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

Institutional repository: Repository of the Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture

Cite this document

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

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

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

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 04 September 2024, https://urn.nsk.hr/urn:nbn:hr:179:091988

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 2024 September 04] Available at: https://urn.nsk.hr/urn:nbn:hr:179:091988

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

Metadata
TitleLocation Privacy And User Deanonymization within Wireless Local Area Networks
Title (croatian)Lokacijska privatnost i de-anonimizacija korisnika u okviru bežičnih lokalnih mreža
AuthorAnte Dagelić https://orcid.org/0000-0002-8393-783X
MentorMario Čagalj (mentor)
Committee memberDinko Begušić (predsjednik povjerenstva)
Committee memberSrđan Čapkun (član povjerenstva)
VIAF: 495154590087543080296
Committee memberMaja Štula (član povjerenstva)
Committee memberJosip Lörincz (član povjerenstva)
Committee memberToni Perković (član povjerenstva)
GranterUniversity of Split
Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture
(Department of Electronics and Computing)
Split
Defense date and country2020-12-08, 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)
Languageenglish
URN:NBNurn:nbn:hr:179:091988
Promotion2021
Study programmeTitle: 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 resourceText
Extent159 str.
File originBorn digital
Access conditionsAccess restricted to students and staff of home institution
Terms of useLicence In copyright icon
Created on2021-10-25 09:07:20