Article
Computer Science, Information Systems
Tohari Ahmad, Alek Nur Fatman
Summary: The rapid development of information technology has made security a crucial factor. This study addresses the challenges of quality and capacity in hiding data within video files by exploring histograms and prediction errors. Experimental results show that this method outperforms other algorithms in terms of peak signal to noise ratio (PSNR) and can hold more bits without sacrificing stego quality. Additionally, this approach is reversible, allowing for extraction of both cover and secret from the stego file.
JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES
(2022)
Article
Computer Science, Information Systems
Xin Lu, Ruochen Dong, Qing Wang, Lizhe Zhang
Summary: This paper studies the basic theories and key technologies of ATM information security assurance, designs a credible security architecture, and provides comprehensive and systematic security assurance for networked ATM. The paper investigates the dynamic and complex data processing process of the ATM system, analyzes the complex interaction between its cyber and physical systems, and constructs the networked ATM cyber-physical fusion system model and threat model. Furthermore, it proposes a game model of networked ATM using a Bayesian Nash equilibrium strategy and establishes an information security assurance architecture based on blockchain technology.
Article
Computer Science, Information Systems
Seungwon Jung, Seunghee Seo, Yeog Kim, Changhoon Lee
Summary: This paper discusses the interference of anti-memory forensics techniques in the memory acquisition process and proposes a memory layout acquisition method that is resistant to these techniques to ensure the reliability of memory imaging.
Article
Computer Science, Interdisciplinary Applications
Jacob Willem Abraham Witsenboer, Klaas Sijtsma, Fedde Scheele
Summary: This study explores the development of cyber secure behavior among Dutch students during their school career. The findings reveal a lack of attention to cyber security in the Dutch school curriculum, with students relying mainly on experience, internet instructions, parents, and siblings to shape their online behavior. Additionally, many students exhibit increasingly reckless behavior over time.
COMPUTERS & EDUCATION
(2022)
Article
Computer Science, Theory & Methods
Yuantian Miao, Chao Chen, Lei Pan, Qing-Long Han, Jun Zhang, Yang Xiang
Summary: In recent years, stealing attacks against controlled information using machine learning algorithms have emerged as a significant cyber security threat, making detection and defense challenging and urgent. This survey reviews the recent advances in this type of attack, categorizes them into three types based on the targeted controlled information, and proposes countermeasures focusing on detection, disruption, and isolation for effective protection.
ACM COMPUTING SURVEYS
(2021)
Article
Education, Scientific Disciplines
Jessica L. Kamerer, Donna S. Mcdermott
Summary: The healthcare industry is at risk of cybercrime, which can lead to financial loss and breach of privacy. Nurses, as frontline healthcare workers, should receive education about the risks and their role in preventing cyber-attacks.
NURSE EDUCATION TODAY
(2023)
Article
Physics, Multidisciplinary
C. T. J. Dodson, John Soldera, Jacob Scharcanski
Summary: Secure user access is enabled by fingerprint or face recognition, while efficient classification and feature retrieval processing for large secure digital object datasets involve methods applicable to multidimensional data represented through probability distributions. Information geometry provides a context for analytic work, representing probability distributions as Riemannian manifolds to identify features, compute dissimilarities, and construct object neighborhoods. A new face recognition method utilizing geodesic distances between RGB Gaussians and joint probabilities shows higher success in recognition rates compared to existing methods.
Article
Computer Science, Information Systems
Sotirios Brotsis, Konstantinos P. Grammatikakis, Dimitrios Kavallieros, Antonio I. Mazilu, Nicholas Kolokotronis, Konstantinos Limniotis, Costas Vassilakis
Summary: With the increasing number of security incidents targeting the Internet of Things (IoT), IoT forensics has emerged as a branch of digital forensics. This paper proposes the integration of blockchain into IoT forensics to address challenges related to digital evidence authenticity, integrity, confidentiality, and privacy. The proposed blockchain-enabled platform achieves high throughput, low latency, and zero error rate in a realistic smart home environment.
INTERNET OF THINGS
(2023)
Article
Chemistry, Analytical
Farhan Ullah, Shamsher Ullah, Muhammad Rashid Naeem, Leonardo Mostarda, Seungmin Rho, Xiaochun Cheng
Summary: This paper presents a malware detection system based on word2vec-based transfer learning and multi-model image representation. The proposed method combines the textual and texture features of network traffic to improve the detection effectiveness, and its effectiveness is verified through experiments.
Article
Engineering, Marine
Stavros Karamperidis, Chronis Kapalidis, Tim Watson
Summary: Maritime cyber security is identified as an emerging issue that demands immediate attention by the International Maritime Organization (IMO). Feedback from global shipping professionals reveals varying perceptions and approaches towards cyber security within the industry. Data collected from focus groups in Europe and Asia show differences in how cyber security is perceived based on technology adoption maturity, with the COVID-19 pandemic further emphasizing these disparities. The findings provide valuable intelligence for maritime decision makers in meeting IMO requirements and preparing for cyber risks.
JOURNAL OF MARINE SCIENCE AND ENGINEERING
(2021)
Review
Psychology, Multidisciplinary
Ahmed A. Moustafa, Abubakar Bello, Alana Maurushat
Summary: The term 'information security' has been replaced by the more generic term 'cybersecurity'. This paper aims to show that behavioral sciences focused on user behavior can provide key techniques to enhance cybersecurity. Research suggests that computer system users possess varying cognitive abilities which determine their capability to counter information security threats.
FRONTIERS IN PSYCHOLOGY
(2021)
Article
Computer Science, Information Systems
Feng Ding, Guopu Zhu, Yingcan Li, Xinpeng Zhang, Pradeep K. Atrey, Siwei Lyu
Summary: The study shows that DeepFake technology may pose a potential threat, so researchers are working on developing anti-forensics methods. The GAN model proposed in this paper can effectively combat DeepFake forensics detectors, generate high-quality anti-forensics videos, significantly boosting the level of DeepFake anti-forensics.
IEEE TRANSACTIONS ON MULTIMEDIA
(2021)
Article
Computer Science, Artificial Intelligence
Xing Gao, Siyu Gong, Ying Wang, Xifan Wang, Manting Qiu
Summary: This paper examines the strategic interaction between firms and hackers in a resource sharing environment and finds that stricter security standards should be formulated from a socially optimal standpoint. It also suggests that compensation mechanisms may harm each firm.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Computer Science, Theory & Methods
Antonia Nisioti, George Loukas, Aron Laszka, Emmanouil Panaousis
Summary: Cyber attacks with multiple attack actions pose challenges to forensic investigations, where investigators must rely on experience and training to choose the next steps. By applying constrained optimization techniques, the efficiency in selecting the next step can be improved, impacting the overall cost of the investigation.
IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY
(2021)
Review
Computer Science, Artificial Intelligence
Kim Strandberg, Nasser Nowdehi, Tomas Olovsson
Summary: A modern vehicle's complexity and wireless connectivity to the Internet, other vehicles, and infrastructure highlight the need for research in automotive digital forensics, especially with the risk of cyber attacks and accidents involving autonomous vehicles. Failures in automated driving functions may stem from hardware, software, and cybersecurity issues, making it crucial to determine and investigate their causes. However, automotive digital forensics is a relatively new field with limited monitoring systems in vehicles. This study provides the first systematic literature review, assessing over 300 papers between 2006 and 2021, categorizing them, and mapping forensically relevant data, enabling practitioners and researchers to access relevant work and guide investigations.
IEEE TRANSACTIONS ON INTELLIGENT VEHICLES
(2023)
