Article
Computer Science, Information Systems
Md. Farhan Haque, Ram Krishnan
Summary: Cyber threat sharing is crucial for timely defense against cyber attacks. This paper emphasizes the importance of sharing threat intelligence in a controlled and automated manner, and proposes Relationship Based Access Control (ReBAC) as a suitable model. By developing an automated approach for threat detection and sharing, along with implementing an Automated Cyber Defense System in a cloud based environment, effective mitigation of cyber threats can be achieved.
INFORMATION SYSTEMS FRONTIERS
(2021)
Article
Computer Science, Information Systems
Shikhar Verma, Yuichi Kawamoto, Nei Kato
Summary: To address security threats in WLAN technologies for IoT, regular vulnerability assessments of IoT devices are necessary, along with optimized port scanning processes to ensure the effectiveness of IPSec services and balance network performance.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Energy & Fuels
Xinhui Zhong
Summary: Digital transformation is crucial for the development of modern enterprises, and the Internet of Things (IoT) serves as a vital bridge between the physical power grid and the digital power grid in the digital transformation of power enterprises. The IoT platform plays a pivotal role in this process.
Article
Computer Science, Information Systems
Taeeun Kim, Hwankuk Kim
Summary: IoT devices are vulnerable to hacking, leading researchers to propose using Internet-wide scanning techniques to discover and manage insecure IoT devices. Remote scanning studies on the Internet face practical limitations, such as lack of information or filtering by network security devices.
IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS
(2021)
Article
Multidisciplinary Sciences
Lu Yu, Yuliang Lu, Yi Shen, Zulie Pan, Hui Huang
Summary: This paper proposes a data-aware program-wide diffing method for vulnerability detection in IoT devices, utilizing semantic features extraction and Earth mover distance calculation for function similarity. Experimental results demonstrate the feasibility and effectiveness of the method across optimization levels and architectures.
ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING
(2022)
Article
Engineering, Civil
Imran Ashraf, Yongwan Park, Soojung Hur, Sung Won Kim, Roobaea Alroobaea, Yousaf Bin Zikria, Summera Nosheen
Summary: This article presents the cyber security threats and their potential impact and loss scale on the maritime industry. It provides recommendations and countermeasures to mitigate the impact of cyber security breaches, emphasizing the necessity of efficient security policies for the future.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Multidisciplinary Sciences
Anton Konev, Alexander Shelupanov, Mikhail Kataev, Valeriya Ageeva, Alina Nabieva
Summary: This review explores various literature on confidentiality- and integrity-aware system design methodologies and threat classification methods, and identifies the shortcomings of existing methodologies. The existing methodologies only superficially cover the description of system models and threats, and it is necessary to develop a more complete abstract model to adapt to various organizations and protect against most threats.
Article
Mathematical & Computational Biology
Lu Yu, Yuliang Lu, Yi Shen, Jun Zhao, Jiazhen Zhao
Summary: The paper introduces a program-wide binary diffing method based on a neural network model, which improves comparison accuracy and efficiency through top-down and bottom-up analysis processes.
MATHEMATICAL BIOSCIENCES AND ENGINEERING
(2022)
Article
Biodiversity Conservation
Hannes Gaisberger, Tobias Fremout, Thea So, Bansa Thammavong, Chaloun Bounithiphonh, Tran Thi Hoa, Zheng Yongqi, Tania Kanchanarak, Suchitra Changtragoon, Sineath Sreng, Huang Ping, Tin Hang Hung, Pyae Pyae Win, Ida Hartvig, Ida Theilade, David Boshier, John MacKay, Chris Kettle, Riina Jalonen
Summary: Understanding the impact of multiple anthropogenic threats is crucial for estimating population decline and implementing effective conservation actions. A study on three Asian rosewood species found that these species face significant threats, with overexploitation being the most important threat followed by habitat conversion and fire. The study proposes priority areas for conservation and suggests specific actions to improve the effectiveness of current conservation measures.
BIOLOGICAL CONSERVATION
(2022)
Article
Business
Wei Gao, Qingqing Guo, Ning Jiang
Summary: Facial recognition payment (FRP) is an emerging payment approach that provides superior user experience and is changing our daily life. However, the sensitive information collected by the FRP service provider may create customers' information vulnerability and hinder the use of FRP. This study empirically examines the impact of information vulnerability on customers' FRP continuance usage intention and the moderating roles of information use fairness and information use transparency.
ELECTRONIC COMMERCE RESEARCH AND APPLICATIONS
(2023)
Article
Computer Science, Information Systems
Juan A. Lopez-Morales, Juan A. Martinez, Antonio F. Skarmeta
Summary: The application of pressurized irrigation technologies has transformed the irrigation sector significantly. Irrigation, together with agricultural machinery, has become the primary energy consumer within the agri-food sector. Improving energy efficiency and reducing costs are key challenges, with energy audit and IoT-based systems playing a crucial role in achieving these goals.
Article
Computer Science, Information Systems
Mohammed Alshehri
Summary: Cyber Threat Intelligence (CTI) is essential for understanding and predicting cyber-attacks; information exchange and collaboration play a crucial role in global solutions; a scoring model for information decay can enhance threat indicator detection efficiency.
CMC-COMPUTERS MATERIALS & CONTINUA
(2021)
Article
Computer Science, Information Systems
Navdeep S. Chahal, Preeti Bali, Praveen Kumar Khosla
Summary: The increasing number of attacks has led to a growing interest in cybersecurity systems. Various organizations are willing to exchange information about threats, incidents, and mitigation strategies with security detection tools. However, existing security detection techniques are insufficient in detecting complicated attacks. This paper proposes a novel intelligent open-source scanning tool that addresses the need for continuous vulnerability assessment in cybersecurity detection processes and has shown promising results in experiments.
COMPUTERS & SECURITY
(2022)
Article
Computer Science, Information Systems
Yuan Cheng, Baojiang Cui, Chen Chen, Thar Baker, Tao Qi
Summary: This paper proposes a new approach that combines ambient information with binary code information to generate an ACFG for discovering vulnerabilities from binaries accurately. The transformed graph is analyzed using a deep neural network. The experiment shows that this method outperforms state-of-the-art methods in terms of accuracy, efficiency, and scalability, with an average accuracy of over 80% on real-world vulnerability datasets.
COMPUTER COMMUNICATIONS
(2023)
Article
Computer Science, Information Systems
Munan Li, Hongbo Liu, Xiangdong Jiang, Zheng Zhao, Tianhao Zhang
Summary: This paper proposes a novel unsupervised semantic learning model called SENSE for cross-platform vulnerability search. SENSE outperforms state-of-the-art methods in terms of binary search accuracy by pre-training semantic and graph learners and employing unsupervised batch-wise sampling with maximum mutual information loss.
COMPUTERS & SECURITY
(2023)
