Article
Computer Science, Information Systems
Heber H. Arcolezi, Sebastien Gambs, Jean-Francois Couchot, Catuscia Palamidessi
Summary: This paper investigates privacy threats against LDP protocols for multidimensional data and evaluates five widely used LDP protocols. It also proposes a countermeasure to improve both utility and robustness. The contributions of this study can assist practitioners in collecting users' statistics privately.
PROCEEDINGS OF THE VLDB ENDOWMENT
(2023)
Article
Mathematics, Interdisciplinary Applications
Yilun Shang
Summary: The study explores the impact of attacks on the core structure of networks, revealing the effects of attack types and number of attacked nodes on network robustness, and demonstrates the role of degree heterogeneity in network resilience and stability.
CHAOS SOLITONS & FRACTALS
(2021)
Article
Computer Science, Information Systems
Meisam Mohammady, Momen Oqaily, Lingyu Wang, Yuan Hong, Habib Louafi, Makan Pourzandi, Mourad Debbabi
Summary: The article discusses the trade-off between privacy protection and data utility, proposing a new method to protect privacy and achieve data utility by generating and analyzing multiple anonymous views. Experimental results show that the approach can significantly reduce information leakage while maintaining high data utility.
ACM TRANSACTIONS ON PRIVACY AND SECURITY
(2021)
Article
Thermodynamics
Na Wei, Wen-Jie Xie, Wei-Xing Zhou
Summary: This study investigates the robustness of the international oil trade network in the face of extreme events and finds that the network's vulnerability stems from regional aggregation. Maintaining stability and security in oil trade requires focusing on economies with significant influence and improving the framework for oil security and trade risk assessment.
Article
Automation & Control Systems
Peijun Wang, Guanghui Wen, Xinghuo Yu, Wenwu Yu, Ying Wan
Summary: This study focuses on synchronization control in complex networks subject to cyber and physical attacks, providing theoretical criteria and algorithmic approaches to ensure synchronization achievement and network security.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2021)
Article
Chemistry, Analytical
Patryk Przybocki, Vassilios G. Vassilakis
Summary: Cybercrime is on the rise worldwide, targeting critical infrastructure like power stations. One concerning trend is the increased use of embedded devices in denial-of-service attacks, posing a significant risk to systems and infrastructures.
Article
Computer Science, Information Systems
Xiaodan Gu, Kai Dong
Summary: This paper investigates semantic attacks in IoT environments and proposes a traffic anonymization method called PD-PAn to defend against semantic attacks, ensuring data utility and privacy.
Article
Computer Science, Artificial Intelligence
Lei Guo, RuiXue Man, YouXi Wu, HongLi Yu, GuiZhi Xu
Summary: This study investigates the anti-injury mechanism of complex spiking neural networks based on the latest findings in brain science, revealing that the topology of the networks plays a significant role in their anti-injury ability.
Article
Computer Science, Information Systems
Harmanjeet Kaur, Nishtha Hooda, Harpreet Singh
Summary: With the rise of social network sites like Twitter, Facebook, and LinkedIn, information sharing has grown significantly. To protect personal information, efficient privacy-preserving techniques like k-anonymization and randomization are used. This paper proposes an improved version of k-degree-anonymization using a hybridization of Neural Network and SVM, called NeuroSVM. The technique preserves the average path length of the graph and reduces the addition of noisy nodes and edges. Experimental results showed that the proposed technique has less distortion in average path length compared to existing techniques, with an accuracy of over 75% and reduced information loss.
JOURNAL OF INFORMATION SECURITY AND APPLICATIONS
(2023)
Article
Chemistry, Multidisciplinary
Fatemeh Amiri, Razaullah Khan, Adeel Anjum, Madiha Haider Syed, Semeen Rehman
Summary: Recent studies have found that data plays a pivotal role in making government policies and business decisions in various organizations. Maintaining privacy while ensuring accurate data for data mining queries remains a challenging task. Existing models like k-anonymity and t-closeness fail to address background knowledge attacks. In this paper, a utility-based hierarchical algorithm (UHRA) is proposed to produce k-anonymous t-closed data, which effectively prevents background knowledge attacks and satisfies privacy requirements. Experimental results demonstrate superior data utility and privacy preservation compared to existing algorithms.
APPLIED SCIENCES-BASEL
(2023)
Article
Computer Science, Information Systems
Ali Kazemy, Ramasamy Saravanakumar, James Lam
Summary: This paper discusses the master-slave synchronization issue of neural networks under mixed-type communication attacks, proposing a synchronization strategy based on static output feedback controller and event-triggered scheme, and investigating various types of network attacks in a unified Markovian jump framework. Design criteria are derived using Lyapunov-Krasovskii theory and stochastic analysis techniques, formulated as matrix inequalities, and a convex optimization algorithm is proposed to design the static output feedback controller. Finally, the effectiveness of the event-triggered static output feedback controller is demonstrated through two chaotic examples.
INFORMATION SCIENCES
(2021)
Article
Computer Science, Hardware & Architecture
Luoyi Fu, Jiapeng Zhang, Shan Qu, Huquan Kang, Xinbing Wang, Guihai Chen
Summary: This paper investigates how the structural properties of different network models affect de-anonymizability. It discovers that the automorphic degree and homomorphic degree universally determine the de-anonymizability of social networks. The paper also provides explicit parametric bounds for three classic network models and demonstrates the practical relevance of the theoretical results.
IEEE-ACM TRANSACTIONS ON NETWORKING
(2022)
Article
Construction & Building Technology
G. Lifshitz Sherzer, G. Ye, E. Schlangen, K. Kovler
Summary: The article describes a multi-scale formulation to estimate the strength reduction of concrete walls exposed to brine attack and provides a method for predicting concrete response. Simulation results indicate that under certain conditions, the trench wall will remain stable.
CONSTRUCTION AND BUILDING MATERIALS
(2022)
Article
Engineering, Industrial
Ruimeng Li, Naiding Yang, Hao Yi, Na Jin
Summary: This paper develops a design change risk propagation model with gray attack information based on complex network theory. Four kinds of gray attack strategies are provided and the robustness of the CPD project is analyzed under different gray attacks. The results show that the project is most robust under the small out-degree attack and most vulnerable under the large out-degree attack. Increasing the gray level of information improves the project robustness under large out-degree attack, but reduces it under small out-degree attack under certain circumstances. Parameters sigma and pi have threshold values that keep the project robustness stable.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2023)
Article
Geosciences, Multidisciplinary
Shuchao Cao, Jialong Qian, Xiaolian Li, Jie Ni
Summary: This paper investigates the evacuation of heterogeneous pedestrians, including rational individuals and herding occupants, under terrorist attacks using an extended floor field model. The study analyzes evacuation time and casualties in different scenarios. The results show that pedestrians need to maintain a proper escape intention when avoiding terrorists, and herding behavior has a negative effect on evacuation, leading to more casualties. The presence of rational pedestrians facilitates the evacuation of herding occupants in mixed crowds.
INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION
(2022)
