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Social networks are becoming increasingly popular nowadays. Users share personal information about themselves and other users in order to build and maintain their social network. However, the large amount of personal information available on social networks poses risks of data misuse. Although social networks offer users the possibility to specify privacy settings to regulate access to their information, these settings are often complicated and unintuitive, especially when dealing with new modalities of social communication like tagging. In this paper we investigate the privacy consequences of information sharing in social networks. In particular, we formally analyze the impact of the privacy settings and the use of tagging in Facebook on the visibility of information. To increase users’ awareness of the risks of information sharing and empower users to control their information, we present a tool for determining the visibility of users’ information based on their privacy settings and tagging.

Searchable encryption allows a party to search over encrypted data without decrypting it. Prior schemes in the symmetric setting deal only with exact or similar keyword matches. We describe a scheme for the problem of wildcard searches over encrypted data to make search queries more flexible, provide a security proof for our scheme and com- pare the computational, communication and space complexity with existing schemes. We develop an efficient scheme, using pseudorandom functions and Bloom filters, that supports wildcard searches over encrypted data. The scheme also supports conjunctive wildcard searches, efficient and secure updates and is more efficient than previous solutions. Besides, our construction is independent of the encryption method of the remote data and is practical to use in real world applications.

Online multimedia distribution is often done by means of adaptive streaming protocols. To protect this content, its owners apply a unique watermark to each copy. However, sending a unique copy to each client incurs a prohibitive cost, especially in terms of bandwidth and server load, and embedding a watermark on a client device not only compromises the system security, but also is not feasible in the uncontrolled environment such as the Internet. In this paper, we propose to solve this problem by creating a few streams, each with different but constant watermarks, and force the client to switch between the streams. This will result in a uniquely watermarked stream for the each client. We illustrate our solution on the example of the currently deployed adaptive streaming protocols.

Information sharing helps to better protect computer sys- tems against digital threats and known attacks. However, since security information is usually considered sensitive, parties are hesitant to share all their information through public channels. Instead, they only exchange this informa- tion with parties with whom they already established trust relationships. We propose the use of two complementary techniques to allow parties to share information without the need to im- mediately reveal private information. We consider a crypto- graphic approach to hide the details of an indicator of com- promise so that it can be shared with other parties. These other parties are still able to detect intrusions with these cryptographic indicators. Additionally, we apply another cryptographic construction to let parties report back their number of sightings to a central party. This central party can aggregate the messages from the various parties to learn the total number of sightings for each indicator, without learning the number of sightings from each individual party. An evaluation of our open-source proof-of-concept imple- mentations shows that both techniques incur only little over- head, making the techniques prime candidates for practice. © 2016 ACM. ACM SIGSAC

Physical unclonable functions (PUFs) can be used as a cost-effective means to store cryptographic key material in an unclonable way. They can be employed for strong authentication of objects, e.g., tokens, and of persons possessing such tokens, but also for other purposes. We give a short overview of security applications where PUFs are useful, and discuss physical realisations, noisy measurements and information content of PUFs. Then we describe an integrated authentication token containing an optical PUF, a challenging mechanism and a detector. Finally, we discuss authentication protocols for controlled and uncontrolled PUFs.

Privacy is becoming a serious concern in the connected world. This chapter presents privacy issues, requirements and privacy protection concepts related to consumers’ private content. First, privacy issues and requirements are described by means of several scenarios. Then, a DRM approach for protecting ownership and controlled sharing of private content is presented. A system is introduced for realizing such a privacy-enhancing approach for home media centers. Particular solutions for protecting and sharing personal content, ownership management, and content deletion in a privacy-preserving way are described.

Aggregation of time-series data offers the possibility to learn certain statistics over data periodically uploaded by different sources. In case of privacy sensitive data, it is desired to hide every data provider's individual values from the other participants (including the data aggregator). Existing privacy preserving time-series data aggregation schemes focus on the sum as aggregation means, since it is the most essential statistics used in many applications such as smart metering, participatory sensing, or appointment scheduling. However, all existing schemes have an important drawback: they do not provide verifiable outputs, thus users have to trust the data aggregator that it does not output fake values. We propose a publicly verifiable data aggregation scheme for privacy preserving time-series data summation. We prove its security and verifiability under the XDH assumption and a widely used, strong variant of the Co-CDH assumption. Moreover, our scheme offers low computation complexity on the users' side, which is essential in many applications.

