Fine-grained Protection Research Articles

Memory Protection Keys: Facts, Key Extension Perspectives, and Discussions

Memory Protection Keys (MPK) offers per-thread memory protection with an affordable overhead, prompting many new studies. With protection key extension, MPK provides more fine-grained protection and better functionality. MPK can be an attractive option for memory protection in industry.

Hyperledger for IoT: A Review of Reconstruction Diagrams Perspective

The convergence of blockchain with the internet of things (IoT) attracted widespread attention. Blockchain mainly solved the problem of secure storage and trusted transactions. The convergence of these two emerging technologies enhanced the security of smart services. However, there were some technical barriers to the deployment of practical IoT systems. In order to further promote the popularity and application of blockchain in the IoT, Hyperledger became the ideal technology to overcome these obstacles. In recent years, the mainstream application fields of IoT tried to carry out integration with Hyperledger to achieve high security, fine-grained privacy protection, real-time data flow, robustness, and other business requirements. However, there was a lack of literature review on this topic. This study obtained the latest related literature of Hyperledger in IoT from Web of Science, Wordlib, and EBSCO databases. To demonstrate more intuitive differences and provide a technology convergence process, this study proposes a reconstruction diagram analysis method. Reconstruction is the process of fusing the core design and the original architecture diagram in the literature and reconstructing the diagram so that it can show the core ideas of the literature. This approach aims to visualize the core ideas of the literature. Finally, this paper prospected and concluded by proposing four directions for future work, including a low-energy consensus algorithm, intelligent transaction validation, mixed on-chain and off-chain storage, and customized incentives.

STEB: A secure service trading ecosystem based on blockchain.

A service can be an intangible commodity in which no physical goods are transferred from the seller to the buyer. However, traditional trading platforms have many limitations in trading services due to dishonest buyers and brokers. In this paper, we propose a service trading ecosystem based on blockchain, named STEB, which combines blockchain, smart contract, encryption, and digital authentication techniques for service trading. In addition, a dual-chain architecture, which contains two types of blockchains, namely TraChain and SerChain, and a hierarchical encryption scheme of the data on the chain, are proposed to ensure the integrity of transaction data and fine-grained privacy protection of users. Furthermore, we describe a new set of smart contracts to ensure safe transactions for the entire service trading. Security analysis and simulation results confirm that the proposed STEB can achieve more efficient contract execution and enhance service transaction privacy.

A model-based approach for multi-level privacy policies derivation for cloud services

To benefit from the advantages offered by the cloud services, a data owner must move his private data to external servers to be accessed and handled by unknown parties. This brings about several concerns such as lack of user control, data leakage, improper access and use, unauthorised data storage location and retention, etc. Although extensive research efforts have been carried out to address data privacy issues in the cloud, this still requires many more efforts. Particularly, the privacy policy specification which presents the first step to ensure fine-grained data protection in such an untrusted environment. In this paper, we introduce a model-based approach that couples access, usage and storage policies specification in the context of cloud services. The approach stands on a high-level abstract model and a low-level concrete model to design the policies. Models refinement from top to bottom and automatic derivation of the final policies are introduced. The approach is demonstrated and evaluated through a case study.

Distributed Security Framework for Reliable Threat Intelligence Sharing

Computer security incident response teams typically rely on threat intelligence platforms for information about sightings of cyber threat events and indicators of compromise. Other security building blocks, such as Network Intrusion Detection Systems, can leverage the information to prevent malicious adversaries from spreading malware across critical infrastructures. The effectiveness of threat intelligence platforms heavily depends on the willingness to share among organizations and the responsible use of sensitive information that may potentially harm the reputation of the reporting organization. The challenge that we address is the lack of trust in the source providing the threat intelligence and the information itself. We enhance our security framework TATIS—offering fine-grained protection for threat intelligence platform APIs—with distributed ledger capabilities to enable reliable and trustworthy threat intelligence sharing with the ability to audit the provenance of threat intelligence. We have implemented and evaluated the feasibility of our distributed framework on top of the Malware Information Sharing Platform (MISP) solution, and we evaluate the performance impact using real-world open-source threat intelligence feeds.

