Lightweight attribute-based encryption supporting access policy update for cloud assisted IoT

Cloud-assisted IoT applications are gaining an expanding interest, such that IoT devices are deployed in different distributed environments to collect and outsource sensed data to remote servers for further processing and sharing among users. On the one hand, in several applications, collected data are extremely sensitive and need to be protected before outsourcing. Generally, encryption techniques are applied at the data producer side to protect data from adversaries as well as curious cloud provider. On the other hand, sharing data among users requires fine grained access control mechanisms. To ensure both requirements, Attribute Based Encryption (ABE) has been widely applied to ensure encrypted access control to outsourced data. Although, ABE ensures fine grained access control and data confidentiality, updates of used access policies after encryption and outsourcing of data remains an open challenge. In this paper, we design PU-ABE, a new variant of key policy attribute based encr yption supporting efficient access policy update that captures attributes addition and revocation to access policies. PU-ABE contributions are multifold. First, access policies involved in the encryption can be updated without requiring sharing secret keys between the cloud server and the data owners neither re-encrypting data. Second, PU-ABE ensures privacy preserving and fine grained access control to outsourced data. Third, ciphertexts received by the end-user are constant sized and independent from the number of attributes used in the access policy which affords low communication and storage costs

Fuzzy Identity Based Encryption with a flexible threshold value

The issue of data and information security on the internet and social network has become more serious and pervasive in recent years. Cryptography is used to solve security problems. However, message encryption cannot merely meet the intended goals because access control over the encrypted messages is required in some applications. To achieve these requirements, attribute-based encryption (ABE) is used. This type of encryption provides both security and access structure for the network users simultaneously. Fuzzy Identity-Based Encryption (FIBE) is a special mode of ABE that provides a threshold access structure for the users. This threshold value is set by the authority for users, which is always fixed and cannot be changed. So, the sender (encryptor) will not play a role in determining the threshold value. The mentioned issue exists also in Key Policy Attribute Based Encryption (KP-ABE) schemes. In this paper, we present a FIBE scheme in addition to the authority, the sender also plays a role in determining the threshold value. Thus, the policy will be more flexible than previous FIBE schemes in that the threshold value is selected only by the authority. We can call the proposed scheme a dual-policy ABE. The proposed technique for flexibility of threshold value can be applied in most of the existing KP-ABE schemes. We use the (indistinguishable) selective security model for security proof. The hardness assumption that we use is the modified bilinear decision Diffie-Hellman problem

Accountable privacy preserving attribute based framework for authenticated encrypted access in clouds

In this paper, we propose an accountable privacy preserving attribute-based framework, called Ins-PAbAC, that combines attribute based encryption and attribute based signature techniques for securely sharing outsourced data contents via public cloud servers. The proposed framework presents several advantages. First, it provides an encrypted access control feature, enforced at the data owner’s side, while providing the desired expressiveness of access control policies. Second, Ins-PAbAC preserves users’ privacy, relying on an anonymous authentication mechanism, derived from a privacy preserving attribute based signature scheme that hides the users’ identifying information. Furthermore, our proposal introduces an accountable attribute based signature that enables an inspection authority to reveal the identity of the anonymously-authenticated user if needed. Third, Ins-PAbAC is provably secure, as it is resistant to both curious cloud providers and malicious users adversaries. Finally, experimental results, built upon OpenStack Swift testbed, point out the applicability of the proposed scheme in real world scenarios

PU-ABE : lightweight attribute-based encryption supporting access policy update for cloud assisted IoT

Cloud-assisted IoT applications are gaining an expanding interest, such that IoT devices are deployed in different distributed environments to collect and outsource sensed data to remote servers for further processing and sharing among users. On the one hand, in several applications, collected data are extremely sensitive and need to be protected before outsourcing. Generally, encryption techniques are applied at the data producer side to protect data from adversaries as well as curious cloud provider. On the other hand, sharing data among users requires fine grained access control mechanisms. To ensure both requirements, Attribute Based Encryption (ABE) has been widely applied to ensure encrypted access control to outsourced data. Although, ABE ensures fine grained access control and data confidentiality, updates of used access policies after encryption and outsourcing of data remains an open challenge. In this paper, we design PU-ABE, a new variant of key policy attribute based encryption supporting efficient access policy update that captures attributes addition to access policies. PUABE contributions are multifold. First, access policies involved in the encryption can be updated without requiring sharing secret keys between the cloud server and the data owners neither re-encrypting data. Second, PUABE ensures privacy preserving and fine grained access control to outsourced data. Third, ciphertexts received by the end-user are constant sized and independent from the number of attributes used in the access policy which affords low communication and storage costs

Privacy Enhancing Technologies for solving the privacy-personalization paradox : taxonomy and survey

Personal data are often collected and processed in a decentralized fashion, within different contexts. For instance, with the emergence of distributed applications, several providers are usually correlating their records, and providing personalized services to their clients. Collected data include geographical and indoor positions of users, their movement patterns as well as sensor-acquired data that may reveal users’ physical conditions, habits and interests. Consequently, this may lead to undesired consequences such as unsolicited advertisement and even to discrimination and stalking. To mitigate privacy threats, several techniques emerged, referred to as Privacy Enhancing Technologies, PETs for short. On one hand, the increasing pressure on service providers to protect users’ privacy resulted in PETs being adopted. One the other hand, service providers have built their business model on personalized services, e.g. targeted ads and news. The objective of the paper is then to identify which of the PETs have the potential to satisfy both usually divergent - economical and ethical - purposes. This paper identifies a taxonomy classifying eight categories of PETs into three groups, and for better clarity, it considers three categories of personalized services. After defining and presenting the main features of PETs with illustrative examples, the paper points out which PETs best fit each personalized service category. Then, it discusses some of the inter-disciplinary privacy challenges that may slow down the adoption of these techniques, namely: technical, social, legal and economic concerns. Finally, it provides recommendations and highlights several research directions