Preserving User Privacy Research Articles

Novel Privacy-preserving algorithm based on frequent path for trajectory data publishing

Existing location-based services have collected a large amount of location data, which contain users’ personal information and has serious personal privacy leakage threats. Therefore, the preservation of individual privacy when publishing data is receiving increasing attention. Most existing methods of preserving user privacy suffer a serious loss in data usability, resulting in low usability of data. In this paper, we address this problem and present TOPF, a novel approach for preserving privacy in trajectory data publishing based on frequent path. TOPF aims to achieve better quality of trajectory data for publishing and strike a balance between the conflicting goals of data usability and data privacy. To the best of our knowledge, this is the first paper that uses frequent path to preserve data privacy. First, infrequent roads in each trajectory are removed, and a new way is adopted to divide trajectories into candidate groups. A new method for finding the most frequent path is then proposed, and then, the representative trajectory is selected to represent all trajectories within a group. Experimental results show that our algorithm not only effectively guarantees the privacy of the user but also ensures the high usability of the data.

A new scheme of preserving user privacy for location-based service

Individual privacy has been a great concern to users who need the location-based service by networked devices such as smart phones and personal computers. Usually, the provider who can provide a location-based service is regarded as semi-trusted or honest-but-curious. It leads to tremendous harmfulness for users who request this service because the dishonest service provider leaks the users' personal information. To preserve user privacy, we propose a scheme which achieves user privacy information including location, identity, and domain, while the user can still obtain the required service from a service provider. For the sake of less computational time and minimal computer power, only symmetric key cryptography is employed in our system. This scheme is secured by our security analysis, and is feasible through our imitating implementation. Compared with related schemes, our scheme can provide sufficient property to meet our requirements.

Dynamic Keyword Search With Hierarchical Attributes in Cloud Computing

A growing number of organizations and individuals outsource their data to the cloud. As the cloud service provider is potentially untrustworthy, cloud user needs to encrypt their sensitive data before outsourcing. One challenge of the cloud service is how to provide an effective search on encrypted data while preserving user privacy. The existing attribute-based keyword search (ABKS) scheme has addressed this issue and enabled a data owner to conduct the search over the outsourced data utilizing an access policy. However, the encryption cost in ABKS linearly increases with the number of attributes in the access policy. In this paper, we proposed a dynamic hierarchical ABKS (DHABKS) scheme to efficiently achieve fine-grained search authorization. We introduced the attribute hierarchy into access policy to improve the encryption performance of the scheme and devised a dynamic updating access policy to largely reduce the workload of the data owner. The efficiency and effectiveness of the DHABKS scheme are validated by extensive experiments using real data sets.

A new scheme of preserving user privacy for location-based service

Individual privacy has been a great concern to users who need the location-based service by networked devices such as smart phones and personal computers. Usually, the provider who can provide a location-based service is regarded as semi-trusted or honest-but-curious. It leads to tremendous harmfulness for users who request this service because the dishonest service provider leaks the users' personal information. To preserve user privacy, we propose a scheme which achieves user privacy information including location, identity, and domain, while the user can still obtain the required service from a service provider. For the sake of less computational time and minimal computer power, only symmetric key cryptography is employed in our system. This scheme is secured by our security analysis, and is feasible through our imitating implementation. Compared with related schemes, our scheme can provide sufficient property to meet our requirements.

Cyber-Physical-Social Aware Privacy Preserving in Location-Based Service

The privacy leakage resulting from location-based service (LBS) has become a critical issue. To preserve user privacy, many previous studies have investigated to prevent LBS servers from user privacy theft. However, they only consider whether the peers are innocent or malicious but ignore the relationship between the peers, whereas such a relationship between each pairwise of users affects the privacy leakage tremendously. For instance, a user has less concern of privacy leakage from a social friend than a stranger. In this paper, we study cyber-physical-social (CPS) aware method to address the privacy preserving in the case that not only LBS servers but also every other participant in the network has the probability to be malicious. Furthermore, by exploring the physical coupling and social ties among users, we construct CPS-aware privacy utility maximization (CPUM) game. We then study the potential Nash equilibrium of the game and show the existence of Nash equilibrium of CPUM game. Finally, we design a CPS-aware algorithm to find the Nash equilibrium for the maximization of privacy utility. Extensive evaluation results show that the proposed approach reduces privacy leakage by 50% in the case that malicious servers and users exist in the network.

