{"id":98,"date":"2019-12-06T09:13:52","date_gmt":"2019-12-06T08:13:52","guid":{"rendered":"https:\/\/project.inria.fr\/mitik\/?page_id=98"},"modified":"2021-01-25T10:35:06","modified_gmt":"2021-01-25T09:35:06","slug":"objectives","status":"publish","type":"page","link":"https:\/\/project.inria.fr\/mitik\/objectives\/","title":{"rendered":"Objectives and Challenges"},"content":{"rendered":"<p><strong>Mitik<\/strong><span style=\"font-family: 'Source Sans Pro';\"> proposes to rely on non-intrusive passive measurements to infer the mobility of nodes and their potential interactions while on the move. The idea is to leverage the fact that mobile devices are likely to transmit Bluetooth and Wi-Fi packets even when users are not explicitly manipulating their devices. <\/span><\/p>\n<p><span style=\"font-family: Source Sans Pro;\">We propose to measure and analyze such transmissions to infer the displacements of the nodes (see the\u00a0<\/span><span style=\"font-family: Source Sans Pro;\">architecture in\u00a0<\/span><a href=\"#fig1\">Figure 1<\/a>).\u00a0<span style=\"font-family: 'Source Sans Pro';\">On the other hand, passive measurement does not come for free (sniffers either capture a packet, or do not), achieving precise mobility characterization while respecting user privacy is challenging. To cope with this specificity, Mitik will adopt a multi-technique methodology involving:<\/span><\/p>\n<div class=\"page\" title=\"Page 2\">\n<div class=\"layoutArea\">\n<div class=\"column\">\n<ul>\n<li>optimization techniques for efficient placement of sniffers<\/li>\n<li>anomaly detection approaches for filtering of noisy wireless measures<\/li>\n<li>advanced synchronization strategies for the merging of measurement data from multiple sniffers<\/li>\n<li>techniques for reconstruction of imprecise trajectories<\/li>\n<li>contact inference from rough estimations of trajectories, and, at last, but not least<\/li>\n<li>Mitik will be made fully respectful of user privacy<\/li>\n<\/ul>\n<div id=\"attachment_129\" style=\"width: 630px\" class=\"wp-caption aligncenter\"><a id=\"fig1\" href=\"https:\/\/project.inria.fr\/mitik\/files\/2019\/12\/system.pdf\" target=\"_blank\" rel=\"noopener\"><img loading=\"lazy\" decoding=\"async\" aria-describedby=\"caption-attachment-129\" class=\"wp-image-129 size-full\" title=\"Passive data collection\" src=\"https:\/\/project.inria.fr\/mitik\/files\/2019\/12\/system.pdf\" alt=\"Passive data collection\" width=\"620\" height=\"360\" \/><\/a><p id=\"caption-attachment-129\" class=\"wp-caption-text\">Passive data collection<\/p><\/div>\n<div class=\"page\" title=\"Page 3\">\n<div class=\"layoutArea\">\n<div class=\"column\">\n<p>At its core, Mitik\u2019s primary objective is the design of an entirely new methodology to help the community obtain real wireless contact traces that are non-intrusive, representative, and independent of third parties. The secondary outcome of Mitik would be the public release of:<\/p>\n<ul>\n<li>the measurement tool designed for the easy contact gathering task<\/li>\n<li>contact traces which are clean, processed, and privacy-preserving, i.e., protecting both the anonymity and the location privacy of the user and\u00a0their spatiotemporal statistical analysis.<\/li>\n<li>we plan to confront the new insights resulted from our analysis with established observations found in the literature, which may invite the research community to revisit opportunistic mobility modeling. We expect Mitik outcomes will support non-biased research on the modeling as well as on the leveraging of wireless contact patterns.<\/li>\n<\/ul>\n<div class=\"page\" title=\"Page 3\">\n<div class=\"layoutArea\">\n<div class=\"column\">\n<p>To achieve these objectives, the consortium will face many scientific and technological challenges:<\/p>\n<ul>\n<li>Challenge 1 \u2013 Sniffers infrastructure design. Mitik\u2019s measurement strategy relies on the physical deployment of passive sniffers over a geographical area. This will require answering the following questions: how many, where, and what type of sniffers have to be deployed? Such questions reveal the need for protocol and hardware specification as well as for optimized placement strategies. Those\u00a0<span style=\"font-family: 'Source Sans Pro';\">require taking into consideration factors such as the size of the monitored area, the type of traffic to be measured, and the measurement capabilities of sniffers, to cite a few.