The protection of cyber Intellectual Property (IP) such as web content is an increasingly critical concern.The rise of large language models (LLMs) with online retrieval capabilities enables convenient access to information but often undermines the rights of original content creators.As users increasingly rely on LLM-generated responses, they gradually diminish direct engagement with original information sources, which will significantly reduce the incentives for IP creators to contribute, and lead to a saturating cyberspace with more AIgenerated content.In response, we propose a novel defense framework that empowers web content creators to safeguard their web-based IP from unauthorized LLM real-time extraction and redistribution by leveraging the semantic understanding capability of LLMs themselves.Our method follows principled motivations and effectively addresses an intractable black-box optimization problem.Real-world experiments demonstrated that our methods improve defense success rates from 2.5% to 88.6% on different LLMs, outperforming traditional defenses such as configuration-based restrictions.

Federated Learning (FL) faces two major issues: privacy leakage and poisoning attacks, which may seriously undermine the reliability and security of the system. Overcoming them simultaneously poses a great challenge. This is because privacy protection policies prohibit access to users’ local gradients to avoid privacy leakage, while Byzantine-robust methods necessitate access to these gradients to defend against poisoning attacks. To address these problems, we propose a novel privacy-preserving Byzantine-robust FL framework PROFL. PROFL is based on the two-trapdoor additional homomorphic encryption algorithm and blinding techniques to ensure the data privacy of the entire FL process. During the defense process, PROFL first utilize secure Multi-Krum algorithm to remove malicious gradients at the user level. Then, according to the Pauta criterion, we innovatively propose a statistic-based privacy-preserving defense algorithm to eliminate outlier interference at the feature level and resist impersonation poisoning attacks with stronger concealment. Detailed theoretical analysis proves the security and efficiency of the proposed method. We conducted extensive experiments on two benchmark datasets, and PROFL improved accuracy by 39% to 75% across different attack settings compared to similar privacy-preserving robust methods, demonstrating its significant advantage in robustness.

The robust formation tracking problems (FTPs) are investigated for noncooperative heterogeneous multiagent systems (MASs). The parameters and state dimensions of each agent in the MASs can be heterogeneous. The leader is noncooperative and has an unknown external input. The followers are affected by uncertainties and disturbances. A distributed extended state observer is designed to estimate the leader's state and the unknown external input. Then a robust formation tracking control method is proposed. It turns out that the output formation tracking error can reduce to any size neighborhood near the origin by selecting appropriate parameters. Finally, the effectiveness of the proposed observer and controller is demonstrated by a numerical simulation example and a hardware-in-the-loop (HITL) simulation example.

This study addresses the task assignment problem with robot coalitions, as encountered in practical scenarios, such as multiplayer reach-avoid games. Unlike the classical assignment problem where a single robot performs each task, the problem considered here involves tasks that require execution by a robot coalition consisting of two robots. This task assignment problem is a special instance of 3-set packing problem, which is known to be nondeterministic polynomial time (NP)-hard. We introduce the concept of$\epsilon$-coalition-competitive equilibrium ($\epsilon$-CCE) to characterize a kind of approximate solution that offers guaranteed performance. A distributed auction algorithm is developed to find an$\epsilon$-CCE within a finite number of iterations. In addition, several enhancements have been implemented to adapt the auction algorithm for practical applications where the task assignment problem may vary over time. Numerical simulations demonstrate that the distributed algorithm achieves satisfactory approximation quality.

This article considers a subspace guarding game in high-dimensional space which consists of a play subspace and a target subspace. Two faster defenders as a team cooperate to protect the target subspace by capturing an attacker which strives to enter the target subspace from the play subspace without being captured. A closed-form solution is provided from the perspectives of kind and degree. Contributions of the work include the use of the attack subspace (AS) method to construct the barrier, by which the game winner can be perfectly predicted before the game starts. In addition to this inclusion, with the priori information about the game result, a critical payoff function is designed when the defenders can win the game. Then, the optimal strategy for each player is explicitly reformulated as a saddle-point equilibrium. Finally, we apply these theoretical results to two half-space and half-plane guarding games in 3-D space and 2-D plane, respectively. Since the entire achieved developments are analytical, they require a little memory without the computational burden and allow for real-time updates, beyond the capacity of the traditional Hamilton-Jacobi-Isaacs method. It is worth noting that this is the first time in the current work to consider the target guarding games for arbitrary high-dimensional space and in a fully analytical form.

