Generative AI-based approach for player behavior analysis and gray area identification
Frontiers in Artificial IntelligenceBackgroundDetecting exploitative or unethical player behavior in online gaming platforms is challenging due to ambiguous gray-area actions that are neither clearly legitimate nor illegal.MethodsThis study presents an interpretable behavior analysis ...
Vinay K., Sriram Sankaran
doaj +1 more source
Comparison of social bot detection techniques
, 2019 Online Social Networks act as a major platform for communication. The origin of social bots is one of the consequences of increasing popularity and utilization of social networks by people.
Vallabhaneni, Bhagyasri
core
Ad Click Fraud Detection Using Machine Learning and Deep Learning Algorithms
IEEE AccessIn online advertising, click fraud poses a significant challenge, draining budgets and threatening the industry’s integrity by redirecting funds away from legitimate advertisers. Despite ongoing efforts to combat these fraudulent practices, recent
Reem A. Alzahrani +2 more
doaj +1 more source
The False positive problem of automatic bot detection in social science research. [PDF]
PLoS One, 2020 Rauchfleisch A, Kaiser J.
europepmc +1 more source
"On Modelling Negotiations within a Dynamic Multi-objective Programming Framework: Analysis of Risk Measurement with an Application to Large BOT Projects" [PDF]
The dynamic and multi-objective programming is used here to establish a risk measurement model. We develop an iterative algorithm and the convergence conditions for the model solution.
Haider Ali Khan +2 more
core
How Effective Is Mouse Dynamics Against Web Bots? A Study Across Different Sophistication Levels
IEEE AccessWeb bots pose an increasing threat to online security with mouse dynamics emerging as a key behavioral biometric for detection. This paper critically evaluates a multi-layered defense strategy against a spectrum of bot attacks from synthetic generation ...
Oguzhan Salman, Kemal Bicakci
doaj +1 more source
BotChase: Graph-Based Bot Detection Using Machine Learning [PDF]
, 2019 Bot detection using machine learning (ML), with network flow-level features, has been extensively studied in the literature. However, existing flow-based approaches typically incur a high computational overhead and do not completely capture the network ...
Abou Daya, Abbas
core
Breaking and Defending LLM-Powered Social Media Bot Detection Systems †
The rise of social media bots poses a persistent threat, enabling misinformation, public opinion manipulation, and erosion of trust in online platforms.
Nof Orenstein, Yoni Birman
core +1 more source
Cerberus: cross-site social bot detection system based on deep learning
智能科学与技术学报Social networking sites have attracted billions of users and influence people's lifestyles. However, as open platform with low requirements for registration and joining, it is inevitable that social bots are able to easily register and do harmful things ...
TANG Jiawei +5 more
doaj
, 2020 Automated programs (bots) are responsible for a large percentage of website traffic. These bots, called web bots, vary in sophistication based on their purpose, ranging from simple automated scripts to advanced web bots that have a browser fingerprint ...
Kostoulas, Theodoros +5 more
core