Untrusted Storage Research Articles

A Survey on Attribute-Based Encryption Schemes Suitable for the Internet of Things

The Internet of Things (IoT) is an information service paradigm based on the integration of smart objects, mobile devices, and computers via the Internet. IoT technologies are key enablers for a multitude of applications in diverse fields, such as digital health, smart city, industrial automation, and supply chain. This raises new security and privacy challenges that can be addressed by advanced cryptographic methods. One of the most prominent is attribute-based encryption (ABE), which allows one to encrypt data while enforcing fine-grained access control on it. ABE is advantageous in many IoT applications since it allows data to be safely stored on untrusted storage, such as third-party cloud servers, hackable publish-subscribe brokers, physically accessible sensors, etc. This article surveys the ABE literature proposing schemes and solutions that are best suited for IoT applications. To do so, it first identifies three performance indicators that are key in IoT, namely, the data producer CPU efficiency, the data producer bandwidth efficiency, and the key authority bandwidth efficiency. Then, it analyzes only those schemes that are promising from the point of view of one or more indicators and, therefore, more applicable in typical IoT applications. As a further contribution, this article selects a subset of representative schemes and assesses their efficiency by thorough simulations. Such simulations show that no scheme excels in all three performance indicators at once, but some simultaneously perform well in two indicators.

Cloud Storage Service Architecture Providing the Eventually Consistent Totally Ordered Commit History of Distributed Key-Value Stores for Data Consistency Verification

Cloud storage services are one of the most popular cloud computing service types these days. Various cloud storage services such as Amazon S3, DropBox, Google Drive, and Microsoft OneDrive currently support billions of users. Nevertheless, data consistency of the underlying distributed key-value store of cloud storage services remains a serious concern, making potential customers of cloud services hesitate to migrate their data to the cloud. Researchers have explored how to allow clients to verify the behavior of untrusted cloud storage services with respect to consistency models. However, previous proposals are limited because they rely on a strongly consistent history server to provide a totally ordered history for clients. This work presents Relief, a novel cloud storage service exposing an eventually consistent totally ordered commit history of the underlying distributed key-value store to enable client-side data consistency verification for various consistency models. By empirically evaluating our system, we demonstrate that Relief is an efficient solution to overcome the limitation of previous approaches.

Privacy preserving biometric authentication using Chaos on remote untrusted server

Biometric-based authentication systems are promising because of unique biometric features for each person. Generally, biometric features are generated , and biometric templates or bio-hash codes are calculated and stored in Authentication Data Table (ADT) along with userid. However, such hashing based authentication is vulnerable to precomputed table attacks. Also, in some cases, the service providers outsource the ADT to cloud or untrusted server. In this paper, a novel biometric-based authentication system is proposed using two servers: crypto-match server and untrusted storage server. The system utilizes biometric image cryptosystem, cryptographic hashing, and Paillier cryptosystem. In the proposed cryptosystem, keystreams are generated from Henon and logistic maps. The control parameters of these chaotic maps are calculated from the input biometric image. The proposed biometric encryption is able to resist statistical and differential attacks and its security level is also validated through various analyzes. Also, the attacks related to the privacy of ADT are analyzed.

Privacy-Preserving Distributed Data Access Control for CloudIoT

The Edge-Fog-Cloud interplay in the Internet-of-Things (IoT) leads to many exciting data-sharing applications that use access control systems as primary requirements. To ensure a fine-grained data access control for such data-sharings on untrusted storage (e.g., Cloud), Attribute-Based Encryption (ABE) is a promising tool. To address privacy concerns in such ABE-based access control systems, we propose a new Privacy-preserving Distributed data Access control (PDAC) in CloudIoT. Our PDAC improves the previous privacy-preserving distributed ABE systems in three aspects. The first introduces a new user's anonymity approach against the colluding untrusted (honest-but-curious) authorities. The second presents a novel policy-hiding mechanism that efficiently preserves the privacy of policy-forming attributes (metadata) against colluding parties. The third introduces an independent-authorities system for our privacy-preserving improvements, where an authority can join and leave the system without reinitializing other authorities. Moreover, our PDAC offloads the user's computations over the Cloud servers for efficiency enhancement. We prove the security of our PDAC through formal analysis. Then, we present empirical results on different classes of mobile devices, including a laptop and a smartphone.

