapede, Ruben Vera-Rodriguez, Ruben Tolosana, Aythami Morales
Summary: Mobile behavioral biometrics has gained popularity in research, showing promising results in authentication by combining touchscreen and background sensor data. However, it is uncertain whether state-of-the-art classifiers can differentiate between users and devices. This article introduces BehavePassDB, a new database structured into separate acquisition sessions and tasks to mimic common mobile Human-Computer Interaction. The authors propose a standard experimental protocol and benchmark, and evaluate a system based on LSTM architecture with triplet loss and modality fusion at the score level.
PATTERN RECOGNITION
(2023)
Article
Computer Science, Information Systems
Yuxiang Hong, Steven Furnell
Summary: Psychological and behavioral characteristics are important factors in causing information security incidents. This study explores the influence of organizational structures on information security policy compliance behavioral intention and finds that perceived organizational formalization significantly affects cognitive processes, behavioral habits, and deterrent certainty. The study suggests the design of formal rules, procedures, and communications to improve employee information security policy compliance habits and intentions.
JOURNAL OF COMPUTER INFORMATION SYSTEMS
(2022)
Article
Computer Science, Information Systems
Karl van der Schyff, Stephen Flowerday, Steven Furnell
COMPUTERS & SECURITY
(2020)
Article
Computer Science, Information Systems
Karl van der Schyff, Stephen Flowerday, Steven Furnell
COMPUTERS & SECURITY
(2020)
Article
Computer Science, Information Systems
Hind Alobaidi, Nathan Clarke, Fudong Li, Abdulrahman Alruban
Summary: Securing smartphones is crucial as they become vulnerable to cybercrime. Gait authentication, an non-intrusive method, has shown promise in recognizing users in real-world environments.
COMPUTERS & SECURITY
(2022)
Editorial Material
Computer Science, Information Systems
Nathan Clarke, Steven Furnell
INFORMATION AND COMPUTER SECURITY
(2023)
Proceedings Paper
Computer Science, Interdisciplinary Applications
Jan Stodt, Christoph Reich, Nathan Clarke
Summary: Artificial intelligence has enormous potential in healthcare and medical technology, and explainability is crucial for certification procedures. This study adapts FastCAM for improving the detection of medical instruments in endoscopy images.
COMPUTATIONAL SCIENCE - ICCS 2022, PT III
(2022)
Proceedings Paper
Computer Science, Interdisciplinary Applications
Hendrik Kuijs, Christoph Reich, Martin Knahl, Nathan Clarke, Ivana Ognjanovic
Summary: This paper discusses the necessity of special access control rules for AAL systems in emergency situations, highlighting the importance of personally identifiable information (PII) for helpers and emergency doctors.
2022 11TH MEDITERRANEAN CONFERENCE ON EMBEDDED COMPUTING (MECO)
(2022)
Article
Computer Science, Information Systems
Joakim Kavrestad, Allex Hagberg, Marcus Nohlberg, Jana Rambusch, Robert Roos, Steven Furnell
Summary: Cybersecurity is a crucial issue, and individuals play a significant role in ensuring secure behavior. This paper evaluates two promising methods of Information Security Awareness Training (ISAT) in supporting users' secure behavior, and suggests future research ideas of combining training with other support systems.
Article
Computer Science, Theory & Methods
Georgios Vranopoulos, Nathan Clarke, Shirley Atkinson
Summary: This paper proposes an automated approach for metadata identification and enrichment in describing Big Data. Through experimentation and the use of algorithmic techniques, it is shown that this approach can improve the accuracy and efficiency of data identification.
JOURNAL OF BIG DATA
(2022)
Article
Computer Science, Information Systems
Bilal Naqvi, Nathan Clarke, Jari Porras
Summary: This paper introduces an integrative framework to address security and usability conflicts throughout the system development lifecycle. By interviewing industry practitioners and validating the framework through a workshop, design patterns are created to assist system designers and developers in making informed decisions.