This paper discusses the trajectory tracking problem for miniature fixed-wing UAVs subject to wind gust disturbances and heterogeneous uncertainties. Based on a simplified aerodynamic model, a 6-state translational model is derived from the fixed-wing UAV dynamics by assuming an ideal inner-loop attitude controller. Combining signal compensation and feedback linearization method, we propose a new robust trajectory tracking controller for planar motion control, which incorporates a nominal linear controller to achieve the prescribed convergence and a robust compensator to restrain the effect of disturbances and uncertainties, while a well-tuned PID controller is developed for altitude regulation. The proposed robust control scheme is implemented on a miniature fixed-wing UAV and the flight tests for different scenarios(including both strong and light wind) are performed. The experimental results are shown to demonstrate the effectiveness and robustness of the robust control scheme.

This article considers a multiplayer reach-avoid game between two adversarial teams in a general convex domain which consists of a target region and a play region. The evasion team, initially lying in the play region, aims to send as many team members into the target region as possible, while the pursuit team with its team members initially distributed in both play region and target region, strives to prevent that by capturing the evaders. We aim at investigating a task assignment about the pursuer-evader matching, which can maximize the number of the evaders who can be captured before reaching the target region safely when both teams play optimally. To address this, two winning regions for a group of pursuers to intercept an evader are determined by constructing an analytical barrier which divides these two parts. Then, a task assignment to guarantee the most evaders intercepted is provided by solving a simplified 0-1 integer programming instead of a nondeterministic polynomial problem, easing the computation burden dramatically. It is worth noting that except the task assignment, the whole analysis is analytical. Finally, simulation results are also presented.

Formation-containment control problems for multiple multirotor unmanned aerial vehicle (UAV) systems with directed topologies are studied, where the states of leaders form desired formation and the states of followers converge to the convex hull spanned by those of the leaders. First, formation-containment protocols are constructed based on the neighboring information of UAVs. Then, sufficient conditions for multi-UAV systems to achieve formation-containment are presented. An explicit expression to describe the relationship among the states of followers, the time-varying formation for the leaders and the formation reference is derived. It is shown that the states of followers not only converge to the convex hull formed by those of leaders but also keep certain formation specified by the convex combination of the formation for the leaders. Moreover, an approach to determine the gain matrices of the formation-containment protocol is proposed by solving an algebraic Riccati equation. Finally, a formation-containment platform with five quadrotor UAVs is introduced, and both the simulation and experimental results are presented to demonstrate the effectiveness of the obtained results. Note to Practitioners-This paper addresses the problem of formation-containment control for multi-UAV systems over directed topologies. In practical applications, there may exist multiple leaders and multiple followers in a multi-UAV system. Formation-containment means that the states of leaders form the desired time-varying formation and at the same time the states of the followers converge to the convex hull spanned by those of the leaders. Formation-containment control provides a unified framework for formation control and containment control, and has potential applications in the cooperative source seeking, load transportation, and surveillance. Although formation control and containment control problems have been studied a lot, the formation-containment control problem for multi-UAV system is still open and challenging. This paper proposed a distributed formation-containment protocol for the multi-UAV system using local neighboring information. Sufficient conditions for multi-UAV systems to achieve formation-containment are presented. It is proven that the states of followers not only converge to the convex hull formed by those of leaders but also keep certain formation specified by the convex combination of the formation for the leaders. An approach to design the formation-containment protocol is given. A remarkable point for this paper is that the obtained results are demonstrated by practical experiments with five quadrotor UAVs.

This paper considers a reach-avoid game on a rectangular domain with two defenders and one attacker. The attacker aims to reach a specified edge of the game domain boundary, while the defenders strive to prevent that by capturing the attacker. First, we are concerned with the barrier, which is the boundary of the reach-avoid set, splitting the state space into two disjoint parts: 1) defender dominance region (DDR) and 2) attacker dominance region (ADR). For the initial states lying in the DDR, there exists a strategy for the defenders to intercept the attacker regardless of the attacker's best effort, while for the initial states lying in the ADR, the attacker can always find a successful attack strategy. We propose an attack region method to construct the barrier analytically by employing Voronoi diagram and Apollonius circle for two kinds of speed ratios. Then, by taking practical payoff functions into considerations, we present optimal strategies for the players when their initial states lie in their winning regions, and show that the ADR is divided into several parts corresponding to different strategies for the players. Numerical approaches, which suffer from inherent inaccuracy, have already been utilized for multiplayer reach-avoid games, but computational complexity complicates solving such games and consequently hinders efficient on-line applications. However, this method can obtain the exact formulation of the barrier and is applicable for real-time updates.

