Game-Based Extraction of Web Users' Personality Factors for Personalization

Halfon, Rachel Yahel; Shehory, Onn; Schwartz, David G.

doi:10.1145/3039677.3039679

Cited by 4 publications

(1 citation statement)

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“…Similarly, without holding any previous information on the users' behavior and, notably, without administering any psychological questionnaires. Halfon, Shehory, & Schwartz (2017) developed a recommendation model for each user by introduced a novel approach of extracting users' personality factors.…”

Section: Recommender Systems Based On Personality and Betweenness Cen...mentioning

confidence: 99%

Sarcp

Asabere

Fiamavle

Agyiri

et al. 2022

International Journal of Decision Support System Technology

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In the domain of cyber security, the defence mechanisms of networks has traditionally been placed in a reactionary role. Cyber security professionals are therefore disadvantaged in a cyber-attack situation due to the fact that it is vital that they maneuver such attacks before the network is totally compromised. In this paper, we utilize the Betweenness Centrality network measure (social property) to discover possible cyber-attack paths and then employ computation of similar personality of nodes/users to generate predictions about possible attacks within the network. Our method proposes a social recommender algorithm called socially-aware recommendation of cyber-attack paths (SARCP), as an attack predictor in the cyber security defence domain. In a social network, SARCP exploits and delivers all possible paths which can result in cyber-attacks. Using a real-world dataset and relevant evaluation metrics, experimental results in the paper show that our proposed method is favorable and effective.

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Section: Recommender Systems Based On Personality and Betweenness Cen...mentioning

confidence: 99%