This paper reflects on security, privacy and trust from the point of you of the innovation in information and communication technologies. It also considers social, economic and legal aspects that need to be taken into account in the development cycles of new technologies. Finally, the major research challenges, which need to be overcome to ensure the future of the digital world, protect people privacy and enable even more rapid innovation, have been discussed.

This book constitutes the refereed proceedings of the 10th VLDB Workshop on Secure Data Management held in Trento, Italy, on August 30, 2013. The 15 revised full papers and one keynote paper presented were carefully reviewed and selected from various submissions. The papers are organized in technical papers and 10 vision papers which address key challenges in secure data management and indicate interesting research questions.

We treat the problem of privacy-preserving statistics verification in clinical research. We show that given aggregated results from statistical calculations, we can verify their correctness efficiently, without revealing any of the private inputs used for the calculation. Our construction is based on the primitive of Secure Multi-Party Computation from Shamir's Secret Sharing. Basically, our setting involves three parties: a hospital, which owns the private inputs, a clinical researcher, who lawfully processes the sensitive data to produce an aggregated statistical result, and a third party (usually several verifiers) assigned to verify this result for reliability and transparency reasons. Our solution guarantees that these verifiers only learn about the aggregated results (and what can be inferred from those about the underlying private data) and nothing more. By taking advantage of the particular scenario at hand (where certain intermediate results, e.g., the mean over the dataset, are available in the clear) and utilizing secret sharing primitives, our approach turns out to be practically efficient, which we underpin by performing several experiments on real patient data. Our results show that the privacy-preserving verification of the most commonly used statistical operations in clinical research presents itself as an important use case, where the concept of secure multi-party computation becomes employable in practice.

To address today’s major concerns of health service providers regarding security, resilience and data protection when moving on the cloud, we propose an approach to build a trustworthy healthcare platform cloud, based on a trustworthy cloud infrastructure. This paper first highlights the main security and privacy risks of market available commodity clouds, and outlines security and privacy requirements of a trustworthy health platform cloud, on top of which to deploy various health applications, in compliance with EU data protection legislation. Results from the recent EU TClouds project will be described as a possible solution towards trustworthy cloud architecture, based on a federated cloud-of-clouds, while enforcing security, resilience and data protection in various cloud layers for provisioning trustworthy IaaS, PaaS and SaaS healthcare services.

Onderzoek naar het gebruik en de waardering van de buitenruimte in Hart van Zuid. In opdracht van de Gemeente Rotterdam, Projectbureau het Hart van Zuid.

Preface. This year was the eighth edition of the VLDB Secure Data Management Workshop. The topic of data security remains an important area of research especially due to the steady growing proliferation of emerging data services such as cloud computing, location-based services, and health-related services. Confidentiality is the main driver for the research that covers topics such as privacy-enhancing technologies, access control, and search in encrypted data. We received 19 submissions of which the Program Committee selected 10 papers to be presented at the workshop and included in the proceedings (approx. 50% acceptance rate).We hope the papers collected in this volume will stimulate your research in this area. The regular papers in the proceedings are grouped into three sections. The first section focuses on privacy. The papers in this section present a study in privacy violations followed by application-driven work on algorithms. The second section focuses on data security in networks. The papers address issues related to management of confidential data that are stored in cloud and sensor networks. The third section groups a collection of more basic secure data management techniques that can find their way toward many different application settings. We wish to thank all the authors of submitted papers for their high-quality submissions. We would also like to thank the Program Committee members as well as additional referees for doing an excellent review job. Finally, let us acknowledge Luan Ibraimi who helped in the technical preparation of the proceedings.

Data protection legislation requires personal data to be collected and processed only for lawful and legitimate purposes. Unfortunately, existing protection mechanisms are not appropriate for purpose control: they only prevent unauthorized actions from occurring and do not guarantee that the data are actually used for the intended purpose. In this paper, we present a flexible framework for purpose control, which connects the intended purpose of data to the business model of an organization and detects privacy infringements by determining whether the data have been processed only for the intended purpose.

A sample preparation method combining solid-phase extraction (SPE) and liquid-liquid extraction (LLE) was developed to be used in Effect-Directed Analysis (EDA) of blood plasma. Until now such a method was not available. It can be used for extraction of a broad range of thyroid hormone (TH)-disruptors from plasma with high recoveries. Validation of the method using spiked cow plasma showed good recoveries for hydroxylated polybrominated diphenyl ethers (OH-PBDEs; 93.8 ± 19.5%), hydroxylated polychlorinated biphenyls (OH-PCBs; 93.8 ± 15.5%), other halogenated phenols (OHPs; 107 ± 8.1%), and for short-chain (

