Biblio
In this paper, we propose principles of information control and sharing that support ORCON (ORiginator COntrolled access control) models while simultaneously improving components of confidentiality, availability, and integrity needed to inherently support, when needed, responsibility to share policies, rapid information dissemination, data provenance, and data redaction. This new paradigm of providing unfettered and unimpeded access to information by authorized users, while at the same time, making access by unauthorized users impossible, contrasts with historical approaches to information sharing that have focused on need to know rather than need to (or responsibility to) share.
Constraints such as separation-of-duty are widely used to specify requirements that supplement basic authorization policies. However, the existence of constraints (and authorization policies) may mean that a user is unable to fulfill her/his organizational duties because access to resources is denied. In short, there is a tension between the need to protect resources (using policies and constraints) and the availability of resources. Recent work on workflow satisfiability and resiliency in access control asks whether this tension compromises the ability of an organization to achieve its objectives. In this paper, we develop a new method of specifying constraints which subsumes much related work and allows a wider range of constraints to be specified. The use of such constraints leads naturally to a range of questions related to "policy existence", where a positive answer means that an organization's objectives can be realized. We provide an overview of our results establishing that some policy existence questions, notably for those instances that are restricted to user-independent constraints, are fixed-parameter tractable.
The Internet of Things (IoT) is the latest Internet evolution that interconnects billions of devices, such as cameras, sensors, RFIDs, smart phones, wearable devices, ODBII dongles, etc. Federations of such IoT devices (or things) provides the information needed to solve many important problems that have been too difficult to harness before. Despite these great benefits, privacy in IoT remains a great concern, in particular when the number of things increases. This presses the need for the development of highly scalable and computationally efficient mechanisms to prevent unauthorised access and disclosure of sensitive information generated by things. In this paper, we address this need by proposing a lightweight, yet highly scalable, data obfuscation technique. For this purpose, a digital watermarking technique is used to control perturbation of sensitive data that enables legitimate users to de-obfuscate perturbed data. To enhance the scalability of our solution, we also introduce a contextualisation service that achieve real-time aggregation and filtering of IoT data for large number of designated users. We, then, assess the effectiveness of the proposed technique by considering a health-care scenario that involves data streamed from various wearable and stationary sensors capturing health data, such as heart-rate and blood pressure. An analysis of the experimental results that illustrate the unconstrained scalability of our technique concludes the paper.
It is increasingly common to outsource data storage to untrusted, third party (e.g. cloud) servers. However, in such settings, low-level online reference monitors may not be appropriate for enforcing read access, and thus cryptographic enforcement schemes (CESs) may be required. Much of the research on cryptographic access control has focused on the use of specific primitives and, primarily, on how to generate appropriate keys and fails to model the access control system as a whole. Recent work in the context of role-based access control has shown a gap between theoretical policy specification and computationally secure implementations of access control policies, potentially leading to insecure implementations. Without a formal model, it is hard to (i) reason about the correctness and security of a CES, and (ii) show that the security properties of a particular cryptographic primitive are sufficient to guarantee security of the CES as a whole. In this paper, we provide a rigorous definitional framework for a CES that enforces read-only information flow policies (which encompass many practical forms of access control, including role-based policies). This framework (i) provides a tool by which instantiations of CESs can be proven correct and secure, (ii) is independent of any particular cryptographic primitives used to instantiate a CES, and (iii) helps to identify the limitations of current primitives (e.g. key assignment schemes) as components of a CES.