Double Cache Approach with Wireless Technology for Preserving User Privacy

Several methods use cache for decreasing the number of connections to protect privacy of user data and improve performance in Location Based Services (LBS). Many of these methods require users to trust other users or third parties, which could be servers. An intruder could be disguised as a user or a third party. In this article, we propose a new method, known as “Double Cache Approach”, which uses a pair of caches to reduce the vulnerability of trust between users or third party and offers a vast improvement in privacy and security of user data in healthcare and other applications that use LBS. This approach divides the area into many cells and manages the cooperation among users within two caches at the access point with wireless communication. To demonstrate the superiority, we also provide simulation results of user queries, comparing the proposed method with those using only one cache. We believe that our approach would solve the trust problem optimally, achieve a comprehensive protection for users’ data, and enhance the privacy and security levels.

Biometrics-Based Privacy-Preserving User Authentication Scheme for Cloud-Based Industrial Internet of Things Deployment

Due to the widespread popularity of Internet-enabled devices, Industrial Internet of Things (IIoT) becomes popular in recent years. However, as the smart devices share the information with each other using an open channel, i.e., Internet, so security and privacy of the shared information remains a paramount concern. There exist some solutions in the literature for preserving security and privacy in IIoT environment. However, due to their heavy computation and communication overheads, these solutions may not be applicable to wide category of applications in IIoT environment. Hence, in this paper, we propose a new biometric-based privacy preserving user authentication (BP2UA) scheme for cloud-based IIoT deployment. BP2UA consists of strong authentication between users and smart devices using preestablished key agreement between smart devices and the gateway node. The formal security analysis of BP2UA using the well-known real-or-random model is provided to prove its session key security. Moreover, an informal security analysis of BP2UA is also given to show its robustness against various types of known attacks. The computation and communication costs of BP2UA in comparison to the other existing schemes of its category demonstrate its effectiveness in the IIoT environment. Finally, the practical demonstration of BP2UA is also done using the NS2 simulation.

Privacy Preserving User Authentication Scheme Based on Smart Card

One of the most commonly used user authentication mechanisms is two factor authentication based on smart card and password. The core feature of the scheme is to enforce that the user must have the smart card and know the password in order to gain access to server. Recently, Liu et al. proposed a smart card based password authentication scheme and argued that it is secure against insider attack, replay attack and man in the middle attack and provides perfect forward secrecy. In this paper, we show security weaknesses in Liu et al.’s scheme focused on off-line password guessing attack and masquerading attack and it does not provide perfect forward secrecy and anonymity. Accordingly, we propose a privacy preserving user authentication scheme based on smart card, denoted as PUAS, to remedy these security weaknesses and to provide anonymity and perfect forward secrecy. PUAS is more secure with a bit of computational overhead to support several positive properties in security and privacy.

Exploring the need for a suitable privacy framework for mHealth when managing chronic diseases

The widespread rises in chronic illnesses (e.g., diabetes and high blood pressure) have resulted in the need to find more efficient ways of managing patients with these conditions. One such way is by the use of mobile health (mHealth) technologies that can gather real-time data from patients and monitor them from a distance, removing the need to be at a medical facility. These technologies can be an integral part of intelligent healthcare environments (e.g., smart homes to monitor and assist elderly patients) which are essential to reducing healthcare costs and improving efficiency. The use of mHealth, however, brings various privacy concerns and challenges. This paper reviews and examines the challenges of preserving user privacy in the context of using mHealth to manage chronic diseases. The paper first discusses mHealth, its importance in managing chronic diseases, and the associated privacy concerns. Second, the paper compares the existing privacy frameworks applicable to mHealth. Third, the key principles gathered from the frameworks are analysed in the context of their suitability for enabling adequate privacy when using mHealth for managing chronic diseases. Finally, the paper argues that a new privacy framework is needed for mHealth in the context of managing chronic diseases.