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Searchable encryption is a technique that allows a client to store documents on a server in encrypted form. Stored documents can be retrieved selectively while revealing as little information as possible to the server. In the symmetric searchable encryption domain, the storage and the retrieval are performed by the same client. Most conventional searchable encryption schemes suffer from two disadvantages. First, searching the stored documents takes time linear in the size of the database, and/or uses heavy arithmetic operations. Secondly, the existing schemes do not consider adaptive attackers; a search-query will reveal information even about documents stored in the future. If they do consider this, it is at a significant cost to the performance of updates. In this paper we propose a novel symmetric searchable encryption scheme that offers searching at constant time in the number of unique keywords stored on the server. We present two variants of the basic scheme which differ in the efficiency of search and storage. We show how each scheme could be used in a personal health record system. Fulltext Preview

Preface. The new emerging technologies put new requirements on security and data management. As data are accessible anytime anywhere, it becomes much easier to get unauthorized data access. Furthermore, the use of new technologies has brought some privacy concerns. It becomes simpler to collect, store, and search personal information thereby endangering people’s privacy. Therefore, research in secure data management is gaining importance, attracting the attention of both the data management and the security research communities. The interesting problems range from traditional topics, such as, access control and general database security, via privacy protection to new research directions, such as cryptographically enforced access control and encrypted databases. This year, the call for papers attracted 24 papers both from universities and industry. For presentation at the workshop, the Program Committee selected 10 full papers (41% acceptance rate). These papers are collected in this volume, which we hope will serve as a useful research and reference material. The papers in the proceeding are grouped into three sections. The first section focuses on database security which remains an important research area. The papers in this section address several interesting topics including query optimization in encrypted databases, database provenance, database intrusion detection, and confidence policy compliant query evaluation. The second section changes the focal point to the topic of access control. The papers in this section deal with provenance access control, access control model for collaborative editors, self-modifying access control policies, and enforcing access control on XML documents. The third section focuses on privacy protection addressing the privacy issues around location-based services and anonymity/diversity for the micro-data release problem. We wish to thank all the authors of submitted papers for their high-quality submissions. We would also like to thank the Program Committee members as well as additional referees for doing an excellent review job. Finally, let us acknowledge Luan Ibraimi who helped in the technical preparation of the proceedings.

This chapter addresses privacy issues in DRM systems. These systems provide a means of protecting digital content, but may violate the privacy of users in that the content they purchase and their actions in the system can be linked to specific users. The chapter proposes a privacy-preserving DRM system in which users interact with the system in an pseudonymous way, while preserving all security requirements of usual DRM systems. To achieve this goal, a set of protocols and methods is proposed for managing user identities and interactions with the basic system during acquisition and consumption of digital content. Privacy-enhancing extensions are also proposed. Unlinkable purchase of content, which prevents content providers from linking all content purchased by a given user, is discussed. Moreover, a method which allows a user to transfer content rights to another user without the two users being linked by the content provider is provided.

This chapter reviews the most important security and privacy issues of the modern digital world, emphasizing the issues brought by the concept of ambient intelligence. Furthermore, the chapter explains the organization of the book, describing which issues and related technologies are addressed by which chapters of the book.

When private information is stored in databases that are under the control of others, the only possible way to protect it, is to encrypt it before storing it. In order to efficiently retrieve the data, a search mechanism is needed that still works over the encrypted data. In this chapter an overview of several search strategies is given. Some add meta-data to the database and do the searching only in the meta-data, others search in the data itself or use secret sharing to solve the problem. Each strategy has its own advantages and disadvantages.

In this chapter we address two approaches to extract high-level concepts from video footage and show the integrated use of both. We also describe an experiment used for validation.

In the framework of secure computation based on threshold homomorphic cryptosystems, we consider scenarios in which a lightweight client device provides encrypted input to a secure computation to be performed on the server side. The computational power at the server side is assumed to be much higher than on the client side. We show how to trade-off work for the client against work for the server such that the total amount of work increases moderately. These client-server trade-offs are considered in detail for two applications: private biometrics and electronic voting.

This chapter is a case study showing how important events (highlights) can be automatically detected in video recordings of Formula 1 car racing. Numerous approaches presented in literature have shown that it is becoming possible to extract interesting events from video. However, the majority of the approaches uses individual visual or audio cues. According to the current understanding of human perception it is expected that using evidence obtained from different modalities should result in a more robust and accurate perception of video. On the other hand, fusion of multimodal evidence is quite challenging, since it has to deal with indications which may contradict each other. In this chapter we deal with three topics, one being fusion of evidence from different modalities.