Connecting the Dots: Privacy Leakage via Write-Access Patterns to the Main Memory

Data-dependent access patterns of an application to an untrusted storage system are notorious for leaking sensitive information about the user's data. Previous research has shown how an adversary capable of monitoring both read and write requests issued to the memory can correlate them with the application to learn its sensitive data. However, information leakage through only the write access patterns is less obvious and not well studied in the current literature. In this work, we demonstrate an actual attack on power-side-channel resistant Montgomery's ladder based modular exponentiation algorithm commonly used in public key cryptography. We infer the complete 512-bit secret exponent in ~ 3.5 minutes by virtue of just the write access patterns of the algorithm to the main memory. In order to learn the victim algorithm's write access patterns under realistic settings, we exploit a compromised DMA device to take frequent snapshots of the application's address space, and then run a simple differential analysis on these snapshots to find the write access sequence. The attack has been shown on an Intel Core(TM) i7-4790 3.60GHz processor based system. We further discuss a possible attack on McEliece public-key cryptosystem that also exploits the write-access patterns to learn the secret key.

SqORAM: Read-Optimized Sequential Write-Only Oblivious RAM

Abstract Oblivious RAMs (ORAMs) allow a client to access data from an untrusted storage device without revealing the access patterns. Typically, the ORAM adversary can observe both read and write accesses. Write-only ORAMs target a more practical, multi-snapshot adversary only monitoring client writes – typical for plausible deniability and censorship-resilient systems. This allows write-only ORAMs to achieve significantly-better asymptotic performance. However, these apparent gains do not materialize in real deployments primarily due to the random data placement strategies used to break correlations between logical and physical names-paces, a required property for write access privacy. Random access performs poorly on both rotational disks and SSDs (often increasing wear significantly, and interfering with wear-leveling mechanisms). In this work, we introduce SqORAM, a new locality-preserving write-only ORAM that preserves write access privacy without requiring random data access. Data blocks close to each other in the logical domain land in close proximity on the physical media. Importantly, SqORAM maintains this data locality property over time, significantly increasing read throughput. A full Linux kernel-level implementation of SqORAM is 100x faster than non locality-preserving solutions for standard workloads and is 60-100% faster than the state-of-the-art for typical file system workloads.

Secure Channel Free Certificate-Based Searchable Encryption Withstanding Outside and Inside Keyword Guessing Attacks

Searchable public key encryption (SPKE) is a useful public key cryptographic primitive that allows a user to perform keyword searches over publicly encrypted messages on an untrusted storage server while guaranteeing the privacy of the original messages as well as the search keywords. However, most of the previously proposed SPKE frameworks suffer from the security vulnerability caused by the keyword guessing attack and some other weaknesses. Inspired by the ideas of certificate-based cryptography and signcryption, we present a new SPKE framework called certificate-based searchable encryption. The new framework not only provides resistance to the existing known types of keyword guessing attacks, but also enjoys some appealing merits, such as implicit authentication, no key escrow and no secure channel. Under this new framework, we devise a concrete searchable certificate-based encryption scheme. In the random oracle model, it is proven to meet the keyword ciphertext indistinguishability, the keyword ciphertext unforgeability and the keyword trapdoor indistinguishability under the adaptive chosen-keyword attack. The comparisons indicate that it is secure and practicable.

ASDS: Attribute‐based secure data sharing scheme for reliable cloud environment

Cloud computing is a new revolution of information technology which provides many benefits to customers such as scalability, on‐demand, 24 × 7 × 365 support, and reduce cost usage of computing resources. But storing data on these untrusted cloud servers makes secure data sharing a big challenge issue. On one hand, enforce data access policies on these untrusted storage servers provider is an effective way to ensure data security. On the other hand, confidentiality of sensitive data should be protected against them. This paper presents an attribute‐based secure data sharing (ASDS) scheme for cloud environment, which provides data access control, data confidentiality, data authentication, and flexible user revocation. In addition, the proposed scheme is able to resist collusion attack and replay attack. The analysis of security properties and the comparison performance with other data sharing schemes have demonstrated that ASDS is very suitable for cloud environment.

