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      SSID Oracle Attack on Undisclosed Wi-Fi Preferred Network Lists

      1 , 2 , 1 , 1
      Wireless Communications and Mobile Computing
      Hindawi Limited

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          Abstract

          User’s location privacy concerns have been further raised by today’s Wi-Fi technology omnipresence. Preferred Network Lists (PNLs) are a particularly interesting source of private location information, as devices are storing a list of previously used hotspots. Privacy implications of a disclosed PNL have been covered by numerous papers, mostly focusing on passive monitoring attacks. Nowadays, however, more and more devices no longer transmit their PNL in clear, thus mitigating passive attacks. Hidden PNLs are still vulnerable against active attacks whereby an attacker mounts a fake SSID hotspot set to one likely contained within targeted PNL. If the targeted device has this SSID in the corresponding PNL, it will automatically initiate a connection with the fake hotspot thus disclosing this information to the attacker. By iterating through different SSIDs (from a predefined dictionary) the attacker can eventually reveal a big part of the hidden PNL. Considering user mobility, executing active attacks usually has to be done within a short opportunity window, while targeting nontrivial SSIDs from user’s PNL. The existing work on active attacks against hidden PNLs often neglects both of these challenges. In this paper we propose a simple mathematical model for analyzing active SSID dictionary attacks, allowing us to optimize the effectiveness of the attack under the above constraints (limited window of opportunity and targeting nontrivial SSIDs). Additionally, we showcase an example method for building an effective SSID dictionary using top-N recommender algorithm and validate our model through simulations and extensive real-life tests.

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          Item-based top-N recommendation algorithms

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            Evolution of Indoor Positioning Technologies: A Survey

            Indoor positioning systems (IPS) use sensors and communication technologies to locate objects in indoor environments. IPS are attracting scientific and enterprise interest because there is a big market opportunity for applying these technologies. There are many previous surveys on indoor positioning systems; however, most of them lack a solid classification scheme that would structurally map a wide field such as IPS, or omit several key technologies or have a limited perspective; finally, surveys rapidly become obsolete in an area as dynamic as IPS. The goal of this paper is to provide a technological perspective of indoor positioning systems, comprising a wide range of technologies and approaches. Further, we classify the existing approaches in a structure in order to guide the review and discussion of the different approaches. Finally, we present a comparison of indoor positioning approaches and present the evolution and trends that we foresee.
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              I know your MAC address: targeted tracking of individual using Wi-Fi

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                Author and article information

                Journal
                Wireless Communications and Mobile Computing
                Wireless Communications and Mobile Computing
                Hindawi Limited
                1530-8669
                1530-8677
                July 22 2018
                July 22 2018
                : 2018
                : 1-15
                Affiliations
                [1 ]FESB, University of Split, Split, Croatia
                [2 ]University Department of Forensic Sciences, University of Split, Split, Croatia
                Article
                10.1155/2018/5153265
                1a81a1ea-eed9-4fbb-aa52-1eba2e8ff281
                © 2018

                http://creativecommons.org/licenses/by/4.0/

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