A PUF-based unified identity verification framework for secure IoT hardware via device authentication

In the era of Internet-of-Things (IoTs), millions of smart devices are interconnected and communicated through networks. To guarantee the security and reliability of data transmission in IoT, the underlying hardware of these devices must first be secure and trusted. However, due to the inherent mobility nature of current embedded devices, IoT hardware could be vulnerable to diverse security threats from multiple malicious participants. Among them, device theft is becoming one of the most challenging security issues that have incurred a serious impact on copyright. To effectively alleviate this threat, silicon physical unclonable function (PUF) has been presented and considered to be a reliable anti-piracy solution to complete the device authentication and key storage. However, current PUF solutions are mostly focused on chip-level verification and cannot provide systematic identification and authentication. To this end, this article proposes a unified identity verification framework which can provide fine-grained protection for embedded devices against theft attacks from the system level. This framework is established on a series of PUF circuits that have been implanted into each individual chip of the devices. We first improve the configurable ring oscillator (CRO) PUFs with the latch structure. Therefore, a unique sub-digital signature of each chip can be generated by performing the challenge-response strategy. We then reassemble all the sub-digital signatures and encode them to acquire the unique fingerprint of each embedded device, so as to achieve system-level device identification and authentication. Any substitution of an individual or all chips in the devices will result in the inconsistencies of the system-level fingerprint. We implement and verify the proposed scheme on the field programmable gate array (FPGA) platforms. Experimental results illustrate that the proposed framework can uniquely and accurately identify any or all of the thefts to the embedded system hardware at low silicon overhead.

A New Group Location Privacy-Preserving Method Based on Distributed Architecture in LBS

Nowadays, the location privacy problem has become an important problem for the users who enjoy the location-based services (LBSs). Researchers have focused on the problem of how to protect the location privacy of user efficiently for a long time. On one hand, many achievements adopt the centralized structure in which there is an additional center server. Additionally, some other researchers adopt the distributed structure to overcome the disadvantages brought by the center server in the centralized anonymous system structure. On the other hand, the existing methods of solving the problem are always to protect the individual user’s location privacy in LBSs, without considering the user group’s location privacy. This kind of methods is not very applicable to the status of a number of users who formed a group to complete a LBS task together by collaborative computing. In order to solve the problem of location privacy protection for a user group in the untrusted mobile social networks, a location privacy protection method based on the distributed structure is discussed in this paper. In the scheme, the special homomorphic features of BGN cryptosystem are cleverly used so that it can solve the group’s three classical location service applications simultaneously, namely, group nearest neighbor query, optimal group collection point determination, and group friend’s distance query, by only one security policy. If there are k users who formed the group, it could achieve k-anonymity without exposing the coordinate of each individual user or using any anonymous areas. Furthermore, theoretical and experimental analysis proves that the proposal can efficiently protect each user’s location privacy in the group through taking full advantage of the collaborative computing and communication capabilities of the mobile terminals. It can resist the existing distance interaction attack and collusion attack and can realize the secure and efficient fine-grained controllable location privacy protection for the user group.

IRODS metadata management for a cancer genome analysis workflow

BackgroundThe massive amounts of data from next generation sequencing (NGS) methods pose various challenges with respect to data security, storage and metadata management. While there is a broad range of data analysis pipelines, these challenges remain largely unaddressed to date.ResultsWe describe the integration of the open-source metadata management system iRODS (Integrated Rule-Oriented Data System) with a cancer genome analysis pipeline in a high performance computing environment. The system allows for customized metadata attributes as well as fine-grained protection rules and is augmented by a user-friendly front-end for metadata input. This results in a robust, efficient end-to-end workflow under consideration of data security, central storage and unified metadata information.ConclusionsIntegrating iRODS with an NGS data analysis pipeline is a suitable method for addressing the challenges of data security, storage and metadata management in NGS environments.

VMGuards: A Novel Virtual Machine Based Code Protection System with VM Security as the First Class Design Concern

Process-level virtual machine (PVM) based code obfuscation is a viable means for protecting software against runtime code tampering and unauthorized code reverse engineering. PVM-based approaches rely on a VM to determine how instructions of the protected code region are scheduled and executed. Therefore, it is crucial to protect the VM against runtime code tampering that alters the instructions and behavior of the VM. This paper presents VMGuards, a novel PVM-based code protection system that puts the security of VM as the first class design concern. Our approach advances prior work by promoting security of the VM as the first class design constraint. We achieve this by introducing two new instruction sets to protect the internal implementations of critical code segments and the host runtime environment where the VM runs in. Our new instruction sets not only have an identical code structure as standard virtual instructions, but also provide additional information to allow the VM to check whether the critical internal implementation or the runtime environment is affected. We evaluate our approach by using a set of real-life applications. Experimental results show that our approach provides stronger and more fine-grained protection when compared to the state-of-the-art with little extra overhead.

