Location Privacy through Secret Sharing Techniques

Marias, Giannis F.; Delakouridis, C.; Kazatzopoulos, L.; Georgiadis, Panagiotis

doi:10.1109/wowmom.2005.60

Cited by 24 publications

(18 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In Marias et al (2005) we have further elaborated on the proposed architecture, evaluating the potential threats and its robustness against brute-force and sophisticated attacks, and we have proved that the STS architecture is stealth against such attacks. If y = 7 is minimum number of STS servers needed to rebuild the location information, z = 10 is the STS servers under attack and m = 20 is the total number of STS servers, the attacker must try an average of 5 · 10 29 combinations in order to find out if the location segments obtained from the z servers are sufficient to rebuild the location information of any (and not specific) user.…”

Section: Experiments and Threats Analysis Against Stsmentioning

confidence: 99%

“…LocInfo is changed go to step 5 4), and to enter Phevos pseudonymÕs segments to the x STS servers. This procedure requires a handshake between the user and each STS server, which is further discussed in Marias et al (2005).…”

Section: Registration To the Sts Servicementioning

confidence: 99%

“…This message can be sent when the user desires to prohibit a previously authorized Service from accessing his location information. A multicast message can inform the entire set of the x STS servers to perform a deletion, as it is described in Marias et al (2005).…”

Section: Lit Entries Remove Policymentioning

confidence: 99%

See 2 more Smart Citations

Applying privacy on the dissemination of location information

Marias

Kazatzopoulos

Delakouridis

et al. 2006

Telematics and Informatics

Self Cite

View full text Add to dashboard Cite

Section: Experiments and Threats Analysis Against Stsmentioning

confidence: 99%

Section: Registration To the Sts Servicementioning

confidence: 99%

See 1 more Smart Citation

Applying privacy on the dissemination of location information

Marias

Kazatzopoulos

Delakouridis

et al. 2006

Telematics and Informatics

Self Cite

View full text Add to dashboard Cite

“…Symmetric encryption techniques are usually used. To deal with the problem of untrusted TTP, (Marias, Delakouridis, Kazatzopoulos, & Georgiadis, 2005) proposed a secret sharing based approach, where the shares are distributed among many untrusted TTP. Thus, to retrieve the true position, you need all the shares.…”

Section: Cryptographymentioning

confidence: 99%

Improved Recommender for Location Privacy Preferences

Hadi¹,

Cazalas²

2015

CIS

View full text Add to dashboard Cite

Location-based services are one of the fastest growing technologies. Millions of users are using these services and sharing their locations using their smart devices. The popularity of using such applications, while enabling others to access user's location, brings with it many privacy issues. The user has the ability to set his location privacy preferences manually. Many users face difficulties in order to set their preferences in the proper way. One solution is to use machine learning based methods to predict location privacy preferences automatically. These models suffer from degraded performance when there is no sufficient training data. Another solution is to make the decision for the intended user, depending on the collected opinions from similar users. User-User Collaborative Filtering (CF) is an example within this category. In this paper, we will introduce an improved machine learning based predictor. The results show significant improvements in the performance. The accuracy was improved from 75.30% up to 84.82%, while the privacy leak was reduced from 11.75% up to 7.65%. We also introduced an integrated model which combines both machine learning based methods and collaborative filtering based methods in order to get the advantages from both of them.

show abstract

“…Using this approach, a location-based server is supposed to answer the user queries but it has no information about the user's location due to encrypted data communication between the nodes that only know the way to decrypt the message. Another approach proposed by Marias et al (Marias, G. F., Delakouridis, C., Kazatzopoulos, L., & Georgiadis, P., 2005) has introduced the idea of distributed sharing of user's location information on different servers for privacy. To retrieve the exact information, the user need to recollect all the shares distributed on different servers.…”

Section: Introductionmentioning

confidence: 99%

Trusted Base Stations-Based Privacy Preserving Technique in Location-Based Services

Aqib¹,

Cazalas²

2015

CIS

View full text Add to dashboard Cite

With the advent in mobile and internet technologies, there is a significant increase in the number of users using smartphones and other internet based applications. There are a large number of applications available online that use the internet and provide useful information to the users. These include ones that provide location-based services e.g. google maps etc. These applications provide many facilities to the users who want information regarding a specific area or directions using an optimal path to a destination. Due to these reasons, the number of clients using these applications is increasing on a daily basis. Although these services are very useful and are making it easy for us to get information about our surroundings, some issues are also linked with the use of these applications and their services. One of the more significant issues of using these services is privacy with respect to sending personal location information to location-based services servers. Researchers have provided many solutions to solve these issues. One of the solutions is through caching and use of k-anonymity techniques. In this paper, we have proposed a method to solve the privacy issue that uses caching data approach to reduce the number of queries sent to the location-based services server. We also discuss the use of the concept of k-anonymity when no relevant data is available in cache, and queries are sent to the server.

show abstract

Location Privacy through Secret Sharing Techniques

Cited by 24 publications

References 15 publications

Applying privacy on the dissemination of location information

Applying privacy on the dissemination of location information

Improved Recommender for Location Privacy Preferences

Trusted Base Stations-Based Privacy Preserving Technique in Location-Based Services

Contact Info

Product

Resources

About