Location Privacy And User Deanonymization within Wireless Local Area Networks

Dagelić, Ante

prikaz prve stranice dokumenta Location Privacy And User Deanonymization within Wireless Local Area Networks

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doctoral thesis

Location Privacy And User Deanonymization within Wireless Local Area Networks

Split: University of Split, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, 2020. urn:nbn:hr:179:091988

Dagelić, Ante

University of Split
Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture
Department of Electronics and Computing

Cite this document

APA 6th Edition

Dagelić, A. (2020). Location Privacy And User Deanonymization within Wireless Local Area Networks (Doctoral thesis). Split: University of Split, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture. Retrieved from https://urn.nsk.hr/urn:nbn:hr:179:091988

MLA 8th Edition

Dagelić, Ante. "Location Privacy And User Deanonymization within Wireless Local Area Networks." Doctoral thesis, University of Split, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, 2020. https://urn.nsk.hr/urn:nbn:hr:179:091988

Chicago 17th Edition

Harvard

Dagelić, A. (2020). 'Location Privacy And User Deanonymization within Wireless Local Area Networks', Doctoral thesis, University of Split, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, accessed 23 March 2025, https://urn.nsk.hr/urn:nbn:hr:179:091988

Vancouver

Dagelić A. Location Privacy And User Deanonymization within Wireless Local Area Networks [Doctoral thesis]. Split: University of Split, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture; 2020 [cited 2025 March 23] Available at: https://urn.nsk.hr/urn:nbn:hr:179:091988

IEEE

A. Dagelić, "Location Privacy And User Deanonymization within Wireless Local Area Networks", Doctoral thesis, University of Split, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, Split, 2020. Available at: https://urn.nsk.hr/urn:nbn:hr:179:091988

Cite this item: https://urn.nsk.hr/urn:nbn:hr:179:091988

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Metadata

Title	Location Privacy And User Deanonymization within Wireless Local Area Networks
Title (croatian)	Lokacijska privatnost i de-anonimizacija korisnika u okviru bežičnih lokalnih mreža
Author	Ante Dagelić https://orcid.org/0000-0002-8393-783X
Mentor	Mario Čagalj (mentor)
Committee member	Dinko Begušić (predsjednik povjerenstva)
Committee member	Srđan Čapkun (član povjerenstva) VIAF: 495154590087543080296
Committee member	Maja Štula (član povjerenstva)
Committee member	Josip Lörincz (član povjerenstva)
Committee member	Toni Perković (član povjerenstva)
Granter	University of Split Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture (Department of Electronics and Computing) Split
Defense date and country	2020-12-08, Croatia
Scientific / art field, discipline and subdiscipline	TECHNICAL SCIENCES Computing Information Systems
Universal decimal classification (UDC)	62 - Engineering. Technology in general
Abstract	Considering the widespread and continuous increase in devices using WiFi networks, privacy implications are a growing concern. Passively monitoring WiFi traffic, forcing devices to initiate a connection or compromising WiFi security can be used by an adversary in order to reveal private location data or even enable long term tracking of individuals by deanonymizing victims MAC address. Device’s Preferred Network List (PNL) - a list of previously usedWiFi access points is a particularly interesting source of private location data. PNL can be obtained by monitoring victims WiFi traffic, however a 4-year study on more than 150,000 devices, reveals that the device manufacturers are implementing more secure WiFi initialization protocols, not vulnerable to passive monitoring attacks. A new active attack called SSID Oracle attack is modeled, optimized and proved to work in practice. It is shown that SSID Oracle attack is almost 20 times faster than previously proposed active attacks, allowing the attacker to perform the attack in a much shorter opportunity window. However, revealing the device’s PNL and the private location data does not have high implications if one does not know the real person behind the WiFi’s MAC address. A new MAC address deanonymization algorithm is modeled, optimized and verified on a real-life data. The algorithm scores the match of the WiFi device’s PNL with social network location tags, allowing us to match the devices MAC address to the user’s social network profile. Another approach to device deanonymization is performed by exploiting a known WPA2-Enterprise vulnerability where it is shown that almost 87% of a widespread student WiFi network eduroam are vulnerable.
Abstract (croatian)	S obzirom na raširenost i kontinuirani rast broja uređaja koji koriste WiFi mrežu, implikacije na privatnost postaju sve veće. Pasivnim osluškivanjem WiFi prometa, provokacijom uređaja da iniciraju WiFi konekciju ili iskorištavanjem ranjivosti WiFi mreža, napadač može otkriti privatne lokacijske podatke ili čak dugotrajno pratiti osobu u slučaju da je de-anonimizirao MAC adresu uređaja. Lista preferiranih mreža (PNL) - niz naziva često korištenihWiFi pristupnih točki je vrlo interesantan izvor privatnih lokacijskih podataka. PNL se može dobiti osluškivanjem WiFi prometa korisnikovog uređaja, međutim tijekom četverogodišnjeg istraživanja baziranog na više od 150,000 uređaja, ustanovili smo da proizvođači uređaja sve više implementiraju sigurnije WiFi inicijalizacijske protokole, koji nisu ranjivi na napade pasivnim osluškivanjem WiFi kanala. U ovoj tezi je matematički modeliran, optimiziran i u praksi testiran novi aktivni napad na PNL listu pod nazivom SSID prorok. Pokazano je da je koristeći napad SSID prorokom moguće ostvariti i do 20 puta brži napad u odnosu na ranije korištene aktivne napada, što u konačnosti omogućava napadaču da napad izvrši u značajno kraćem prozoru dostupnosti žrtve. Međutim, otkriti PNL listu i privatne lokacijske podatke nekog uređaja nema vrlo visoke implikacije ako ne znamo stvarnu osobu koja se nalazi iza WiFi MAC adrese uređaja. U ovoj tezi matematički je modeliran, optimiziran i nad stvarnim podacima verificiran novi de-anonimizacijski algoritam. Algoritam daje ocjenu sličnosti PNL liste WiFi uređaja sa lokacijskim oznakama objava na društvenoj mreži, omogućava uparivanje MAC adresu uređaja i korisnikovog račun na društvenoj mreži. Također, drugim pristupom problematici de-anonimizacije uređaja, iskorištena je poznata ranjivost WPA2-Enterprise protokola gdje je pokazano da se u čak 87% korisnika poznate raširene studentske WiFi mreže eduroam može provesti de-anonimizacijski napad.
Keywords
Keywords (croatian)
Language	english
URN:NBN	urn:nbn:hr:179:091988
Promotion	2021
Study programme	Title: Electrical Engineering and Information Technology Study programme type: university Study level: postgraduate Academic / professional title: doktor/doktorica znanosti, područje tehničkih znanosti, polje elektrotehnika (doktor/doktorica znanosti, područje tehničkih znanosti, polje elektrotehnika)
Type of resource	Text
Extent	159 str.
File origin	Born digital
Access conditions	Access restricted to students and staff of home institution
Terms of use
Repository	Repository of the Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture
Created on	2021-10-25 09:07:20