Analytics in big data is maturing and moving towards mass adoption. The emergence of analytics increases the need for innovative tools and methodologies to protect data against privacy violation. Many data anonymization methods were proposed to provide some degree of privacy protection by applying data suppression and other distortion techniques. However, currently available methods suffer from poor scalability, performance and lack of framework standardization. Current anonymization methods are unable to cope with the massive size of data processing. Some of these methods were especially proposed for MapReduce framework to operate in Big Data. However, they still operate in conventional data management approaches. Therefore, there were no remarkable gains in the performance. We introduce a framework that can operate in MapReduce environment to benefit from its advantages, as well as from those in Hadoop ecosystems. Our framework provides a granular user's access that can be tuned to different authorization levels. The proposed solution provides a fine-grained alteration based on the user's authorization level to access MapReduce domain for analytics. Using well-developed role-based access control approaches, this framework is capable of assigning roles to users and map them to relevant data attributes.
Recently, Ransomware has been rapidly increasing and is becoming far more dangerous than other common malware types. Unlike previous versions of Ransomware that infect email attachments or access certain sites, the new Ransomware, such as WannaCryptor, corrupts data even when the PC is connected to the Internet. Therefore, many studies are being conducted to detect and defend Ransomware. However, existing studies on Ransomware detection cannot effectively detect and defend the new Ransomware because it detects Ransomware using signature databases or monitoring specific activities of processes. In this paper, we propose a method to make decoy files for detecting Ransomwares efficiently. The proposed method is based on the analysis of the behaviors of existing Ransomwares at the source code level.
NoSQL databases have gained a lot of popularity over the last few years. They are now used in many new system implementations that work with vast amounts of data. This data will typically also include sensitive information that needs to be secured. NoSQL databases are also underlying a number of cloud implementations which are increasingly being used to store sensitive information by various organisations. This has made NoSQL databases a new target for hackers and other state sponsored actors. Forensic examinations of compromised systems will need to be conducted to determine what exactly transpired and who was responsible. This paper examines specifically if NoSQL databases have security features that leave relevant traces so that accurate forensic attribution can be conducted. The seeming lack of default security measures such as access control and logging has prompted this examination. A survey into the top ranked NoSQL databases was conducted to establish what authentication and authorisation features are available. Additionally the provided logging mechanisms were also examined since access control without any auditing would not aid forensic attribution tremendously. Some of the surveyed NoSQL databases do not provide adequate access control mechanisms and logging features that leave relevant traces to allow forensic attribution to be done using those. The other surveyed NoSQL databases did provide adequate mechanisms and logging traces for forensic attribution, but they are not enabled or configured by default. This means that in many cases they might not be available, leading to insufficient information to perform accurate forensic attribution even on those databases.
Generative policies enable devices to generate their own policies that are validated, consistent and conflict free. This autonomy is required for security policy generation to deal with the large number of smart devices per person that will soon become reality. In this paper, we discuss the research issues that have to be addressed in order for devices involved in security enforcement to automatically generate their security policies - enabling policy-based autonomous security management. We discuss the challenges involved in the task of automatic security policy generation, and outline some approaches based om machine learning that may potentially provide a solution to the same.
With the development of the information and communications technology, new network architecture and applications keep emerging promoted by cloud computing, big data, virtualization technology, etc. As a novel network architecture, Software Defined Network (SDN) realizes separation of the control plane and the data plane, thus controlling hardware by a software platform which is known as the central controller. Through that method SDN realizes the flexible deployment of network resources. In the process of the development and application of SDN, its open architecture has exposed more and more security problem, which triggers a critical focus on how to build a secure SDN. Based on the hierarchical SDN architecture and characteristics, this paper analyzes the security threats that SDN may face in the application layer, the control layer, the resource layer and the interface layer. In order to solve those security threats, the paper presents an SDN security architecture which can provide corresponding defense ability. The paper also puts forward an enhanced access control strategy adopting an attribute-based encryption method in the SDN security architecture.
