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Mahshad Shariat's Projects

dcopf icon dcopf

DCOPF Solves a DC optimal power flow.

id3 icon id3

Machine Learning Algorithms

privacy-limits-in-bipartite-networks-under-active-attacks icon privacy-limits-in-bipartite-networks-under-active-attacks

This work considers active deanonymization of bipartite networks. The scenario arises naturally in evaluating privacy in various applications such as social networks, mobility networks, and medical databases. For instance, in active deanonymization of social networks, an anonymous victim is targeted by an attacker (e.g. the victim visits the attacker's website), and the attacker queries her group memberships (e.g. by querying the browser history) to deanonymize her. In this work, the fundamental limits of privacy, in terms of the minimum number of queries necessary for deanonymization, is investigated. The bipartite network is generated based on linear and sublinear preferential attachment, and the stochastic block model. The victim's identity is chosen randomly based on a distribution modeling the users' risk of being the victim (e.g. probability of visiting the website). An attack algorithm is proposed which builds upon techniques from communication with feedback, and its performance, in terms of expected number of queries, is analyzed. Simulation results are provided to verify the theoretical derivations. In this project, we provide several simulations of synthesized and real-world attacks to verify the theoretical results presented in the paper and gain further intuition regarding the users’ privacy risks under such attack scenarios. For detailed problem formulation you can visit the following paper: https://arxiv.org/abs/2106.04766

security-constrained-unit-commitment--benders-decomposition icon security-constrained-unit-commitment--benders-decomposition

Considering the global warming the power generation is going to be based on renewable generation. Between renewable generation wind power is one of the fastest growing renewable sources of energy generation in the U.S. and many other countries. Wind energy is a desirable resource because it’s cheap and clean. However, it’s intermittent, and the profile of energy generation does not correlate with the demand cycle. Wind energy is available when the wind blows, and the power level depends on wind speed. Therefore, they are not dispatched in the traditional sense. As installed wind capacity grows in a region, the intermittency of wind energy becomes a significant issue. This paper presents a security-constrained unit commitment (SCUC) algorithm with the Benders Decomposition method for considering wind generation volatility.

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