INFORMATION AND COMPUTER SECURITY
(2021)
Article
Computer Science, Information Systems
Fayez Ghazai Alotaibi, Nathan Clarke, Steven M. Furnell
Summary: This paper proposes a system for improving security management and awareness for home users through creating and assigning different security policies for digital devices. Experts have evaluated the proposed approach positively, agreeing that it is usable, feasible, and effective in enhancing security management and awareness for home users. The study offers a framework and mock-up design to strengthen information security for home users.
INFORMATION AND COMPUTER SECURITY
(2021)
Article
Computer Science, Information Systems
Adele Da Veiga, Ruthea Vorster, Fudong Li, Nathan Clarke, Steven M. Furnell
INFORMATION AND COMPUTER SECURITY
(2020)
Proceedings Paper
Computer Science, Software Engineering
Abdulaziz Altamimi, Nathan Clarke, Steven Furnell, Fudong Li
THIRD CENTRAL EUROPEAN CYBERSECURITY CONFERENCE (CECC 2019)
(2019)
Article
Computer Science, Information Systems
Kashan Ahmed, Syed Khaldoon Khurshid, Sadaf Hina
Summary: This paper mainly introduces the construction of the cyber threat intelligence knowledge graph and the information extraction technique. By using joint extraction technique, it solves the problem of traditional techniques becoming ineffective due to the increasing size of CTI data. Experimental results show that this technique outperforms state-of-the-art models in knowledge triple extraction on CTI data and improves the F1 score.
COMPUTERS & SECURITY
(2024)
Article
Computer Science, Information Systems
Xinlong He, Yang Xu, Sicong Zhang, Weida Xu, Jiale Yan
Summary: This paper proposes a new membership inference attack method in federated learning, which utilizes data poisoning and sequence prediction confidence. The attack is effective and results in minimal overall model performance degradation.
COMPUTERS & SECURITY
(2024)
Article
Computer Science, Information Systems
Tieming Chen, Huan Zeng, Mingqi Lv, Tiantian Zhu
Summary: In this paper, the authors propose a deep learning based dynamic malware detection method called CTIMD, which integrates threat knowledge from CTIs into the learning process of API call sequences with runtime parameters. Experimental results show that CTIMD outperforms existing methods in terms of performance.
COMPUTERS & SECURITY
(2024)
Article
Computer Science, Information Systems
Wonwoo Choi, Minjae Seo, Seongman Lee, Brent Byunghoon Kang
Summary: This paper proposes SUM, a backward-edge control flow protection scheme for ARM Cortex-M processors. It combines MPU and the overlooked hardware feature FaultMask to achieve efficient and robust protection. The empirical evaluation shows minimal runtime overhead for the proposed solution.
COMPUTERS & SECURITY
(2024)
Article
Computer Science, Information Systems
Liliana Ribeiro, Ines Sousa Guedes, Carla Sofia Cardoso
Summary: Phishing susceptibility is influenced by individual and contextual factors. The study found that individuals who perceive themselves as capable of detecting phishing and those who use online services more frequently are more susceptible to phishing. However, technology competencies and other individual variables do not predict phishing susceptibility.
COMPUTERS & SECURITY
(2024)
Article
Computer Science, Information Systems
Wenjie Wang, Yuanhai Shao, Yiju Wang
Summary: In this paper, we investigate the adversarial perturbations of twin support vector machines (TWSVMs) and propose an optimization framework, which provides explicit solutions to increase the interpretability of the conclusion and convenience for calculation.
COMPUTERS & SECURITY
(2024)
Article
Computer Science, Information Systems
Snofy D. Dunston, V. Mary Anita Rajam
Summary: This paper proposes a novel adversarial attack technique that can synthesize adversarial images to mislead deep learning models, and also studies interpretability plots. The research findings show that the proposed attack technique influences the interpretability plots, regardless of the success of the attack.
COMPUTERS & SECURITY
(2024)
Article
Computer Science, Information Systems
Junchen Li, Guang Cheng, Zongyao Chen, Peng Zhao
Summary: Protocol Reverse Engineering (PRE) is a direct approach for analyzing unknown traffic. This paper proposes a method for clustering unknown traffic based on private protocol labels, and the experimental results demonstrate its advantages on real-world network traffic.
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
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
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
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
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
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
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)
