Modeling and Analysis of Uncertainty-Based False Information Propagation in Social Networks

Cho, Jin-Hee; Cook, Trevor L.; Rager, Scott; O’Donovan, John; Adalı, Sibel

doi:10.1109/glocom.2017.8255079

Cited by 15 publications

(15 citation statements)

References 11 publications

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“…This type of agents keeps updating their opinions unless its uncertainty u reaches 0, based on SL's consensus operator in Eq. (6). As discussed in Section III-B, uncertainty can increase as an opinion decays over time as shown in Eq.…”

Section: A Agent Typesmentioning

confidence: 96%

“…In this section, we describe how our work modeled the following: (i) the impact of an agent's topic competence on its prior belief/disbelief; (ii) homophily-based (i.e., like-minded) opinion update; and and (iii) opinion decay over time. We adopt the features of (ii) and (iii) from our prior work [6] and include them here to be self-contained.…”

Section: B Opinion Updatementioning

confidence: 99%

“…We model the evolution of false information propagation using a variant of the SIR model [6]. The three states in the SIR model are defined based on the conditions associated with the expected belief or disbelief probabilities, E bi and E di , as follows:…”

Section: B Epidemic Status Of Agentsmentioning

confidence: 99%

“…Accordingly, the neighbors also forward their updated opinions to their neighbors based on Eq. (6). Note that each agent has a chance to disseminate its opinion to its neighbors.…”

Section: B Experimental Setupmentioning

confidence: 99%

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Is Uncertainty Always Bad?: Effect of Topic Competence on Uncertain Opinions

Cho

Adalı

2018

2018 IEEE International Conference on Communications (ICC)

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The proliferation of information disseminated by public/social media has made decision-making highly challenging due to the wide availability of noisy, uncertain, or unverified information. Although the issue of uncertainty in information has been studied for several decades, little work has investigated how noisy (or uncertain) or valuable (or credible) information can be formulated into people's opinions, modeling uncertainty both in the quantity and quality of evidence leading to a specific opinion. In this work, we model and analyze an opinion and information model by using Subjective Logic where the initial set of evidence is mixed with different types of evidence (i.e., pro vs. con or noisy vs. valuable) which is incorporated into the opinions of original propagators, who propagate information over a network. With the help of an extensive simulation study, we examine how the different ratios of information types or agents' prior belief or topic competence affect the overall information diffusion. Based on our findings, agents' high uncertainty is not necessarily always bad in making a right decision as long as they are competent enough not to be at least biased towards false information (e.g., neutral between two extremes).Index Terms-Subjective logic, uncertain opinion, information credibility, prior belief, and topic competence.

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Section: A Agent Typesmentioning

confidence: 96%

Section: B Opinion Updatementioning

confidence: 99%

Section: B Epidemic Status Of Agentsmentioning

confidence: 99%

“…Accordingly, the neighbors also forward their updated opinions to their neighbors based on Eq. (6). Note that each agent has a chance to disseminate its opinion to its neighbors.…”

Section: B Experimental Setupmentioning

confidence: 99%

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Is Uncertainty Always Bad?: Effect of Topic Competence on Uncertain Opinions

Cho

Adalı

2018

2018 IEEE International Conference on Communications (ICC)

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“…The importance of the deception strategy motivates the researchers in different fields of study to develop its formulation. Utilizing asymmetric information in the game-theoretic environment [24][25][26][27][28][29], using probabilistic approach [30,31], graph theory [30], cosine similarity of binary variables [32], and incorrect cost function [29] are among the reported efforts to model the deception strategy. Considering the importance of feint strategy in the decision-making process, the works mentioned above try to model the deception and simulate the reaction of the opponent to the false data.…”

Section: Deception Modellingmentioning

confidence: 99%

A novel approach in strategic planning of power networks against physical attacks

Davarikia

Barati

Alassad

et al. 2020

Electric Power Systems Research

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The reported work points at developing a practical approach for power transmission planners to secure power networks from potential deliberate attacks. We study the interaction between a system planner (defender) and a rational attacker who threatens the operation of power grid. In addition to the commonly used hardening strategy for protecting the network, a new sort of resources is introduced under the deception concept. Feint and deception are acknowledged as effective tools for misleading the attacker in strategic planning. To this end, the defender deception is mathematically formulated by releasing misinformation about his plan in the shared cognition-based model. To reduce the risk of damage in case of deception failure, preemptive-goal programming is utilized to prioritize the hardening strategy for the vital components. Furthermore, the "value of posturing" is introduced which is the benefits that the deception brings to the system. The problems are formulated as tri-level mixedinteger linear programming and solved by constraint-and-column generation method. Comprehensive simulation studies performed on WSCC 9-bus and IEEE 118-bus systems indicate how the defender will save significant cost from protecting his network with posturing rather than hardening and the proposed approach is a promising development to ensure the secure operation of power networks.

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