Prioritized access control enabling weighted, fine-grained protection in cyber-physical systems

This article investigates access control in cyber-physical systems, making a decision to permit or deny a user’s request for access operations on a system. Access operations in cyber-physical syste...

SARRE: Semantics-Aware Rule Recommendation and Enforcement for Event Paths on Android

This paper presents a semantics-aware rule recommendation and enforcement (SARRE) system for taming information leakage on Android. SARRE leverages statistical analysis and a novel application of minimum path cover algorithm to identify system event paths from dynamic runtime monitoring. Then, an online recommendation system is developed to automatically assign a fine-grained security rule to each event path, capitalizing on both known security rules and application semantic information. The proposed SARRE system is prototyped on Android devices and evaluated using real-world malware samples and popular apps from Google Play spanning multiple categories. Our results show that SARRE achieves 93.8% precision and 96.4% recall in identifying the event paths, compared with tainting technique. Also, the average difference between rule recommendation and manual configuration is less than 5%, validating the effectiveness of the automatic rule recommendation. It is also demonstrated that by enforcing the recommended security rules through a camouflage engine, SARRE can effectively prevent information leakage and enable fine-grained protection over private data with very small performance overhead.

A non-intrusive runtime enforcement on behaviors of open supervisory control and data acquisition systems

With the development of Web-based services and related technologies, today’s supervisory control and data acquisition is regarded as an Internet of things service system for industrial infrastructures and ensuring open supervisory control and data acquisition systems in a secure and safe state at runtime becomes a critical and mandatory requirement. Existing host-based monitoring automata are vulnerable because “inside” malware may compromise and subvert the monitoring mechanism itself, and the virtual machine–based monitoring cannot provide observable running traces of the protected services because of the isolation between these services and the runtime monitor. In this article, we propose a non-intrusive solution to guarantee runtime state of open supervisory control and data acquisition systems. In this solution, the running traces of protected services are obtained in an “out-of-box” framework, which is built on abstract execution of network events on Internet of things service models and virtual machine semantic reconstruction of the protected services. In addition, a property checking procedure is employed to check the states of physical devices in advance to guarantee the runtime behavior in compliance with the security policies of open supervisory control and data acquisition systems. In such a way, the solution provides a fine-grained protection for open supervisory control and data acquisition systems and physical devices running in safety.

DriverGuard

Most commodity peripheral devices and their drivers are geared to achieve high performance with security functions being opted out. The absence of strong security measures invites attacks on the I/O data and consequently posts threats to those services feeding on them, such as fingerprint-based biometric authentication. In this article, we present a generic solution called DriverGuard, which dynamically protects the secrecy of I/O flows such that the I/O data are not exposed to the malicious kernel. Our design leverages a composite of cryptographic and virtualization techniques to achieve fine-grained protection without using any extra devices and modifications on user applications. We implement the DriverGuard prototype on Xen by adding around 1.7K SLOC. DriverGuard is lightweight as it only needs to protect around 2% of the driver code’s execution. We measure the performance and evaluate the security of DriverGuard with three input devices (keyboard, fingerprint reader and camera) and three output devices (printer, graphic card, and sound card). The experiment results show that DriverGuard induces negligible overhead to the applications.

Twitsper: Tweeting privately

Although today's online social networks provide some privacy controls to protect a user's shared content from other users, these controls aren't sufficiently expressive to provide fine-grained protection. Twitsper offers fine-grained control over who sees a Twitter user's messages, enabling private group communication while preserving Twitter's commercial interests.

Efficient and flexible anonymization of transaction data

Transaction data are increasingly used in applications, such as marketing research and biomedical studies. Publishing these data, however, may risk privacy breaches, as they often contain personal information about individuals. Approaches to anonymizing transaction data have been proposed recently, but they may produce excessively distorted and inadequately protected solutions. This is because these approaches do not consider privacy requirements that are common in real-world applications in a realistic and flexible manner, and attempt to safeguard the data only against either identity disclosure or sensitive information inference. In this paper, we propose a new approach that overcomes these limitations. We introduce a rule-based privacy model that allows data publishers to express fine-grained protection requirements for both identity and sensitive information disclosure. Based on this model, we also develop two anonymization algorithms. Our first algorithm works in a top-down fashion, employing an efficient strategy to recursively generalize data with low information loss. Our second algorithm uses sampling and a combination of top-down and bottom-up generalization heuristics, which greatly improves scalability while maintaining low information loss. Extensive experiments show that our algorithms significantly outperform the state-of-the-art in terms of retaining data utility, while achieving good protection and scalability.

