首页|Economic feasibility study for stealthy socialbot network establishment

Economic feasibility study for stealthy socialbot network establishment

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Socialbots are intelligent software that controls all behaviour of fake accounts in an online social network. Since they are armed with detection evasion techniques, it is valuable to be able to determine the effectiveness of these techniques. In this study, an analytical model is developed to estimate a lower bound for the cost of automatic establishment of a socialbot network. Moreover, by considering fake accounts purchasing as an establishment strategy, an upper bound is suggested for acceptable costs. These two boundaries are compared to decide on the economic feasibility of a socialbot network design strategy. To demonstrate the practicality and effectiveness of the model, two case studies are investigated. They show that although designing a fully stealthy socialbot network is economically feasible, the infiltration time would be unacceptable. Thus, this ideal situation in which the establishment is fully stealthy, performs in a tolerable time, and satisfactory infiltration scale, is impractical. A possible solution could be achieved by reducing the time and cost in exchange for less stealthy behaviour while the infiltration scale kept unchanged. Since the model presents a trade-off between stealthiness, time, and cost, it is a useful tool facilitating the design of a possible strategy.

social networking (online)security of datapurchasinginfiltration scalestealthy behaviourinfiltration timefully stealthy socialbot networksocialbot network design strategyacceptable costsestablishment strategyautomatic establishmentanalytical modeldetection evasion techniquesonline social networkfake accountsintelligent softwarestealthy socialbot network establishmenteconomic feasibility study

Hosseini Moghaddam, Samaneh、Abbaspour, Maghsoud

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Shahid Beheshti Univ, Network Secur Lab, Fac Comp Sci & Engn, Tehran, Iran

2020

10.1049/iet-ifs.2019.0152

IET information security

IET information security

ISSN：1751-8709
年,卷(期)：2020.14(6)
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