In the Content-Centric Networking (CCN) architecture, content confidentiality is treated as an application-layer concern. Data is only encrypted if the producer and consumer agree on a suitable access control policy and enforcement mechanism. In contrast, transport encryption in TCP/IP applications is increasingly opportunistic for better privacy. This type of encryption is woefully lacking in CCN. To that end, we present TRAPS, a protocol to enable transparent packet security and opportunistic encryption for all CCN data. TRAPS builds on the assumption that knowledge of a name gives one access to the corresponding content; otherwise, by design, the content remains encrypted and secure. TRAPS builds on recent advances in memory hard functions and message-locked encryption to protect data in transit. We show that the security of TRAPS is dependent on the distribution of content names and argue that it can be significantly improved if secure sessions are used to transmit small pieces of information from producers to consumers. Our performance assessment indicates TRAPS is capable of providing opportunistic encryption to CCN without significant throughput loss for reasonable packet throughput measurements.
Often considered as the brain of an industrial process, Industrial control systems are presented as the vital part of today's critical infrastructure due to their crucial role in process control and monitoring. Any failure or error in the system will have a considerable damage. Their openness to the internet world raises the risk related to cyber-attacks. Therefore, it's necessary to consider cyber security challenges while designing an ICS in order to provide security services such as authentication, integrity, access control and secure communication channels. To implement such services, it's necessary to provide an efficient key management system (KMS) as an infrastructure for all cryptographic operations, while preserving the functional characteristics of ICS. In this paper we will analyze existing KMS and their suitability for ICS, then we propose a new KMS based on Identity Based Cryptography (IBC) as a better alternative to traditional KMS. In our proposal, we consider solving two security problems in IBC which brings it up to be more suitable for ICS.
Securing their critical documents on the cloud from data threats is a major challenge faced by organizations today. Controlling and limiting access to such documents requires a robust and trustworthy access control mechanism. In this paper, we propose a semantically rich access control system that employs an access broker module to evaluate access decisions based on rules generated using the organizations confidentiality policies. The proposed system analyzes the multi-valued attributes of the user making the request and the requested document that is stored on a cloud service platform, before making an access decision. Furthermore, our system guarantees an end-to-end oblivious data transaction between the organization and the cloud service provider using oblivious storage techniques. Thus, an organization can use our system to secure their documents as well as obscure their access pattern details from an untrusted cloud service provider.
Use of digital token - which certifies the bearer's rights to some kind of products or services - is quite common nowadays for its convenience, ease of use and cost-effectiveness. Many of such digital tokens, however, are produced with software alone, making them vulnerable to forgery, including alteration and duplication. For a more secure safeguard for both token owner's right and service provider's accountability, digital tokens should be tamper-resistant as much as possible in order for them to withstand physical attacks as well. In this paper, we present a rights management system that leverages tamper-resistant digital tokens created by hardware-software collaboration in our eTRON architecture. The system features the complete life cycle of a digital token from generation to storage and redemption. Additionally, it provides a secure mechanism for transfer of rights in a peer-to-peer manner over the Internet. The proposed system specifies protocols for permissible manipulation on digital tokens, and subsequently provides a set of APIs for seamless application development. Access privileges to the tokens are strictly defined and state-of-the-art asymmetric cryptography is used for ensuring their confidentiality. Apart from the digital tokens being physically tamper-resistant, the protocols involved in the system are proven to be secure against attacks. Furthermore, an authentication mechanism is implemented that invariably precedes any operation involving the digital token in question. The proposed system presents clear security gains compared to existing systems that do not take tamper-resistance into account, and schemes that use symmetric key cryptography.
5G, the fifth generation of mobile communication networks, is considered as one of the main IoT enablers. Connecting billions of things, 5G/IoT will be dealing with trillions of GBytes of data. Securing such large amounts of data is a very challenging task. Collected data varies from simple temperature measurements to more critical transaction data. Thus, applying uniform security measures is a waste of resources (processing, memory, and network bandwidth). Alternatively, a multi-level security model needs to be applied according to the varying requirements. In this paper, we present a multi-level security scheme (BLP) applied originally in the information security domain. We review its application in the network domain, and propose a modified version of BLP for the 5G/IoT case. The proposed model is proven to be secure and compliant with the model rules.