A framework for secure and privacy protected collaborative contents sharing using public OSN

A major issue thoroughly raised and potentially vulnerable in online social networks (OSNs) is the user privacy preservation. Generally, the issue of privacy is tackled from the user point of view without considering the service providers and the third-party data collectors, who can manipulate user data for third party advertisement and behavioral analysis. Therefore, the privacy risk exists not only from the unauthorized users but also from the OSN service providers. To secure data from both the unauthorized users and OSN service providers a framework for collaborative contents sharing is proposed. In the proposed framework, contents are secured at the time of data dissemination and provided assurance about the data sharing among the legitimate users based on collaborative contents sharing. The proposed framework assures not only the confidentiality of contents but also the privacy of data owner and co-owners in OSN. An architecture is provided to support the theoretical and practical basis for the proposed framework; which exhibits the objective of preserving user and contents privacy.

Off-the-Hook: An Efficient and Usable Client-Side Phishing Prevention Application

Phishing is a major problem on the Web. Despite the significant attention it has received over the years, there has been no definitive solution. While the state-of-the-art solutions have reasonably good performance, they suffer from several drawbacks including potential to compromise user privacy, difficulty of detecting phishing websites whose content change dynamically, and reliance on features that are too dependent on the training data. To address these limitations we present a new approach for detecting phishing webpages in real-time as they are visited by a browser. It relies on modeling inherent phisher limitations stemming from the constraints they face while building a webpage. Consequently, the implementation of our approach, Off-the-Hook , exhibits several notable properties including high accuracy, brand-independence and good language-independence, speed of decision, resilience to dynamic phish and resilience to evolution in phishing techniques. Off-the-Hook is implemented as a fully-client-side browser add-on, which preserves user privacy. In addition, Off-the-Hook identifies the target website that a phishing webpage is attempting to mimic and includes this target in its warning. We evaluated Off-the-Hook in two different user studies. Our results show that users prefer Off-the-Hook warnings to Firefox warnings.

Forward and backward secure fuzzy encryption for data sharing in cloud computing

The great benefits introduced by big data analysis technology motivate both individuals and enterprises to collect and share the data over the internet. Although cloud storage provides a perfect platform for data sharing, the security issue becomes the principal obstacle to preventing users from outsourcing their data to cloud servers, especially when the data involve sensitive information. As a new variant of public-key encryption scheme, attribute-based encryption (ABE) provides a fuzzy matching between the data encryptor and decryptor. That is, the encryptor ensures that all those users with attributes satisfying the defined access policy can decrypt the shared data, but cannot identify which one can do that. Thus, the ABE scheme can preserve user privacy, and is regarded as a promising solution of securing data sharing in the cloud storage system. But the original ABE scheme cannot be directly deployed for several practical issues, such as key exposure and user revocation. In this paper, we simultaneously conquer the above two issues and put forward a forward and backward secure ciphertext-policy ABE scheme such that a revealed user secret key is useless for decrypting any ciphertexts. The proposed forward and backward secure ABE scheme is proved secure under a q-type assumption in the selective model, without random oracles. The performance discussion indicates that the proposed scheme provides stronger security guarantees than other similar ABE schemes, and thus is more desirable for cloud storage systems.

EPPRD: An Efficient Privacy-Preserving Power Requirement and Distribution Aggregation Scheme for a Smart Grid.

