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Article Citation - WoS: 11Citation - Scopus: 24The Effect of Social Media User Behaviors on Security and Privacy Threats(Ieee-inst Electrical Electronics Engineers inc, 2022) Cengiz, Aslihan Banu; Kalem, Guler; Boluk, Pinar SarisarayThe number of online social network (OSN) users is increasing daily and attacks and threats against over the time spent on online networks has been increasing equally. Attacks against OSN users exploit not only system vulnerabilities but also user-induced vulnerabilities, which naturally affect the hacker's attack strategy as well. This study is designed to investigate the effect of social media user behaviors on their vulnerability level in terms of security and privacy. The study was conducted survey methods, which was applied to social media users in two countries - Turkey and Iraq. This study documents and analyzes the behaviors of 700 OSN users in two countries. This study examines the behaviors of social media users from two nationalities, investigating whether there is a relationship between social media users' behaviors and security and privacy threats. Research findings demonstrate that there is a significant relationship between OSN users' behaviors and their attitudes towards security and privacy. Additionally, Turkish social media users pay more attention to their behaviors in terms of privacy and security awareness than Iraq users.Article Citation - WoS: 4Citation - Scopus: 4Privacy Protection Via Joint Real and Reactive Load Shaping in Smart Grids(Elsevier, 2022) Kement, Cihan Emre; Ilic, Marija; Gultekin, Hakan; Cicek, Cihan Tugrul; Tavli, BulentFrequent metering of electricity consumption is crucial for demand-side management in smart grids. However, metered data can be processed fairly easily by employing well-established nonintrusive appliance load monitoring techniques to infer appliance usage, which reveals information about consumers' private lives. Existing load shaping techniques for privacy primarily focus only on altering metered real power, whereas smart meters collect reactive power consumption data as well for various purposes. This study addresses consumer privacy preservation via load shaping in a demand response scheme, considering both real and reactive power. We build a multi-objective optimization framework that enables us to characterize the interplay between privacy maximization, user cost minimization, and user discomfort minimization objectives. Our results reveal that minimizing information leakage due to a single component, e.g., real power, would suffer from overlooking information leakage due to the other component, e.g., reactive power, causing sub-optimal decisions. In fact, joint shaping of real and reactive power components results in the best possible privacy preservation performance, which leads to more than a twofold increase in privacy in terms of mutual information. (c) 2022 Elsevier Ltd. All rights reserved.
