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In this paper we present an elaborated graph-based algorithmic technique for efficient malware detection. More precisely, we utilize the system-call dependency graphs (or, for short ScD graphs), obtained by capturing taint analysis traces…

Cryptography and Security · Computer Science 2014-12-31 Stavros D. Nikolopoulos , Iosif Polenakis

Connectomics has focused primarily on the mapping of synaptic links in the brain; yet it is well established that extrasynaptic volume transmission, especially via monoamines and neuropeptides, is also critical to brain function. Here we…

Neurons and Cognition · Quantitative Biology 2017-02-08 Barry Bentley , Robyn Branicky , Christopher L. Barnes , Edward T. Bullmore , Petra E. Vértes , William R. Schafer

A central problem of neuroscience involves uncovering the principles governing the organization of nervous systems which ensure robustness in brain development. The nematode Caenorhabditis elegans provides us with a model organism for…

Neurons and Cognition · Quantitative Biology 2020-07-01 Anand Pathak , Nivedita Chatterjee , Sitabhra Sinha

Contraction of an edge merges its end points into a new vertex which is adjacent to each neighbor of the end points of the edge. An edge in a $k$-connected graph is {\em contractible} if its contraction does not result in a graph of lower…

Discrete Mathematics · Computer Science 2009-02-10 N. S. Narayanaswamy , N. Sadagopan , Apoorve Dubey

Graph are a ubiquitous data representation, as they represent a flexible and compact representation. For instance, the 3D structure of RNA can be efficiently represented as $\textit{2.5D graphs}$, graphs whose nodes are nucleotides and…

Machine Learning · Computer Science 2021-09-21 Vincent Mallet , Carlos G. Oliver , William L. Hamilton

The correspondence between weighted undirected graphs and reversible Markov chains via vertex random walks is simple and well known. Leveraging this correspondence and ideas from the theory of dynamical systems, we study the structural…

Statistics Theory · Mathematics 2026-05-12 Yang Xiang , Kevin McGoff , Andrew B. Nobel

In weighted graphs the shortest path between two nodes is often reached through an indirect path, out of all possible connections, leading to structural redundancies which play key roles in the dynamics and evolution of complex networks. We…

Social and Information Networks · Computer Science 2023-06-14 Felipe Xavier Costa , Rion Brattig Correia , Luis M. Rocha

Designing well-connected graphs is a fundamental problem that frequently arises in various contexts across science and engineering. The weighted number of spanning trees, as a connectivity measure, emerges in numerous problems and plays a…

Data Structures and Algorithms · Computer Science 2016-04-13 Kasra Khosoussi , Gaurav S. Sukhatme , Shoudong Huang , Gamini Dissanayake

This paper studies the problem of designing networks that are strong structurally controllable, and robust simultaneously. For given network specifications, including the number of nodes $N$, the number of leaders $N_L$, and diameter $D$,…

Systems and Control · Electrical Eng. & Systems 2023-03-13 Priyanshkumar I. Patel , Johir Suresh , Waseem Abbas

Motif discovery is a powerful and insightful method to quantify network structures and explore their function. As a case study, we present a comprehensive analysis of regulatory motifs in the connectome of the model organism Caenorhabditis…

Molecular Networks · Quantitative Biology 2024-09-02 Deepak Sharma , Matthias Renz , Philipp Hövel

Graph neural networks (GNNs) have achieved state-of-the-art performance in many graph learning tasks. However, recent studies show that GNNs are vulnerable to both test-time evasion and training-time poisoning attacks that perturb the graph…

Cryptography and Security · Computer Science 2023-03-14 Binghui Wang , Meng Pang , Yun Dong

Graph Neural Networks (GNNs) have shown their great ability in modeling graph structured data. However, real-world graphs usually contain structure noises and have limited labeled nodes. The performance of GNNs would drop significantly when…

Machine Learning · Computer Science 2022-07-26 Enyan Dai , Wei Jin , Hui Liu , Suhang Wang

Given that no existing graph construction method can generate a perfect graph for a given dataset, graph-based algorithms are often affected by redundant and erroneous edges present within the constructed graphs. In this paper, we view…

Machine Learning · Computer Science 2024-11-27 Yongyu Wang , Xiaotian Zhuang

Edge connectivity and vertex connectivity are two fundamental concepts in graph theory. Although by now there is a good understanding of the structure of graphs based on their edge connectivity, our knowledge in the case of vertex…

Discrete Mathematics · Computer Science 2013-04-17 Keren Censor-Hillel , Mohsen Ghaffari , Fabian Kuhn

Despite the exploding interest in graph neural networks there has been little effort to verify and improve their robustness. This is even more alarming given recent findings showing that they are extremely vulnerable to adversarial attacks…

Machine Learning · Computer Science 2019-12-20 Aleksandar Bojchevski , Stephan Günnemann

We prove that the class of chordal graphs is easily testable in the following sense. There exists a constant $c>0$ such that, if adding/removing at most $\epsilon n^2$ edges to a graph $G$ with $n$ vertices does not make it chordal, then a…

Combinatorics · Mathematics 2019-02-19 Rémi de Joannis de Verclos

This work considers the robustness of uncertain consensus networks. The first set of results studies the stability properties of consensus networks with negative edge weights. We show that if either the negative weight edges form a cut in…

Optimization and Control · Mathematics 2015-03-03 Daniel Zelazo , Mathias Bürger

One of the major results of [N. Robertson and P. D. Seymour. Graph minors. XIII. The disjoint paths problem. J. Combin. Theory Ser. B, 63(1):65--110, 1995], also known as the weak structure theorem, revealed the local structure of graphs…

Combinatorics · Mathematics 2011-03-01 Archontia C. Giannopoulou , Dimitrios M. Thilikos

Network structure or topology is the basis for understanding complex systems. Recently, higher-order structures have been considered as a new research direction that can provide new perspectives and phenomena. However, most existing studies…

Neurons and Cognition · Quantitative Biology 2022-12-08 Bo Liu , Rongmei Yang , Hao Wang , Linyuan Lü

Given a graph $G$ whose edges are perfectly reliable and whose nodes each operate independently with probability $p\in[0,1],$ the node reliability of $G$ is the probability that at least one node is operational and that the operational…

Combinatorics · Mathematics 2018-02-14 Jason Brown , Lucas Mol
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