Security Analysis and Enhancement for Prefix-Preserving Encryption Schemes

Prefix-preserving encryption (PPE) is an important type of encryption scheme, having a wide range of applications, such as IP addresses anonymization, prefix-matching search, and rang search. There are two issues in PPE schemes, security proof and single key requirement. Existing security proofs for PPE only reduce the security of a real PPE scheme to that of the ideal PPE object by showing their computational indistinguishability \cite{Ama07,Xu02}. Such security proof is incomplete since the security of the ideal encryption object is unknown. Also, existing prefix-preserving encryption schemes only consider a single encryption key, which is infeasible for a practical system with multiple users (Implying that all users should have the single encryption key in order to encrypt or decrypt confidential data). In this paper we develop a novel mechanism to analyze the security of the ideal PPE object. We follow the modern cryptographic approach and create a new security notion IND-PCPA. Then, we show that such weakened security notion is necessary and the ideal PPE object is secure under IND-PCPA. We also design a new, security-enhanced PPE protocol to support its use in multi-user systems, where no single entity in the system knows the PPE key. The protocol secret shares and distributes the PPE key to a group of key agents and let them ``distributedly encrypt\u27\u27 critical data. We develop a novel distributed PPE algorithm and the corresponding request and response protocols. Experimental results show that the protocol is feasible in practical systems

Enabling Access Control for Encrypted Multi-Dimensional Data in Cloud Computing through Range Search

With the growing popularity of cloud computing, data owners are increasingly opting to outsource their data to cloud servers due to the numerous benefits it offers. However, this outsourcing raises concerns about data privacy since the data stored on remote cloud servers is not directly controlled by the owners. Encryption of the data is an effective approach to mitigate these privacy concerns. However, encrypted data lacks distinguishability, leading to limitations in supporting common operations such as range search and access control. In this research paper, we propose a method called RSAC (Range Search Supporting Access Control) for encrypted multi-dimensional data in cloud computing. Our method leverages policy design, bucket embedding, algorithm design, and Ciphertext Policy-Attribute Based Encryption (CPABE) to achieve its objectives. We present extensive experimental results that demonstrate the efficiency of our method and conduct a thorough security analysis to ensure its robustness. Our proposed RSAC method addresses the challenges of range search and access control over encrypted multi-dimensional data, thus contributing to enhancing privacy and security in cloud computing environments

Iris Recognition Approach for Preserving Privacy in Cloud Computing

Biometric identification systems involve securing biometric traits by encrypting them using an encryption algorithm and storing them in the cloud. In recent decades, iris recognition schemes have been considered one of the most effective biometric models for identifying humans based on iris texture, due to their relevance and distinctiveness. The proposed system focuses on encrypting biometric traits. The user’s iris feature vector is encrypted and stored in the cloud. During the matching process, the user’s iris feature vector is compared with the one stored in the cloud. If it meets the threshold conditions, the user is authenticated. Iris identification in cloud computing involves several steps. First, the iris image is pre-processed to remove noise using the Hough transform. Then, the pixel values are normalized, Gabor filters are applied to extract iris features. The features are then encrypted using the AES 128-bit algorithm. Finally, the features of the test image are matched with the stored features on the cloud to verify authenticity. The process ensures the privacy and security of the iris data in cloud storage by utilizing encryption and efficient image processing techniques. The matching is performed by setting an appropriate threshold for comparison. Overall, the approach offers a significant level of safety, effectiveness, and accuracy

Revealing Encryption for Partial Ordering

We generalize the cryptographic notion of Order Revealing Encryption (ORE) to arbitrary functions and we present a construction that allows to determine the (partial) ordering of two vectors i.e., given E(x) and E(y) it is possible to learn whether x is less than or equal to y, y is less than or equal to x or whether x and y are incomparable. This is the first non-trivial example of a Revealing Encryption (RE) scheme with output larger than one bit, and which does not rely on cryptographic obfuscation or multilinear maps

SDA-SM: An Efficient Secure Data Aggregation Scheme using Separate MAC across Wireless Sensor Networks

Securing the aggregated data of the wireless sensor networks (WSNs) is a vital issue to minimize energy consumption and face potential attacks. This paper presents a novel end to end encryption scheme defined as Aggregating Secure Data -Separate MAC (SDA-SM). The importance of the SDA-SM is twofold. First, it separates the secured aggregated data and the message authentication codes (MAC) into two different packets. Second, it transmits these packets in a random separate time-slot according to the scheduling of the TDMA. Moreover, the TDMA applied in the LEACH protocol is modified to adequate to the proposed SDA-SM scheme. The SDA-SM uses MACs to verify the integrity of the aggregated data and uses a sensor protected identifier to authenticate the source of data. The simulation results of the experiments assure the SDA-SM objectives can be achieved with less computation of the communication overheads than earlier techniques. Besides, SDA-SM will be able to accomplish the integrity and confidentiality of accurate aggregated data while saving the energy to prolong the network lifetime

