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This paper considers a multi-armed bandit (MAB) problem in which multiple mobile agents receive rewards by sampling from a collection of spatially dispersed stochastic processes, called bandits. The goal is to formulate a decentralized…

Machine Learning · Computer Science 2020-04-01 Pathmanathan Pankayaraj , D. H. S. Maithripala , J. M. Berg

Lateral movement of advanced persistent threats has posed a severe security challenge. Due to the stealthy and persistent nature of the lateral movement, defenders need to consider time and spatial locations holistically to discover latent…

Networking and Internet Architecture · Computer Science 2020-10-07 Linan Huang , Quanyan Zhu

Conventional wireless security assumes wireless communications are rightful and aims to protect them against malicious eavesdropping and jamming attacks. However, emerging infrastructure-free mobile communication networks are likely to be…

Information Theory · Computer Science 2016-12-26 Jie Xu , Lingjie Duan , Rui Zhang

Most of the current anti-jamming algorithms for wireless communications only consider how to avoid jamming attacks, but ignore that the communication waveform or frequency action may be obtained by the jammers. Although existing…

Information Theory · Computer Science 2020-12-24 Yifan Wang , Xin Liu , Mei Wang , Yu Yu

Restless multi-armed bandits (RMAB) have been widely used to model sequential decision making problems with constraints. The decision maker (DM) aims to maximize the expected total reward over an infinite horizon under an "instantaneous…

Machine Learning · Computer Science 2023-12-25 Shufan Wang , Guojun Xiong , Jian Li

A mobile ad hoc network (MANETs) is a self-organizing system of mobile nodes that communicate with each other via wireless links with no fixed infrastructure or centralized administration such as base station or access points. Nodes in a…

Cryptography and Security · Computer Science 2009-09-09 V. Palanisamy , P. Annadurai

In this paper, we consider a novel variant of the multi-armed bandit (MAB) problem, MAB with cost subsidy, which models many real-life applications where the learning agent has to pay to select an arm and is concerned about optimizing…

Machine Learning · Computer Science 2021-03-16 Deeksha Sinha , Karthik Abinav Sankararama , Abbas Kazerouni , Vashist Avadhanula

In this paper, we study jamming attacks against wireless networks. Specifically, we consider a network of base stations (BS) or access points (AP) and investigate the impact of a fixed number of jammers that are randomly deployed according…

Information Theory · Computer Science 2016-11-17 SaiDhiraj Amuru , Harpreet S. Dhillon , R. Michael Buehrer

Intentional interference constitutes a major threat for communication networks operating over a shared medium where availability is imperative. Jamming attacks are often simple and cheap to implement. In particular, today's jammers can…

Data Structures and Algorithms · Computer Science 2011-03-04 Andrea Richa , Christian Scheideler , Stefan Schmid , Jin Zhang

Applying Reinforcement Learning (RL) to Restless Multi-Arm Bandits (RMABs) offers a promising avenue for addressing allocation problems with resource constraints and temporal dynamics. However, classic RMAB models largely overlook the…

Machine Learning · Computer Science 2025-03-20 Yunfan Zhao , Tonghan Wang , Dheeraj Nagaraj , Aparna Taneja , Milind Tambe

This paper presents a simple local medium access control protocol, called \textsc{Jade}, for multi-hop wireless networks with a single channel that is provably robust against adaptive adversarial jamming. The wireless network is modeled as…

Distributed, Parallel, and Cluster Computing · Computer Science 2010-07-12 Andrea Richa , Christian Scheideler , Stefan Schmid , Jin Zhang

In this paper, we introduce a strong adversarial attack, referred to as the flipping attack, on Direct-Sequence Spread Spectrum (DSSS) systems. In this attack, the attacker, which is appropriately positioned between the transmitter and the…

Information Theory · Computer Science 2018-04-04 J. Harshan , Yih-Chun Hu

Randomized election timeouts are a simple and effective liveness heuristic for Raft, but they become brittle under long-tail latency, jitter, and partition recovery, where repeated split votes can inflate unavailability. This paper presents…

Machine Learning · Computer Science 2025-12-25 Qizhi Wang

In the edge computing paradigm, mobile devices offload the computational tasks to an edge server by routing the required data over the wireless network. The full potential of edge computing becomes realized only if a smart device selects…

Machine Learning · Computer Science 2020-08-25 Saeed Ghoorchian , Setareh Maghsudi

Large language models (LLMs) are increasingly vulnerable to multi-turn jailbreak attacks, where adversaries iteratively elicit harmful behaviors that bypass single-turn safety filters. Existing defenses predominantly rely on passive…

Cryptography and Security · Computer Science 2025-10-20 ChenYu Wu , Yi Wang , Yang Liao

Deep reinforcement learning (DRL) has recently been used to perform efficient resource allocation in wireless communications. In this paper, the vulnerabilities of such DRL agents to adversarial attacks is studied. In particular, we…

Machine Learning · Computer Science 2021-05-13 Feng Wang , M. Cenk Gursoy , Senem Velipasalar

User mobility in wireless data networks is increasing because of technological advances and the desire for voice and multimedia applications. These applications, however, require fast handoffs between base stations to maintain the quality…

Networking and Internet Architecture · Computer Science 2012-06-18 S. Alagu , T. Meyyappan

This paper investigates the grant-free random access with massive IoT devices. By embedding the data symbols in the signature sequences, joint device activity detection and data decoding can be achieved, which, however, significantly…

Machine Learning · Computer Science 2020-01-29 Jialin Dong , Jun Zhang , Yuanming Shi , Jessie Hui Wang

We consider the nonstochastic multi-agent multi-armed bandit problem with agents collaborating via a communication network with delays. We show a lower bound for individual regret of all agents. We show that with suitable regularizers and…

Machine Learning · Statistics 2023-10-24 Jialin Yi , Milan Vojnović

Current state-of-the-art approaches to video understanding adopt temporal jittering to simulate analyzing the video at varying frame rates. However, this does not work well for multirate videos, in which actions or subactions occur at…

Computer Vision and Pattern Recognition · Computer Science 2018-10-31 Yi Zhu , Shawn Newsam