Optimal DoS Attack Scheduling in Wireless Networked Control System

By Heng Zhang, Peng Cheng, Ling Shi, Jiming Chen. IEEE Transactions on Control Systems Technology, 2016

533 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Control and Systems Engineering

View Paper: https://www.semanticscholar.org/paper/129236f56a989af9ae295db803b3000f5f8b8852

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Networks and Communications

1. Chen Peng
2. Xiaohua Ge
3. Hongtao Sun
4. Qing-Long Han
5. Dong Yue
6. Ling Shi
7. W. Zheng
8. Hongyi Li

In Control and Systems Engineering

1. Chen Peng
2. Xiaohua Ge
3. Hongtao Sun
4. Hongyi Li
5. Qing-Long Han
6. W. Zheng
7. Dong Yue
8. Ling Shi

Citations in the corpus

• SINR-Based DoS Attack on Remote State Estimation: A Game-Theoretic Approach (2017, methodology): “In many existing works, such as [5], [9], [12], the DoS attack is modelled as a binary process considering sending or not for the sensor and blocking or not for the attacker.”
• Energy Storage Sharing in Smart Grid: A Modified Auction-Based Approach (2015, unknown): “Studies of other aspects of smart grid can be found in [30]–[36].”
• Distributed Attack Detection and Secure Estimation of Networked Cyber-Physical Systems Against False Data Injection Attacks and Jamming Attacks (2018, methodology): “Note that a frequently used DoS technique is to launch jamming attacks on communication channels by interfering with their radio frequencies [14], [15].”
• Resilient Event-Triggered Controller Synthesis of Networked Control Systems Under Periodic DoS Jamming Attacks (2019, background): “Among the existing works on networked control under DoS attacks, to name a few, security-constrained optimal control strategy is investigated in [6] and [9], the model-based resilient controller is studied in [10], the “maximally robust” control architectures are designed in [11], switched resilient”
• Secure Cooperative Event-Triggered Control of Linear Multiagent Systems Under DoS Attacks (2020, background): “Gupta et al. [9], Zhang et al. [13], Teixeira et al. [14], Shisheh et al. [16], Cetinkaya et al. [17], De. Persis and Tesi [18], Chen et al. [19] studied the secure control against DoS attacks in a centralized setting.”
• Event-Triggered Consensus Control for Multi-Agent Systems Against False Data-Injection Attacks (2019, background): “For example, in [37]–[39], DoS attacks on controlled system have been discussed, where the DoS attacks prevent information exchange by sending a large amount of useless data.”
• A Survey on Security Communication and Control for Smart Grids Under Malicious Cyber Attacks (2019, background): “From the perspectives of both attack and defense, the choices of attack and defense strategies in the studies [64]–[66] are all based on the results of competition between the attacker and defender, and they fail to describe this interactive decisionmaking process between the two sides.”
• Decentralized Adaptive Fuzzy Secure Control for Nonlinear Uncertain Interconnected Systems Against Intermittent DoS Attacks (2019, background): “Due to the energy constraint of adversaries [16], [17], or several provisions such as spreading techniques and high-pass filtering to mitigate DoS attacks [29], [30], the DoS attacks usually arrive in an intermittent or random manner [31].”
• Optimal Denial-of-Service Attack Scheduling With Energy Constraint Over Packet-Dropping Networks (2018, background): “They also proposed the optimal DoS attack schedules subject to insufficient energy such that the linear quadratic Gaussian control cost function is maximized [19].”
• Distributed impulsive synchronization of Lur'e dynamical networks via parameter variation methods (2018, methodology): “(27) From Definition 1 and the evaluation of e(t) in Equation 27, one could derive the conclusion that the exponential synchronization between the coupled stochastic Lur'e network (1) and leader Lur'e system (2) is achieved by applying the distributed impulsive controller (5).”