Lightweight attribute-based encryption supporting access policy update for cloud assisted IoT

Cloud-assisted IoT applications are gaining an expanding interest, such that IoT devices are deployed in different distributed environments to collect and outsource sensed data to remote servers for further processing and sharing among users. On the one hand, in several applications, collected data are extremely sensitive and need to be protected before outsourcing. Generally, encryption techniques are applied at the data producer side to protect data from adversaries as well as curious cloud provider. On the other hand, sharing data among users requires fine grained access control mechanisms. To ensure both requirements, Attribute Based Encryption (ABE) has been widely applied to ensure encrypted access control to outsourced data. Although, ABE ensures fine grained access control and data confidentiality, updates of used access policies after encryption and outsourcing of data remains an open challenge. In this paper, we design PU-ABE, a new variant of key policy attribute based encr yption supporting efficient access policy update that captures attributes addition and revocation to access policies. PU-ABE contributions are multifold. First, access policies involved in the encryption can be updated without requiring sharing secret keys between the cloud server and the data owners neither re-encrypting data. Second, PU-ABE ensures privacy preserving and fine grained access control to outsourced data. Third, ciphertexts received by the end-user are constant sized and independent from the number of attributes used in the access policy which affords low communication and storage costs

CUPS : Secure Opportunistic Cloud of Things Framework based on Attribute Based Encryption Scheme Supporting Access Policy Update

The ever‐growing number of internet connected devices, coupled with the new computing trends, namely within emerging opportunistic networks, engenders several security concerns. Most of the exchanged data between the internet of things (IoT) devices are not adequately secured due to resource constraints on IoT devices. Attribute‐based encryption is a promising cryptographic mechanism suitable for distributed environments, providing flexible access control to encrypted data contents. However, it imposes high decryption costs, and does not support access policy update, for highly dynamic environments. This paper presents CUPS, an ABE‐based framework for opportunistic cloud of things applications, that securely outsources data decryption process to edge nodes in order to reduce the computation overhead on the user side. CUPS allows end‐users to offload most of the decryption overhead to an edge node and verify the correctness of the received partially decrypted data from the edge node. Moreover, CUPS provides the access policy update feature with neither involving a proxy‐server, nor re‐encrypting the enciphered data contents and re‐distributing the users' secret keys. The access policy update feature in CUPS does not affect the size of the message received by the end‐user, which reduces the bandwidth and the storage usage. Our comprehensive theoretical analysis proves that CUPS outperforms existing schemes in terms of functionality, communication and computation overheads

A survey of IoT security based on a layered architecture of sensing and data analysis

The Internet of Things (IoT) is leading today’s digital transformation. Relying on a combination of technologies, protocols, and devices such as wireless sensors and newly developed wearable and implanted sensors, IoT is changing every aspect of daily life, especially recent applications in digital healthcare. IoT incorporates various kinds of hardware, communication protocols, and services. This IoT diversity can be viewed as a double-edged sword that provides comfort to users but can lead also to a large number of security threats and attacks. In this survey paper, a new compacted and optimized architecture for IoT is proposed based on five layers. Likewise, we propose a new classification of security threats and attacks based on new IoT architecture. The IoT architecture involves a physical perception layer, a network and protocol layer, a transport layer, an application layer, and a data and cloud services layer. First, the physical sensing layer incorporates the basic hardware used by IoT. Second, we highlight the various network and protocol technologies employed by IoT, and review the security threats and solutions. Transport protocols are exhibited and the security threats against them are discussed while providing common solutions. Then, the application layer involves application protocols and lightweight encryption algorithms for IoT. Finally, in the data and cloud services layer, the main important security features of IoT cloud platforms are addressed, involving confidentiality, integrity, authorization, authentication, and encryption protocols. The paper is concluded by presenting the open research issues and future directions towards securing IoT, including the lack of standardized lightweight encryption algorithms, the use of machine-learning algorithms to enhance security and the related challenges, the use of Blockchain to address security challenges in IoT, and the implications of IoT deployment in 5G and beyond

A HYBRIDIZED ENCRYPTION SCHEME BASED ON ELLIPTIC CURVE CRYPTOGRAPHY FOR SECURING DATA IN SMART HEALTHCARE

Recent developments in smart healthcare have brought us a great deal of convenience. Connecting common objects to the Internet is made possible by the Internet of Things (IoT). These connected gadgets have sensors and actuators for data collection and transfer. However, if users' private health information is compromised or exposed, it will seriously harm their privacy and may endanger their lives. In order to encrypt data and establish perfectly alright access control for such sensitive information, attribute-based encryption (ABE) has typically been used. Traditional ABE, however, has a high processing overhead. As a result, an effective security system algorithm based on ABE and Fully Homomorphic Encryption (FHE) is developed to protect health-related data. ABE is a workable option for one-to-many communication and perfectly alright access management of encrypting data in a cloud environment. Without needing to decode the encrypted data, cloud servers can use the FHE algorithm to take valid actions on it. Because of its potential to provide excellent security with a tiny key size, elliptic curve cryptography (ECC) algorithm is also used. As a result, when compared to related existing methods in the literature, the suggested hybridized algorithm (ABE-FHE-ECC) has reduced computation and storage overheads. A comprehensive safety evidence clearly shows that the suggested method is protected by the Decisional Bilinear Diffie-Hellman postulate. The experimental results demonstrate that this system is more effective for devices with limited resources than the conventional ABE when the system’s performance is assessed by utilizing standard model