A Smart Grid (SG) facilitates bidirectional demand-response communication between individual users and power providers with high computation and communication performance but also brings about the risk of leaking users’ private information. Therefore, improving the individual power requirement and distribution efficiency to ensure communication reliability while preserving user privacy is a new challenge for SG. Based on this issue, we propose an efficient and privacy-preserving power requirement and distribution aggregation scheme (EPPRD) based on a hierarchical communication architecture. In the proposed scheme, an efficient encryption and authentication mechanism is proposed for better fit to each individual demand-response situation. Through extensive analysis and experiment, we demonstrate how the EPPRD resists various security threats and preserves user privacy while satisfying the individual requirement in a semi-honest model; it involves less communication overhead and computation time than the existing competing schemes.

Privacy-Preserving Power Injection Over a Hybrid AMI/LTE Smart Grid Network

The future smart grid will enable homes to have energy storage units that can store the excess power generated from renewable energy sources and sell it to the grid during the peak hours. Realization of this process, however, requires the utility company to be able to communicate with the storage units whenever needed. Nonetheless, the security and the privacy of this communication is essential to not only ensure a fair energy selling market but also eliminate any privacy concerns of the users due to potential exposure of their energy levels. In this paper, we propose a secure and privacy-preserving power injection querying scheme by exploiting the already available advanced metering infrastructure (AMI) and long-term evolution (LTE) cellular networks. The idea is based on collecting power injection bids from storage units and sending their aggregated value to the utility rather than the individual bids in order to preserve user privacy. We also develop a bilinear pairing-based technique to enable the utility company to ensure the integrity and authenticity of the aggregated bid without accessing the individual bids. In this way, no party will have access to the storage units’ individual bids and use them to achieve unfair financial gains. We implemented the proposed scheme in an integrated AMI/LTE network using the ns-3 network simulator. Our evaluations have demonstrated that the proposed scheme is secure and can protect user privacy with acceptable communication and computation overhead.

Privacy preserving security using biometrics in cloud computing

Cloud computing and the efficient storage provide new paradigms and approaches designed at efficiently utilization of resources through computation and many alternatives to guarantee the privacy preservation of individual user. It also ensures the integrity of stored cloud data, and processing of stored data in the various data centers. However, to provide better protection and management of sensitive information (data) are big challenge to maintain the confidentiality and integrity of data in the cloud computation. Thus, there is an urgent need for storing and processing the data in the cloud environment without any information leakage. The sensitive data require the storing and processing mechanism and techniques to assurance the privacy preservation of individual user, to maintain the data integrity, and preserve confidentiality. Face recognition has recently achieved advancements in the unobtrusive recognition of individuals to maintain the privacy-preservation in the cloud computing. This paper emphasizes on cloud security and privacy issues and provides the solution using biometric face recognition. We propose a biometrics face recognition approach for security and privacy preservation of cloud users during their access to cloud resources. The proposed approach has three steps: (1) acquisition of face images (2) preprocessing and extraction of facial feature (3) recognition of individual using encrypted biometric feature. The experimental results establish that our proposed recognition approach can ensure the privacy and security of biometrics data.

Local Suppression and Splitting Techniques for Privacy Preserving Publication of Trajectories

We study the problem of preserving user privacy in the publication of location sequences. Consider a database of trajectories, corresponding to movements of people, captured by their transactions when they use credit cards, RFID debit cards, or NFC ( http://en.wikipedia.org/wiki/Near_field_communication ) compliant devices. We show that, if such trajectories are published exactly (by only hiding the identities of persons that followed them), one can use partial trajectory knowledge as a quasi-identifier for the remaining locations in the sequence. We devise four intuitive techniques, based on combinations of locations suppression and trajectories splitting, and we show that they can prevent privacy breaches while keeping published data accurate for aggregate query answering and frequent subsets data mining.