The increasing demand for secure interactions between network domains brings in new challenges to access control technologies. In this paper we design an access control framework which provides a multilevel mapping method between hierarchical access control structures for achieving multilevel security protection in cross-domain networks. Hierarchical access control structures ensure rigorous multilevel security in intra domains. And the mapping method based on subject attributes is proposed to determine the subject's security level in its target domain. Experimental results we obtained from simulations are also reported in this paper to verify the effectiveness of the proposed access control model.
In the big data era, many users upload data to cloud while security concerns are growing. By using attribute-based encryption (ABE), users can securely store data in cloud while exerting access control over it. Revocation is necessary for real-world applications of ABE so that revoked users can no longer decrypt data. In actual implementations, however, revocation requires re-encryption of data in client side through download, decrypt, encrypt, and upload, which results in huge communication cost between the client and the cloud depending on the data size. In this paper, we propose a new method where the data can be re-encrypted in cloud without downloading any data. The experimental result showed that our method reduces the communication cost by one quarter in comparison with the trivial solution where re-encryption is performed in client side.
In the recent years, we have observed the development of several connected and mobile devices intended for daily use. This development has come with many risks that might not be perceived by the users. These threats are compromising when an unauthorized entity has access to private big data generated through the user objects in the Internet of Things. In the literature, many solutions have been proposed in order to protect the big data, but the security remains a challenging issue. This work is carried out with the aim to provide a solution to the access control to the big data and securing the localization of their generator objects. The proposed models are based on Attribute Based Encryption, CHORD protocol and $μ$TESLA. Through simulations, we compare our solutions to concurrent protocols and we show its efficiency in terms of relevant criteria.
Data outsourcing in cloud is emerging as a successful paradigm that benefits organizations and enterprises with high-performance, low-cost, scalable data storage and sharing services. However, this paradigm also brings forth new challenges for data confidentiality because the outsourced are not under the physic control of the data owners. The existing schemes to achieve the security and usability goal usually apply encryption to the data before outsourcing them to the storage service providers (SSP), and disclose the decryption keys only to authorized user. They cannot ensure the security of data while operating data in cloud where the third-party services are usually semi-trustworthy, and need lots of time to deal with the data. We construct a privacy data management system appending hierarchical access control called HAC-DMS, which can not only assure security but also save plenty of time when updating data in cloud.
Security challenges are the most important obstacles for the advancement of IT-based on-demand services and cloud computing as an emerging technology. Lack of coincidence in identity management models based on defined policies and various security levels in different cloud servers is one of the most challenging issues in clouds. In this paper, a policy- based user authentication model has been presented to provide a reliable and scalable identity management and to map cloud users' access requests with defined polices of cloud servers. In the proposed schema several components are provided to define access policies by cloud servers, to apply policies based on a structural and reliable ontology, to manage user identities and to semantically map access requests by cloud users with defined polices. Finally, the reliability and efficiency of this policy-based authentication schema have been evaluated by scientific performance, security and competitive analysis. Overall, the results show that this model has met defined demands of the research to enhance the reliability and efficiency of identity management in cloud computing environments.
Fast Health Interoperability Services (FHIR) is the most recent in the line of standards for healthcare resources. FHIR represents different types of medical artifacts as resources and also provides recommendations for their authorized disclosure using web-based protocols including O-Auth and OpenId Connect and also defines security labels. In most cases, Role Based Access Control (RBAC) is used to secure access to FHIR resources. We provide an alternative approach based on Attribute Based Access Control (ABAC) that allows attributes of subjects and objects to take part in authorization decision. Our system allows various stakeholders to define policies governing the release of healthcare data. It also authenticates the end user requesting access. Our system acts as a middle-layer between the end-user and the FHIR server. Our system provides efficient release of individual and batch resources both during normal operations and also during emergencies. We also provide an implementation that demonstrates the feasibility of our approach.