Cloud computing bring a tremendous complexity to information security. Remote attestation can be used to establish trust relationship in cloud. TBVMM is designed to extend the existing chain of trust into the software layers to support dynamic remote attestation for cloud computing. TBVMM uses Bayesian network and Kalman filter to solve the dynamicity of the trusted relationship. It is proposed to fill the trust gap between the infrastructure and upper software stacks.

Cryptographic cloud storage (CCS) is a secure architecture built in the upper layer of a public cloud infrastructure. In the CCS system, a user can define and manage the access control of the data by himself without the help of cloud storage service provider. The ciphertext-policy attribute-based encryption (CP-ABE) is considered as the critical technology to implement such access control. However, there still exists a large security obstacle to the implementation of CP-ABE in CCS. That is, how to identify the malicious cloud user who illegally shares his private keys with others or applies his keys to construct a decryption device/black-box, and provides the decryption service. Although several CP-ABE schemes with black-box traceability have been proposed to address the problem, most of them are not practical in CCS systems, due to the absence of scalability and expensive computation cost, especially the cost of tracing. Thus, we present a new black-box traceable CP-ABE scheme that is scalable and high efficient. To achieve a much better performance, our work is designed on the prime order bilinear groups that results in a great improvement in the efficiency of group operations, and the cost of tracing is reduced greatly to $O\left(N\right)$ or $O\left(1\right)$ , where N is the number of users of a system. Furthermore, our scheme is proved secure in a selective standard model. To the best of our knowledge, this work is the first such practical and provably secure CP-ABE scheme for CCS, which is black-box traceable.

While cloud customers can benefit from migrating applications to the cloud, they are concerned about the security of the hosted applications. This is complicated by the customers not knowing whether their cloud applications are working as expected. Although memory-safety Java Virtual Machine (JVM) can alleviate their anxiety due to the control flow integrity, their applications are prone to a violation of bytecode integrity. The analysis of some Java exploits indicates that the violation results primarily from the given excess sandbox permission, loading flaws in Java class libraries and third-party middlewares and the abuse of sun.misc.UnsafeAPI. To such an end, we design an architecture, called RIM4J, to enforce a runtime integrity measurement of Java bytecode within a cloud system, with the ability to attest this to a cloud customer in an unforgeable manner. Our RIM4J architecture is portable, such that it can be quickly deployed and adopted for real-world purposes, without requiring modifications to the underlying systems and access to application source code. Moreover, our RIM4J architecture is the first to measure dynamically-generated bytecode. We apply our runtime measurement architecture to a messaging server application where we show how RIM4J can detect undesirable behaviors, such as uploading arbitrary files and remote code execution. This paper also reports the experimental evaluation of a RIM4J prototype using both a macro- and a micro-benchmark; the experimental results indicate that RIM4J is a practical solution for real-world applications.

Cloud computing emerges as a change in the business paradigm that offers pay-as-you-go computing capability and brings enormous benefits, but there are numerous organizations showing hesitation for the adoption of cloud computing due to security concerns. Remote attestation has been proven to boost confidence in clouds to guarantee hosted cloud applications’ integrity. However, the state-of-the-art attestation schemes do not fit that multiple requesters raise their challenges simultaneously, thereby leading to larger performance overheads on the attester side. To address that, we propose an efficient and trustworthy concurrent attestation architecture under multi-requester scenarios, Astrape, to improve efficiency in the integrity and confidentiality protection aspects to generate an unforgeable and encrypted attestation report. Specifically, we propose two key techniques in this paper. The first one—aggregated attestation signature—reliably protects the attestation content from being compromised even in the presence of adversaries who have full control of the network, therefore successfully providing attestation integrity. The second one—delegation-based controlled report—introduces a third-party service to distribute the attestation report to requesters in order to save computation and communication overload on the attested party. The report is encrypted with an access policy by using attribute-based encryption and accessed by a limited number of qualified requesters, hence supporting attestation confidentiality. The experimental results show that Astrape can take no more than $0.4$ s to generate an unforgeable and encrypted report for 1000 requesters and deliver a throughput speedup of approximately $30\times$ in comparison to the existing attestation systems.

In application scenarios such as cloud storage, a symmetric algorithm can be used to encrypt massive data. However, using the symmetric operation and keys in encryption and decryption, it is very difficult to realize an efficient access control system. The asymmetric encryption algorithm ciphertext-policy attribute-based encryption (CP-ABE), as a versatile one-to-many encryption algorithm, is considered an ideal access control tool to solve the user’s distrust of the service provider of cloud storage. However, in a traditional CP-ABE system, the malicious users may deliberately leak their attribute keys to others or build a decryption black box (DB) to provide illegal decryption services for benefits, while no one can determine their identities. To deal with the problems, especially the problem of tracing the DB builder, CP-ABE schemes with black-box traceability have been proposed in the past few years. But in this paper, we point out that for now, the tracing algorithms in all existing schemes actually work on an impractical assumption. That is, whenever a DB receives a decryption request, it always performs the decryption algorithm honestlycorrectly. We argue that if a DB finds the decryption request comes from the tracing algorithm, it may intentionally output incorrect decryption results to counter the tracing. Thus, we present the structural defect of the tracing algorithm applied to all known traceable CP-ABE schemes. We describe the construction of an alert decryption black box (ADB) that is capable of distinguishing a tracing ciphertext from a normal one. We also show how an ADB frustrates the tracing algorithm, and furthermore, malicious users can even apply an ADB to frame innocent users.

Many scholars have attempted to use an encryption method to resolve the problem of data leakage in data outsourcing storage. However, encryption methods reduce data availability and are inefficient. Vertical fragmentation perfectly solves this problem. It was first used to improve the access performance of the relational database, and nowadays some researchers employ it for privacy protection. However, there are some problems that remain to be solved with the vertical fragmentation method for privacy protection in the relational database. First, current vertical fragmentation methods for privacy protection require the user to manually define privacy constraints, which is difficult to achieve in practice. Second, there are many vertical fragmentation solutions that can meet privacy constraints; however, there are currently no quantitative evaluation criteria evaluating how effectively solutions can protect privacy more effectively. In this article, we introduce the concept of information entropy to quantify privacy in vertical fragmentation, so we can automatically discover privacy constraints. Based on this, we propose a privacy protection model with a minimum entropy fragmentation algorithm to achieve minimal privacy disclosure of vertical fragmentation. Experimental results show that our method is suitable for privacy protection with a lower overhead.