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Expressing attack-defence trees in a multi-agent setting allows for studying a new aspect of security scenarios, namely how the number of agents and their task assignment impact the performance, e.g. attack time, of strategies executed by…

多智能体系统 · 计算机科学 2022-05-02 Jaime Arias , Łukasz Maśko , Wojciech Penczek , Laure Petrucci , Teofil Sidoruk

Tree ensembles are one of the most widely used model classes. However, these models are susceptible to adversarial examples, i.e., slightly perturbed examples that elicit a misprediction. There has been significant research on designing…

机器学习 · 计算机科学 2024-02-14 Lorenzo Cascioli , Laurens Devos , Ondřej Kuželka , Jesse Davis

Finding shortest paths in a given network (e.g., a computer network or a road network) is a well-studied task with many applications. We consider this task under the presence of an adversary, who can manipulate the network by perturbing its…

社会与信息网络 · 计算机科学 2021-07-08 Benjamin A. Miller , Zohair Shafi , Wheeler Ruml , Yevgeniy Vorobeychik , Tina Eliassi-Rad , Scott Alfeld

We tackle a stochastic version of the Critical Node Problem (CNP) where the goal is to minimize the pairwise connectivity of a graph by attacking a subset of its nodes. In the stochastic setting considered, the attacks on nodes can fail…

数据结构与算法 · 计算机科学 2019-05-30 Pierre Hosteins , Rosario Scatamacchia

Tree ensemble models such as random forests and boosted trees are among the most widely used and practically successful predictive models in applied machine learning and business analytics. Although such models have been used to make…

最优化与控制 · 数学 2019-10-11 Velibor V. Mišić

According to the World Economic Forum, cyber attacks are considered as one of the most important sources of risk to companies and institutions worldwide. Attacks can target the network, software, and/or hardware. During the past years, much…

密码学与安全 · 计算机科学 2022-08-31 Tara Ghasempouri , Jaan Raik , Cezar Reinbrecht , Said Hamdioui , Mottaqiallah Taouil

The goal of this note is to assess whether simple machine learning algorithms can be used to determine whether and how a given network has been attacked. The procedure is based on the $k$-Nearest Neighbor and the Random Forest…

物理与社会 · 物理学 2023-08-30 Davide Coppes , Paolo Cermelli

The robustness of complex networks under targeted attacks is deeply connected to the resilience of complex systems, i.e., the ability to make appropriate responses to the attacks. In this article, we investigated the state-of-the-art…

社会与信息网络 · 计算机科学 2018-01-19 Xiao-Long Ren , Niels Gleinig , Dijana Tolic , Nino Antulov-Fantulin

We study budget constrained network upgradeable problems. We are given an undirected edge weighted graph $G=(V,E)$ where the weight an edge $e \in E$ can be upgraded for a cost $c(e)$. Given a budget $B$ for improvement, the goal is to find…

数据结构与算法 · 计算机科学 2014-12-12 Debjyoti Saharoy , Sandeep Sen

Advanced persistent threats (APT) combine a variety of different attack forms ranging from social engineering to technical exploits. The diversity and usual stealthiness of APT turns them into a central problem of contemporary practical…

密码学与安全 · 计算机科学 2022-05-03 Stefan Rass , Sandra König , Stefan Schauer

The new cyber attack pattern of advanced persistent threat (APT) has posed a serious threat to modern society. This paper addresses the APT defense problem, i.e., the problem of how to effectively defend against an APT campaign. Based on a…

密码学与安全 · 计算机科学 2017-12-29 Pengdeng Li , Lu-Xing Yang , Xiaofan Yang , Qingyu Xiong , Junhao Wen , Yuan Yan Tang

It has been known that heterogeneous networks are vulnerable to the intentional removal of a small fraction of highly connected or loaded nodes, which implies that, to protect a network effectively, a few important nodes should be allocated…

网络与互联网体系结构 · 计算机科学 2009-11-13 Xingang Wang , Shuguang Guan , Choy Heng Lai

This paper studies a fundamental algorithmic problem related to the design of demand-aware networks: networks whose topologies adjust toward the traffic patterns they serve, in an online manner. The goal is to strike a tradeoff between the…

数据结构与算法 · 计算机科学 2020-04-07 Chen Avin , Kaushik Mondal , Stefan Schmid

Informed sampling-based planning algorithms exploit problem knowledge for better search performance. This knowledge is often expressed as heuristic estimates of solution cost and used to order the search. The practical improvement of this…

机器人学 · 计算机科学 2020-12-10 Marlin P. Strub , Jonathan D. Gammell

This paper presents the current state of the art on attack and defense modeling approaches that are based on directed acyclic graphs (DAGs). DAGs allow for a hierarchical decomposition of complex scenarios into simple, easily understandable…

密码学与安全 · 计算机科学 2013-04-01 Barbara Kordy , Ludovic Piètre-Cambacédès , Patrick Schweitzer

In the present day we use machine learning for sensitive tasks that require models to be both understandable and robust. Although traditional models such as decision trees are understandable, they suffer from adversarial attacks. When a…

机器学习 · 计算机科学 2020-12-21 Daniël Vos , Sicco Verwer

Graphical security models constitute a well-known, user-friendly way to represent the security of a system. These kinds of models are used by security experts to identify vulnerabilities and assess the security of a system. The manual…

密码学与安全 · 计算机科学 2023-09-26 Alyzia-Maria Konsta , Beatrice Spiga , Alberto Lluch Lafuente , Nicola Dragoni

We provide an overview of three different query languages whose objective is to specify properties on the highly popular formalisms of fault trees (FTs) and attack trees (ATs). These are BFL, a Boolean Logic for FTs, PFL, a probabilistic…

计算机科学中的逻辑 · 计算机科学 2024-01-30 Stefano M. Nicoletti , Milan Lopuhaä-Zwakenberg , E. Moritz Hahn , Mariëlle Stoelinga

Reachability analysis is a powerful tool when it comes to capturing the behaviour, thus verifying the safety, of autonomous systems. However, general-purpose methods, such as Hamilton-Jacobi approaches, suffer from the curse of…

最优化与控制 · 数学 2022-10-27 Alessandro Alla , Peter M. Dower , Vincent Liu

Adversarial training (AT) is a simple yet effective defense against adversarial attacks to image classification systems, which is based on augmenting the training set with attacks that maximize the loss. However, the effectiveness of AT as…

计算机视觉与模式识别 · 计算机科学 2022-06-17 Kaleab A. Kinfu , René Vidal