Cycle ORAM: A Practical Protection for Access Pattern in Untrusted Storage

Oblivious RAM (ORAM) is a cryptographic primitive to hide memory access pattern in untrusted storage, but the cost remains prohibitively expensive. This paper proposes cycle ORAM, an improvement of Ring ORAM for small client setting. It gains the most efficient bandwidth and client storage simultaneously. In the eviction, Cycle ORAM is the first scheme which does not need to evict all buckets in the target path. Instead, it only evicts the root bucket. Moreover, to preserve the stash size, the root bucket is expected to provide the largest empty storage by cycling shifting buckets in the server. On the other hand, to meet the security requirement, the randomness of blocks is carried out in the process of bucket reshuffle. Comparing to Ring ORAM, the simulation shows that stash size is smaller and the amortized bandwidth is 1.5× better. In addition, the size of buffer required in ORAM refreshment is reduced from O(logN) to almost a constant, where N is the number of distinct data blocks in the server.

Cryptanalysis of the existing integrated PKE and PEKS schemes

Public key encryption with keyword search (PEKS) is a useful cryptographic primitive which allows one to delegate to an untrusted storage server the capability of searching on publicly encrypted data without impacting the security and privacy of original data. However, due to lack of data encryption/decryption function, a PEKS scheme cannot be used alone but has to be coupled with a standard public key encryption (PKE) scheme. For this reason, a new cryptographic primitive called integrated PKE and PEKS (PKE/PEKS) was introduced by Baek et al. in 2006, which provides the functions of both PKE and PEKS. So far, several PKE/PEKS schemes have been proposed in the literature. However, none of them considers the keyword guessing attack. The first PKE/PEKS scheme proposed by Baek et al. was shown to be insecure under this attack. In this paper, we analyse the security of other PKE/PEKS schemes. We demonstrate that none of these schemes can resist the keyword guessing attack. The presented attacks show that a malicious storage server can successfully guess the keyword encoded in any keyword trapdoor produced by these schemes. Therefore, it is still an unsolved problem to devise a PKE/PEKS scheme withstanding the keyword guessing attack.

Cryptanalysis of the existing integrated PKE and PEKS schemes

Public key encryption with keyword search (PEKS) is a useful cryptographic primitive which allows one to delegate to an untrusted storage server the capability of searching on publicly encrypted data without impacting the security and privacy of original data. However, due to lack of data encryption/decryption function, a PEKS scheme cannot be used alone but has to be coupled with a standard public key encryption (PKE) scheme. For this reason, a new cryptographic primitive called integrated PKE and PEKS (PKE/PEKS) was introduced by Baek et al. in 2006, which provides the functions of both PKE and PEKS. So far, several PKE/PEKS schemes have been proposed in the literature. However, none of them considers the keyword guessing attack. The first PKE/PEKS scheme proposed by Baek et al. was shown to be insecure under this attack. In this paper, we analyse the security of other PKE/PEKS schemes. We demonstrate that none of these schemes can resist the keyword guessing attack. The presented attacks show that a malicious storage server can successfully guess the keyword encoded in any keyword trapdoor produced by these schemes. Therefore, it is still an unsolved problem to devise a PKE/PEKS scheme withstanding the keyword guessing attack.