Optimal Pick up Point Selection for Effective Ride Sharing

Car occupancy rates (travelers per vehicle) are currently very low in most developed countries, for example, on average between 1.15 and 1.25 in Australia. Enabling shared rides on short notice can be an effective solution to counter the problem of increasing traffic through the use of the untapped transportation capacity. Common inhibitors for the uptake of ride sharing services are privacy and safety concerns. We present an approach to ride sharing where the pick up/drop off locations for passengers are selected from a fixed set, which has the advantage of increased safety through video surveillance. We present a scheme that chooses optimally fixed locations of Pick up Points (PuPs) and aims to maximize the car occupancy rates while preserving user privacy and safety. Our method enhances privacy as the users do not need to provide their precise home/work locations. We have extended the well studied 1-coverage problem, i.e., to cover an area with the minimum number of circles of a given radius [1] , to road networks. The challenges for road networks are the varying population densities of suburbs which requires circles of different radii. The aim is to ensure that every point of a city's area is covered by at least one PuP while minimizing the total number of PuPs. By ensuring that we have different circle radii for PuPs the anonymity of individuals is the same throughout. Using Voronoi diagrams we present a k -anonymity model that guarantees a minimum number of individuals covered by every PuP. Our problem is a multi objective problem where we aim to maximize coverage, k -anonymity and privacy provided by the system to its users while facilitating ride sharing. Through greedy randomized adaptive search procedure (GRASP) we find out the Pareto front of solutions and evaluate their impact on ride sharing.

A New Efficient Chaotic Maps Based Three Factor User Authentication and Key Agreement Scheme

In order to provide secure remote access control, a robust and efficient authentication protocol should achieve mutual authentication and session key agreement between clients and the server over public channels. Recently, Wang et al. proposed a password based authentication protocol using chaotic maps. In this paper, we demonstrate the security of their scheme, and show that Wang et al.’s scheme cannot provide session key agreement and is insecure against denial of service attack for no detecting wrong password in password change. To remedy these issues, we use the techniques of fuzzy extractor and chaotic maps to propose a three-factor remote authentication scheme. The new scheme preserves user privacy and is secure against various attacks. Detailed analysis of previous schemes in efficiency and security shows our proposed scheme is more suitable for practical application.

Towards privacy-preserving user targeting

User targeting via behavioral analysis is becoming increasingly prevalent in online messaging services. By taking into account users’ behavior information such as geographic locations, purchase behaviors, and search histories, vendors can deliver messages to users who are more likely to have a strong preference. For example, advertisers can rely on some ad-network for distributing ads to targeted users. However, collecting such personal information for accurate targeting raises severe privacy concerns. In order to incentivize users to participate in such behavioral targeting systems, addressing the privacy concerns becomes of paramount importance. We provide a survey of privacy-preserving user targeting. We present the architectures of user targeting, the security threats faced by user targeting, and existing approaches to privacy-preserving user targeting. Some future research directions are also identified.

Design of a Secure Authentication and Key Agreement Scheme Preserving User Privacy Usable in Telecare Medicine Information Systems

Authentication and key agreement schemes play a very important role in enhancing the level of security of telecare medicine information systems (TMISs). Recently, Amin and Biswas demonstrated that the authentication scheme proposed by Giri et al. is vulnerable to off-line password guessing attacks and privileged insider attacks and also does not provide user anonymity. They also proposed an improved authentication scheme, claiming that it resists various security attacks. However, this paper demonstrates that Amin and Biswas's scheme is defenseless against off-line password guessing attacks and replay attacks and also does not provide perfect forward secrecy. This paper also shows that Giri et al.'s scheme not only suffers from the weaknesses pointed out by Amin and Biswas, but it also is vulnerable to replay attacks and does not provide perfect forward secrecy. Moreover, this paper proposes a novel authentication and key agreement scheme to overcome the mentioned weaknesses. Security and performance analyses show that the proposed scheme not only overcomes the mentioned security weaknesses, but also is more efficient than the previous schemes.