Privacy-preserving data search with fine-grained dynamic search right management in fog-assisted Internet of Things

This is the author accepted manuscript. The final version is available from Elsevier via the DOI in this record.Fog computing, as an assisted method for cloud computing, collects Internet of Things (IoT) data to multiple fog nodes on the edge of IoT and outsources them to the cloud for data search, and it reduces the computation cost on IoT nodes and provides fine-grained search right management. However, to provide privacy-preserving IoT data search, the existing searchable encryptions are very inefficient as the computation cost is too high for the resource-constrained IoT ends. Moreover, to provide dynamic search right management, the users need to be online all the time in the existing schemes, which is impractical. In this paper, we first present a new fog-assisted privacy-preserving IoT data search framework, where the data from each IoT device is collected by a fog node, stored in a determined document and outsourced to the cloud, the users search the data through the fog nodes, and the fine-grained search right management is maintained at document level. Under this framework, two searchable encryption schemes are proposed, i.e., Credible Fog Nodes assisted Searchable Encryption (CFN-SE) and Semi-trusted Fog Nodes assisted Searchable Encryption (STFN-SE). In CFN-SE scheme, the indexes and trapdoors are generated by the fog nodes, which greatly reduce the computation costs at the IoT devices and user ends, and fog nodes are used to support offline users’ key update. In STFN-SE scheme, the semi-trusted fog nodes are used to provide storage of encrypted key update information to assist offline users’ search right update. In both schemes, no re-encryption of the keywords is needed in search right updates. The performance evaluations of our schemes demonstrate the feasibility and high efficiency of our system.National Key Research and Development ProgramNational Natural Science Foundation of ChinaSichuan Provincial Major Frontier IssuesState Key Laboratory of Integrated Services Networks, Xidian Universit

BLA2C2: Design of a Novel Blockchain-based Light-Weight Authentication & Access Control Layer for Cloud Deployments

Cloud deployments are consistently under attack, from both internal and external adversaries. These attacks include, but are not limited to brute force, masquerading, improper access, session hijacking, cross site scripting (XSS), etc. To mitigate these attacks, a wide variety of authentication & access control models are proposed by researchers, and each of them vary in terms of their internal implementation characteristics. It was observed that these models are either highly complex, or lack in terms of security under multiple attacks, which limits their applicability for real-time deployments. Moreover, some of these models are not flexible and cannot be deployed under dynamic cloud scenarios (like constant reconfigurations of Virtual Machines, dynamic authentication use-cases, etc.). To overcome these issues, this text proposes design of a novel blockchain-based Light-weight authentication & access control layer that can be used for dynamic cloud deployments. The proposed model initially applies a header-level light-weight sanitization layer that removes Cross Site Scripting, SQL Injection, and other data-level attacks. This is followed by a light-weight authentication layer, that assists in improving login-level security for external attacks. The authentication layer uses IP matching with reverse geolocation mapping in order to estimate outlier login attempts. This layer is cascaded with an efficient blockchain-based access control model, which assists in mitigating session hijacking, masquerading, sybil and other control-level attacks. The blockchain model is developed via integration of Grey Wolf Optimization (GWO) to reduce unnecessary complexities, and provides faster response when compared with existing blockchain-based security deployments. Efficiency of the model was estimated in terms of accuracy of detection for different attack types, delay needed for detection of these attacks, and computational complexity during attack mitigation operations. This performance was compared with existing models, and it was observed that the proposed model showcases 8.3% higher accuracy, with 10.5% lower delay, and 5.9% lower complexity w.r.t. standard blockchain-based & other security models. Due to these enhancements, the proposed model was capable of deployment for a wide variety of large-scale scenarios

PARFAIT:Privacy-preserving, secure, and low-delay service access in fog-enabled IoT ecosystems

Traditional fog-enabled IoT ecosystems always assume fully-trusted and secure fog nodes, offering computational capabilities and storage space closer to constrained IoT devices. However, such security-related assumptions can easily fall when considering the exposure of fog nodes’ location, the heterogeneity of device providers, and the ease of misuse and misconfigurations by end-users, to name a few. As a result, compromised fog nodes can stealthily steal sensitive information, such as the devices’ location, path, and private personal attributes. This paper presents PARFAIT, a privacy-preserving, secure, and low-delay framework for securely accessing services in fog-enabled IoT ecosystems. PARFAITguarantees low-delay authentication and authorization to local fog nodes, protecting the identity and the attributes possessed by the IoT devices. Moreover, PARFAITuses rolling ephemeral identities, providing unlinkability among access requests, thus preventing the tracking of mobile IoT devices by multiple compromised fog nodes. We performed several experimental tests on a reference proof-of-concept to show the viability of PARFAIT. Specifically, adopting an elliptic curve with a group size of 512 bits, PARFAITallows the access to a single protected resource in only 0.274 s, and such a delay rises to only 0.359 s with 10 consecutive requests (66.8% less than the quickest competing approach).</p