Efficient searchable public key encryption against keyword guessing attacks for cloud-based EMR systems

Due to the tremendous benefits of cloud computing, an increasing number of health care providers tend to deploy the electronic medical record (EMR) storages and application services into cloud. To protect patients’ privacy, sensitive EMRs have to be encrypted before being uploaded to cloud. This makes effective utilization of EMRs, such as plaintext keyword search, a very challenging problem. Public key encryption with keyword search (PEKS) provides a promising cryptographic solution to encrypted EMR data retrieval, because it allows one to delegate to an untrusted storage server the capability of searching on publicly encrypted EMR data without compromising the security of original EMR data. Recently, two secure channel free PEKS schemes were proposed for cloud-based EMR systems. However, our cryptanalysis demonstrates that both of these two schemes suffer from the security vulnerabilities caused by the keyword guessing attack. To deal with this problem, a novel secure channel free PEKS scheme is developed in this paper. The proposed scheme not only provides the resistance to the existing known three types of keyword guessing attacks, but also has the merit of no designated server. In the standard model, it is formally proven to achieve both the keyword ciphertext indistinguishability and the trapdoor indistinguishability under the adaptive chosen-keyword attacks. The comparisons indicate that the scheme is secure and practicable.

Two-factor authentication for trusted third party free dispersed storage

We propose a trusted third party free protocol for secure (in terms of content access, manipulation, and confidentiality) data storage and multi-user collaboration over an infrastructure of untrusted storage servers. It is achieved by the application of data dispersal, encryption as well as two-factor (knowledge and possession) based authentication and access control techniques so that unauthorized parties (attackers) or a small set of colluding servers cannot gain access to the stored data. The protocol design takes into account usability issues as opposed to the closest prior work Esiner and Datta (2016). We explore the security implications of the proposed model with event tree analysis and report on experiment results to demonstrate the practicality of the approach concerning computational overheads. Given that the protocol does not rely on any trusted third party, and most operations including actual collaboration do not require users to be online simultaneously, it is suitable not only for traditional multi-cloud setups but also for edge/fog computing environments.

DATS - Data Containers for Web Applications

Data containers enable users to control access to their data while untrusted applications compute on it. However, they require replicating an application inside each container - compromising functionality, programmability, and performance. We propose DATS - a system to run web applications that retains application usability and efficiency through a mix of hardware capability enhanced containers and the introduction of two new primitives modeled after the popular model-view-controller (MVC) pattern. (1) DATS introduces a templating language to create views that compose data across data containers. (2) DATS uses authenticated storage and confinement to enable an untrusted storage service, such as memcached and deduplication, to operate on plain-text data across containers. These two primitives act as robust declassifiers that allow DATS to enforce non-interference across containers, taking large applications out of the trusted computing base (TCB). We showcase eight different web applications including Gitlab and a Slack-like chat, significantly improve the worst-case overheads due to application replication, and demonstrate usable performance for common-case usage.

MetaSync: Coordinating Storage across Multiple File Synchronization Services

Cloud-based file synchronization services such as Dropbox are a worldwide resource for many millions of users. However, individual services often have tight resource limits, suffer from temporary outages or shutdowns, and sometimes silently corrupt or leak user data. As a solution, the authors design, implement, and evaluate MetaSync, a secure and reliable file synchronization service using multiple cloud synchronization services as untrusted storage providers. To provide global consistency among the storage providers, the authors devise a novel variant of Paxos that enables efficient updates on top of the unmodified APIs exported by each service. MetaSync provides better availability and performance, stronger confidentiality and integrity, and larger storage for end users.

Provable Data Possession at Untrusted Cloud Storage server

Provable Data Possession at Untrusted Cloud Storage server

Effective Data Utilization in Public Cloud through Hash Table Assorted Trie Indexed Encrypted Fuzzy Search

Cloud computing offers seamless service in the recent past to provide cloud infrastructure as a service that facilitates number of third party data owners across the world. Owing to various advantages like low infrastructure cost, high flexibility and ease of managing data, public cloud service has been widely adopted by several data owners. Cloud computing supports third party owners to optimize their cost spent towards cloud resources and infrastructure for their own data. While data owners are convinced with the security of individual data, the key is to make effective data utilization. This paper presents a novel approach hash table assorted trie encrypted fuzzy search method that creates wild card-based fuzzy keyword set to provide effective data utilization. It also creates hash table assorted trie fuzzy searchable index for fuzzy keyword set that resolves typos and representation inconsistencies and reduces searching time. The objective of the proposed searching method is to utilize the data effectively in terms of searching time, total number of files accessed from the untrusted cloud storage server.

