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Register a new userAccess Control Encryption: Enforcing Information Flow with Cryptography
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Added by
Helene Haagh
Publication date
2016
fields
Informatics Engineering
and research's language is
English
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We initiate the study of Access Control Encryption (ACE), a novel cryptographic primitive that allows fine-grained access control, by giving different rights to different users not only in terms of which messages they are allowed to receive, but also which messages they are allowed to send. Classical examples of security policies for information flow are the well known Bell-Lapadula [BL73] or Biba [Bib75] model: in a nutshell, the Bell-Lapadula model assigns roles to every user in the system (e.g., public, secret and top-secret). A users role specifies which messages the user is allowed to receive (i.e., the no read-up rule, meaning that users with public clearance should not be able to read messages marked as secret or top-secret) but also which messages the user is allowed to send (i.e., the no write-down rule, meaning that a user with top-secret clearance should not be able to write messages marked as secret or public). To the best of our knowledge, no existing cryptographic primitive allows for even this simple form of access control, since no existing cryptographic primitive enforces any restriction on what kind of messages one should be able to encrypt. Our contributions are: - Introducing and formally defining access control encryption (ACE); - A construction of ACE with complexity linear in the number of the roles based on classic number theoretic assumptions (DDH, Paillier); - A construction of ACE with complexity polylogarithmic in the number of roles based on recent results on cryptographic obfuscation;
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Data security is required when communications over untrusted networks takes place. Security tools such as cryptography and steganography are applied to achieve such objectives, but both have limitations and susceptible to attacks if they were used individually. To overcome these limitations, we proposed a powerful and secured system based on the integration of cryptography and steganography. The secret message is encrypted with blowfish cipher and visual cryptography. Finally, the encrypted data is embedded into two innocent cover images for future transmission. An extended analysis was made to prove the efficiency of the proposed model by measuring Mean-Square-Error (MSE), Peak-Signal-to-noise-Ratio (PSNR), and image histogram. The robustness was examined by launching statistical and 8-bit plane visual attacks. The proposed model provides a secure mean to transmit or store highly classified data that could be applied to the public security sector.
Security researchers have stated that the core concept behind current implementations of access control predates the Internet. These assertions are made to pinpoint that there is a foundational gap in this field, and one should consider revisiting the concepts from the ground up. Moreover, Insider threats, which are an increasing threat vector against organizations are also associated with the failure of access control. Access control models derived from access control matrix encompass three sets of entities, Subjects, Objects and Operations. Typically, objects are considered to be files and operations are regarded as Read, Write, and Execute. This implies an `open sesame approach when granting access to data, i.e. once access is granted, there is no restriction on command executions. Inspired by Functional Encryption, we propose applying access authorizations at a much finer granularity, but instead of an ad-hoc or computationally hard cryptographic approach, we postulate a foundational transformation to access control. From an abstract viewpoint, we suggest storing access authorizations as a three-dimensional tensor, which we call Access Control Tensor (ACT). In Function-based Access Control (FBAC), applications do not give blind folded execution right and can only invoke commands that have been authorized for data segments. In other words, one might be authorized to use a certain command on one object, while being forbidden to use exactly the same command on another object. The theoretical foundations of FBAC are presented along with Policy, Enforcement and Implementation (PEI) requirements of it. A critical analysis of the advantages of deploying FBAC, how it will result in developing a new generation of applications, and compatibility with existing models and systems is also included. Finally, a proof of concept implementation of FBAC is presented.
In a recent approach, we proposed to model an access control mechanism as a Markov Decision Process, thus claiming that in order to make an access control decision, one can use well-defined mechanisms from decision theory. We present in this paper an implementation of such mechanism, using the open-source solver GLPK, and we model the problem in the GMPL language. We illustrate our approach with a simple, yet expressive example, and we show how the variation of some parameters can change the final outcome. In particular, we show that in addition to returning a decision, we can also calculate the value of each decision.
Large commercial buildings are complex cyber-physical systems containing expensive and critical equipment that ensure the safety and comfort of their numerous occupants. Yet occupant and visitor access to spaces and equipment within these buildings are still managed through unsystematic, inefficient, and human-intensive processes. As a standard practice, long-term building occupants are given access privileges to rooms and equipment based on their organizational roles, while visitors have to be escorted by their hosts. This approach is conservative and inflexible. In this paper, we describe a methodology that can flexibly and securely manage building access privileges for long-term occupants and short-term visitors alike, taking into account the risk associated with accessing each space within the building. Our methodology relies on blockchain smart contracts to describe, grant, audit, and revoke fine-grained permissions for building occupants and visitors, in a decentralized fashion. The smart contracts are specified through a process that leverages the information compiled from Brick and BOT models of the building. We illustrate the proposed method through a typical application scenario in the context of a real office building and argue that it can greatly reduce the administration overhead, while, at the same time, providing fine-grained, auditable access control.
Control-flow hijacking attacks are used to perform malicious com-putations. Current solutions for assessing the attack surface afteracontrol flow integrity(CFI) policy was applied can measure onlyindirect transfer averages in the best case without providing anyinsights w.r.t. the absolute calltarget reduction per callsite, and gad-get availability. Further, tool comparison is underdeveloped or notpossible at all. CFI has proven to be one of the most promising pro-tections against control flow hijacking attacks, thus many effortshave been made to improve CFI in various ways. However, there isa lack of systematic assessment of existing CFI protections. In this paper, we presentLLVM-CFI, a static source code analy-sis framework for analyzing state-of-the-art static CFI protectionsbased on the Clang/LLVM compiler framework.LLVM-CFIworksby precisely modeling a CFI policy and then evaluating it within aunified approach.LLVM-CFIhelps determine the level of securityoffered by different CFI protections, after the CFI protections weredeployed, thus providing an important step towards exploit cre-ation/prevention and stronger defenses. We have usedLLVM-CFIto assess eight state-of-the-art static CFI defenses on real-worldprograms such as Google Chrome and Apache Httpd.LLVM-CFIprovides a precise analysis of the residual attack surfaces, andaccordingly ranks CFI policies against each other.LLVM-CFIalsosuccessfully paves the way towards construction of COOP-like codereuse attacks and elimination of the remaining attack surface bydisclosing protected calltargets under eight restrictive CFI policies.
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