Zobrazeno 1 - 10
of 77
pro vyhledávání: '"Waniek, Marcin"'
Autor:
Waniek, Marcin, Rahwan, Talal
Group centrality measures are a generalization of standard centrality, designed to quantify the importance of not just a single node (as is the case with standard measures) but rather that of a group of nodes. Some nodes may have an incentive to evad
Externí odkaz:
http://arxiv.org/abs/2312.09791
Autor:
Lai, Yuni, Waniek, Marcin, Li, Liying, Wu, Jingwen, Zhu, Yulin, Michalak, Tomasz P., Rahwan, Talal, Zhou, Kai
Random Walks-based Anomaly Detection (RWAD) is commonly used to identify anomalous patterns in various applications. An intriguing characteristic of RWAD is that the input graph can either be pre-existing or constructed from raw features. Consequentl
Externí odkaz:
http://arxiv.org/abs/2307.14387
Attribute inference - the process of analyzing publicly available data in order to uncover hidden information - has become a major threat to privacy, given the recent technological leap in machine learning. One way to tackle this threat is to strateg
Externí odkaz:
http://arxiv.org/abs/2304.11853
Autor:
Godziszewski, Michał T., Waniek, Marcin, Zhu, Yulin, Zhou, Kai, Rahwan, Talal, Michalak, Tomasz P.
Publikováno v:
In Artificial Intelligence October 2024 335
Social network analysis tools can infer various attributes just by scrutinizing one's connections. Several researchers have studied the problem faced by an evader whose goal is to strategically rewire their social connections in order to mislead such
Externí odkaz:
http://arxiv.org/abs/2107.13174
Publikováno v:
iScience, Volume 25, Issue 9 (2022)
Influencing (and being influenced by) others through social networks is fundamental to all human societies. Whether this happens through the diffusion of rumors, opinions, or viruses, identifying the diffusion source (i.e., the person that initiated
Externí odkaz:
http://arxiv.org/abs/2102.10539
Autor:
Waniek, Marcin, Woźnica, Jan, Zhou, Kai, Vorobeychik, Yevgeniy, Rahwan, Talal, Michalak, Tomasz
Among the most fundamental tools for social network analysis are centrality measures, which quantify the importance of every node in the network. This centrality analysis typically disregards the possibility that the network may have been deliberatel
Externí odkaz:
http://arxiv.org/abs/2101.10648
Disinformation continues to attract attention due to its increasing threat to society. Nevertheless, a disinformation-based attack on critical infrastructure has never been studied to date. Here, we consider traffic networks and focus on fake informa
Externí odkaz:
http://arxiv.org/abs/2003.03723
Multilayer networks allow for modeling complex relationships, where individuals are embedded in multiple social networks at the same time. Given the ubiquity of such relationships, these networks have been increasingly gaining attention in the litera
Externí odkaz:
http://arxiv.org/abs/1911.05947
Social technologies have made it possible to propagate disinformation and manipulate the masses at an unprecedented scale. This is particularly alarming from a security perspective, as humans have proven to be the weakest link when protecting critica
Externí odkaz:
http://arxiv.org/abs/1908.02589