Protocols and Architecture for Privacy-preserving Authentication and Secure Message Dissemination in Vehicular Ad Hoc Networks

The rapid development in the automotive industry and wireless communication technologies have enhanced the popularity of Vehicular ad hoc networks (VANETs). Today, the automobile industry is developing sophisticated sensors that can provide a wide range of assistive features, including accident avoidance, automatic lane tracking, semi-autonomous driving, suggested lane changes, and more. VANETs can provide drivers a safer and more comfortable driving experience, as well as many other useful services by leveraging such technological advancements. Even though this networking technology enables smart and autonomous driving, it also introduces a plethora of attack vectors. However, the main issues to be sorted out and addressed for the widespread deployment/adoption of VANETs are privacy, authenticating users, and the distribution of secure messages. These issues have been addressed in this dissertation, and the contributions of this dissertation are summarized as follows: Secure and privacy-preserving authentication and message dissemination in VANETs: Attackers can compromise the messages disseminated within VANETs by tampering with the message content or sending malicious messages. Therefore, it is crucial to ensure the legitimacy of the vehicles participating in the VANETs as well as the integrity and authenticity of the messages transmitted in VANETs. In VANET communication, the vehicle uses pseudonyms instead of its real identity to protect its privacy. However, the real identity of a vehicle must be revealed when it is determined to be malicious. This dissertation presents a distributed and scalable privacy-preserving authentication and message dissemination scheme in VANET. Low overhead privacy-preserving authentication scheme in VANETs: The traditional pseudonym-based authentication scheme uses Certificate Revocation Lists (CRLs) to store the certificates of revoked and malicious entities in VANETs. However, the size of CRL increases significantly with the increased number of revoked entities. Therefore, the overhead involved in maintaining the revoked certificates is overwhelming in CRL-based solutions. This dissertation presents a lightweight privacy-preserving authentication scheme that reduces the overhead associated with maintaining CRLs in VANETs. Our scheme also provides an efficient look-up operation for CRLs. Efficient management of pseudonyms for privacy-preserving authentication in VANETs: In VANETs, vehicles change pseudonyms frequently to avoid the traceability of attackers. However, if only one vehicle out of 100 vehicles changes its pseudonym, an intruder can easily breach the privacy of the vehicle by linking the old and new pseudonym. This dissertation presents an efficient method for managing pseudonyms of vehicles. In our scheme, vehicles within the same region simultaneously change their pseudonyms to reduce the chance of linking two pseudonyms to the same vehicle

Trading Indistinguishability-based Privacy and Utility of Complex Data

The collection and processing of complex data, like structured data or infinite streams, facilitates novel applications. At the same time, it raises privacy requirements by the data owners. Consequently, data administrators use privacy-enhancing technologies (PETs) to sanitize the data, that are frequently based on indistinguishability-based privacy definitions. Upon engineering PETs, a well-known challenge is the privacy-utility trade-off. Although literature is aware of a couple of trade-offs, there are still combinations of involved entities, privacy definition, type of data and application, in which we miss valuable trade-offs. In this thesis, for two important groups of applications processing complex data, we study (a) which indistinguishability-based privacy and utility requirements are relevant, (b) whether existing PETs solve the trade-off sufficiently, and (c) propose novel PETs extending the state-of-the-art substantially in terms of methodology, as well as achieved privacy or utility. Overall, we provide four contributions divided into two parts. In the first part, we study applications that analyze structured data with distance-based mining algorithms. We reveal that an essential utility requirement is the preservation of the pair-wise distances of the data items. Consequently, we propose distance-preserving encryption (DPE), together with a general procedure to engineer respective PETs by leveraging existing encryption schemes. As proof of concept, we apply it to SQL log mining, useful for database performance tuning. In the second part, we study applications that monitor query results over infinite streams. To this end, -event differential privacy is state-of-the-art. Here, PETs use mechanisms that typically add noise to query results. First, we study state-of-the-art mechanisms with respect to the utility they provide. Conducting the so far largest benchmark that fulfills requirements derived from limitations of prior experimental studies, we contribute new insights into the strengths and weaknesses of existing mechanisms. One of the most unexpected, yet explainable result, is a baseline supremacy. It states that one of the two baseline mechanisms delivers high or even the best utility. A natural follow-up question is whether baseline mechanisms already provide reasonable utility. So, second, we perform a case study from the area of electricity grid monitoring revealing two results. First, achieving reasonable utility is only possible under weak privacy requirements. Second, the utility measured with application-specific utility metrics decreases faster than the sanitization error, that is used as utility metric in most studies, suggests. As a third contribution, we propose a novel differential privacy-based privacy definition called Swellfish privacy. It allows tuning utility beyond incremental -event mechanism design by supporting time-dependent privacy requirements. Formally, as well as by experiments, we prove that it increases utility significantly. In total, our thesis contributes substantially to the research field, and reveals directions for future research