CuPIDS: An exploration of highly focused, co-processor-based information system protection

The Co-Processing Intrusion Detection System (CuPIDS) project explores improving information system security through dedicating computational resources to system security tasks in a shared resource, multi-processor (MP) architecture. Our research explores ways in which this architecture offers improvements over the traditional uni-processor (UP) model of security. One approach we examined has a protected application running on one processor in a symmetric multi-processing (SMP) system while a shadow process specific to that application runs on a different processor. The shadow process monitors the application process' activity, ready to respond immediately if the application violates policy. Experiments with a prototype CuPIDS system demonstrate the feasibility of this approach in the context of a self-protecting and self-healing system. An untuned prototype supporting fine-grained protection of the real-world application WU-FTP resulted in less than a 15% slowdown while demonstrating CuPIDS' ability to quickly detect illegitimate behavior, raise an alarm, automatically repair the damage done by the fault or attack, allow the application to resume execution, and export a signature for the activity leading up to the error.

The Perm architecture approach: Supporting embedded system development

Abstract Despite of innovations in computer science software technology as high level languages, object-oriented programming, memory management units and operating systems with some security functions, software is still afflicted with the fault of a certain unreliability. Coarse-grained segment or page protection mechanism in hardware works with fix-sized memory blocks. A sufficient technique for a fine-grained protection mechanism down to a byte size resolution is still missing. This work has led to the new PERM (Protection Enhanced RISC Machine) processor architecture introducing a new approach to this problem. The load-store architecture of a RISC machine leads to a consistent realization of an enhanced address pointer procedure. This is combined with the ability to use much more information about the data objects and implements an effective data protection of all data in the processor's address range. This paper shows the effectiveness of the processor enhancement and gives some hints for its use inside embedded system development.

Mondrian memory protection

Mondrian memory protection (MMP) is a fine-grained protection scheme that allows multiple protection domains to flexibly share memory and export protected services. In contrast to earlier page-based systems, MMP allows arbitrary permissions control at the granularity of individual words. We use a compressed permissions table to reduce space overheads and employ two levels of permissions caching to reduce run-time overheads. The protection tables in our implementation add less than 9% overhead to the memory space used by the application. Accessing the protection tables adds than 8% additional memory references to the accesses made by the application. Although it can be layered on top of demand-paged virtual memory, MMP is also well-suited to embedded systems with a single physical address space. We extend MMP to support segment translation which allows a memory segment to appear at another location in the address space. We use this translation to implement zero-copy networking underneath the standard read system call interface, where packet payload fragments are connected together by the translation system to avoid data copying. This saves 52% of the memory references used by a traditional copying network stack.

Mondrian memory protection

Mondrian memory protection (MMP) is a fine-grained protection scheme that allows multiple protection domains to flexibly share memory and export protected services. In contrast to earlier page-based systems, MMP allows arbitrary permissions control at the granularity of individual words. We use a compressed permissions table to reduce space overheads and employ two levels of permissions caching to reduce run-time overheads. The protection tables in our implementation add less than 9% overhead to the memory space used by the application. Accessing the protection tables adds than 8% additional memory references to the accesses made by the application. Although it can be layered on top of demand-paged virtual memory, MMP is also well-suited to embedded systems with a single physical address space. We extend MMP to support segment translation which allows a memory segment to appear at another location in the address space. We use this translation to implement zero-copy networking underneath the standard read system call interface, where packet payload fragments are connected together by the translation system to avoid data copying. This saves 52% of the memory references used by a traditional copying network stack.

Mondrian memory protection

Mondrian memory protection (MMP) is a fine-grained protection scheme that allows multiple protection domains to flexibly share memory and export protected services. In contrast to earlier page-based systems, MMP allows arbitrary permissions control at the granularity of individual words. We use a compressed permissions table to reduce space overheads and employ two levels of permissions caching to reduce run-time overheads. The protection tables in our implementation add less than 9% overhead to the memory space used by the application. Accessing the protection tables adds than 8% additional memory references to the accesses made by the application. Although it can be layered on top of demand-paged virtual memory, MMP is also well-suited to embedded systems with a single physical address space. We extend MMP to support segment translation which allows a memory segment to appear at another location in the address space. We use this translation to implement zero-copy networking underneath the standard read system call interface, where packet payload fragments are connected together by the translation system to avoid data copying. This saves 52% of the memory references used by a traditional copying network stack.