<\/span><\/li>\n<li>Challenge 2 \u2013 Trace handling, sanitization, and merging. The spatiotemporal aspects of distributed passive measurement make the handling and merging of traces collected by each sniffer a challenging task. This requires advanced approaches for error handling, filtering, and synchronization, packet parsing, as well as merging of traces coming from different sniffers. Furthermore, we want to ensure that the privacy of the users is adequately protected under the GDPR guidelines, i.e., it should not be possible to retrieve the identity of the users from the traces we make available. In this regard, we will anonymize users\u2019 identifiers as well as apply controlled noise to any users\u2019 location. This should be done while minimizing the impact on the utility of the Mitik outcomes.<\/li>\n<li>Challenge 3 \u2013 Trajectory reconstruction and contact inference. Two aspects make the computation of the exact trajectories of individuals a challenging task, namely the communication uncertainties brought by the wireless medium and the unfeasibility of measuring the precise geographical distances between devices and sniffers. Hence, instead of trajectories that are perfect lines, we obtain what we call a trajectory envelop (see the rose and green trajectories in <a href=\"#fig2\"> Figure 2 <\/a>). The shapes of such envelopes depend on several parameters, ranging from the communication technology of nodes (e.g., Bluetooth\u2019s physical coverage differentiates from Wi-Fi\u2019s) to the density and positioning of sniffers. This makes the inference of contacts from such imprecise trajectories a difficult exercise.<\/li>\n<\/ul>\n<div id=\"attachment_129\" style=\"width: 630px\" class=\"wp-caption aligncenter\"><a id=\"fig2\" href=\"https:\/\/project.inria.fr\/mitik\/files\/2019\/12\/idea-02.pdf\" target=\"_blank\" rel=\"noopener\"><img loading=\"lazy\" decoding=\"async\" aria-describedby=\"caption-attachment-129\" class=\"wp-image-129 size-full\" title=\"Trajectory envelopes and plausible contact zone\" src=\"https:\/\/project.inria.fr\/mitik\/files\/2019\/12\/idea-02.pdf\" alt=\"Trajectory envelopes and plausible contact zone\" width=\"620\" height=\"360\" \/><\/a><p id=\"caption-attachment-129\" class=\"wp-caption-text\">Trajectory envelopes and plausible contact zone<\/p><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<p><\/p>","protected":false},"excerpt":{"rendered":"<p>Mitik proposes to rely on non-intrusive passive measurements to infer the mobility of nodes and their potential interactions while on the move. The idea is to leverage the fact that mobile devices are likely to transmit Bluetooth and Wi-Fi packets even when users are not explicitly manipulating their devices. We&#8230;<\/p>\n<p> <a class=\"continue-reading-link\" href=\"https:\/\/project.inria.fr\/mitik\/objectives\/\"><span>Continue reading<\/span><i class=\"crycon-right-dir\"><\/i><\/a> <\/p>\n","protected":false},"author":1697,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-98","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/project.inria.fr\/mitik\/wp-json\/wp\/v2\/pages\/98","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/project.inria.fr\/mitik\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/project.inria.fr\/mitik\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/project.inria.fr\/mitik\/wp-json\/wp\/v2\/users\/1697"}],"replies":[{"embeddable":true,"href":"https:\/\/project.inria.fr\/mitik\/wp-json\/wp\/v2\/comments?post=98"}],"version-history":[{"count":16,"href":"https:\/\/project.inria.fr\/mitik\/wp-json\/wp\/v2\/pages\/98\/revisions"}],"predecessor-version":[{"id":235,"href":"https:\/\/project.inria.fr\/mitik\/wp-json\/wp\/v2\/pages\/98\/revisions\/235"}],"wp:attachment":[{"href":"https:\/\/project.inria.fr\/mitik\/wp-json\/wp\/v2\/media?parent=98"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}