Formation control problems for second-order unmanned aerial vehicle (UAV) swarm systems with switching topologies to achieve the time-varying formation and the predefined time-varying formation reference are investigated. The second-order UAV swarm systems considered are not only required to achieve the specified time-varying formation but also track the predefined time-varying formation reference, and the switching topologies are also taken into consideration. To achieve the predefined time-varying formation reference, a new time-varying formation protocol is proposed, and the formation problem is transformed into the consensus problem. Sufficient and necessary conditions for second-order UAV swarm systems modeled by double integrator to achieve the time-varying formation and the predefined time-varying formation reference are presented. Finally, a quadrotor formation platform consisting of three quadrotors is introduced. The simulation and experiment to demonstrate the efficiency of the proposed formation tracking theory are performed.

Output consensus problems for multi-agent systems under disturbances are investigated. Distributed dynamic consensus protocols, which estimate the state and the disturbances of each agent and distribute the estimations to other neighbor agents, are applied, and output consensus problems under disturbances are converted into output regulation problems. On this basis, a necessary and sufficient condition for output consensus in the form of a simultaneous stabilization condition and the solvability of regulator equations which have the same dimensions as the dynamic model of a single agent is shown, and an analytical expression of the output consensus function is obtained. Further, a sufficient condition for output consensualizability is given and a procedure for control protocol design is summarized. Finally, theoretical results are demonstrated by a numerical simulation example.

A reliable pose estimation is crucial in the landing tasks of helicopters. This paper mainly focuses on presenting a smooth and reliable pose estimation method during helicopter landing using Augmented Reality (AR) markers. Based on the proposed hierarchical fiducial marker system called Hierarchical Augmented Reality Code (HArCo), pose estimation can be performed within a much longer range. The design of the system, generation of the marker dictionary and the application in helicopter landing are thoroughly described in this paper. The performance of the pose estimation algorithm based on HArCo is tested in a landing task. As pose information is accessible throughout the landing procedure, a safe auto-landing based on HArCo can also be conducted.

A robust nonlinear attitude control method is proposed for uncertain robotic quadrotors. The proposed controller is developed based on a nonlinear model with the quaternion representation and subject to parameter uncertainties, nonlinearities, and external disturbances. A new state feedback controller is proposed to restrain the effects of nonlinearities and uncertainties on the closed-loop control system. These uncertainties are considered as input equivalent disturbances and their effects are guaranteed to be attenuated. Experimental results are given to show good steady-state and dynamic tracking performance of the closed-loop system by the proposed robust control method compared with other nonlinear control methods.

Output containment control problems for high-order linear time-invariant swarm systems are investigated. Firstly, output containment protocols are presented for leaders and followers respectively to make sure that the output dynamics property of leaders can be improved and the outputs of followers can converge to the convex hull formed by the outputs of leaders. Then output containment problems for swarm systems are transformed into stability problems, and sufficient conditions for swarm systems to achieve output containment are proposed. Moreover, an approach to determine the gain matrix in the output containment protocol is given, which has less calculation complexity. Finally, numerical simulations are presented to demonstrate theoretical results.

Data streaming management and scheduling is required by many grid computing applications, especially when the volume of data to be processed is extremely high while available storage is relatively limited. Big bulk of data from scientific experiments is usually partitioned into lots of small files (LOSF), bringing challenges to data streaming supports. Block-based data transferring is proposed in this work and implemented using GridFTP, where the number of blocks or the size of each block must be carefully scheduled, taking makespan and available storage into account simultaneously. To increase processing efficiency, data streaming and processing have to be performed concurrently; data streaming scheduling must be storage-aware to avoid data overflow. Experimental results show that the optimization method for block-based concurrent and storage-aware data streaming proposed in this work is efficient to deal with the LOSF problem with a relatively good performance in terms of makespan and storage usage.

This paper proposes a design method of decentralized robust controllers for robots with joint backlash, flexibility and damping characteristics. For each joint subsystem, a robust tracking controller is designed in two steps: first, a nominal controller is designed for the nominal plant to get desired tracking performance, then a robust compensator is added to restrain the influence of the perturbation, that is the difference of the real plant from the nominal plant. The controller designed by the proposed method is a linear time-invariant one. It is shown that by applying the controller with a sufficiently wide frequency bandwidth robust output tracking property can be achieved in the contact phase while a new contact of the motor with the load in the correct direction is ensured in the backlash phase. An important feature of the method is that the controller parameters can be tuned on-line easily