A Hybrid Approach of AES and File Encryption to Enhance The Cloud Security

Cloud computing is a paradigm shift in the way we define software and hardware, and architect our IT solutions. The emerging cloud technologies, due to their various unique and attractive properties, are evolving with tremendous momentum and rapidly being adopted throughout the IT industry. In this dissertation, we identify security challenges that arise in integration of cloud-based services, and present a set of novel solutions to address them. We analyze the security of our solutions, demonstrate their usage and effectiveness, and evaluate their performance by extensive experimentation. To address the problem of security in untrusted cloud storage, we introduce a hybrid solution of AES and file encryption. The key used in AES algorithm is generated randomly from the file's data which is sent by the cloud provider. After implementing the proposed methodology, we have seen an improvement in the processing time and cost which will increase the overall efficiency of the system.Â

PrORAM

Oblivious RAM (ORAM) is an established technique to hide the access pattern to an untrusted storage system. With ORAM, a curious adversary cannot tell what address the user is accessing when observing the bits moving between the user and the storage system. All existing ORAM schemes achieve obliviousness by adding redundancy to the storage system, i.e., each access is turned into multiple random accesses. Such redundancy incurs a large performance overhead. Although traditional data prefetching techniques successfully hide memory latency in DRAM based systems, it turns out that they do not work well for ORAM because ORAM does not have enough memory bandwidth available for issuing prefetch requests. In this paper, we exploit ORAM locality by taking advantage of the ORAM internal structures. While it might seem apparent that obliviousness and locality are two contradictory concepts, we challenge this intuition by exploiting data locality in ORAM without sacrificing security. In particular, we propose a dynamic ORAM prefetching technique called PrORAM (Dynamic Prefetcher for ORAM) and comprehensively explore its design space. PrORAM detects data locality in programs at runtime, and exploits the locality without leaking any information on the access pattern. Our simulation results show that with PrORAM, the performance of ORAM can be significantly improved. PrORAM achieves an average performance gain of 20% over the baseline ORAM for memory intensive benchmarks among Splash2 and 5.5% for SPEC06 workloads. The performance gain for YCSB and TPCC in DBMS benchmarks is 23.6% and 5% respectively. On average, PrORAM offers twice the performance gain than that offered by a static super block scheme.

Freecursive ORAM

Oblivious RAM (ORAM) is a cryptographic primitive that hides memory access patterns as seen by untrusted storage. Recently, ORAM has been architected into secure processors. A big challenge for hardware ORAM schemes is how to efficiently manage the Position Map (PosMap), a central component in modern ORAM algorithms. Implemented naively, the PosMap causes ORAM to be fundamentally unscalable in terms of on-chip area. On the other hand, a technique called Recursive ORAM fixes the area problem yet significantly increases ORAM's performance overhead. To address this challenge, we propose three new mechanisms. We propose a new ORAM structure called the PosMap Lookaside Buffer (PLB) and PosMap compression techniques to reduce the performance overhead from Recursive ORAM empirically (the latter also improves the construction asymptotically). Through simulation, we show that these techniques reduce the memory bandwidth overhead needed to support recursion by 95%, reduce overall ORAM bandwidth by 37% and improve overall SPEC benchmark performance by 1.27x. We then show how our PosMap compression techniques further facilitate an extremely efficient integrity verification scheme for ORAM which we call PosMap MAC (PMMAC). For a practical parameterization, PMMAC reduces the amount of hashing needed for integrity checking by >= 68x relative to prior schemes and introduces only 7% performance overhead. We prototype our mechanisms in hardware and report area and clock frequency for a complete ORAM design post-synthesis and post-layout using an ASIC flow in a 32~nm commercial process. With 2 DRAM channels, the design post-layout runs at 1~GHz and has a total area of .47~mm2. Depending on PLB-specific parameters, the PLB accounts for 10% to 26% area. PMMAC costs 12% of total design area. Our work is the first to prototype Recursive ORAM or ORAM with any integrity scheme in hardware.