Biblio
To allow fine-grained access control of sensitive data, researchers have proposed various types of functional encryption schemes, such as identity-based encryption, searchable encryption and attribute-based encryption. We observe that it is difficult to define some complex access policies in certain application scenarios by using these schemes individually. In this paper, we attempt to address this problem by proposing a functional encryption approach named Key-Policy Attribute-Based Encryption with Attribute Extension (KP-ABE-AE). In this approach, we utilize extended attributes to integrate various encryption schemes that support different access policies under a common top-level KP-ABE scheme, thus expanding the scope of access policies that can be defined. Theoretical analysis and experimental studies are conducted to demonstrate the applicability of the proposed KP-ABE-AE. We also present an optimization for a special application of KP-ABE-AE where IPE schemes are integrated with a KP-ABE scheme. The optimization results in an integrated scheme with better efficiency when compared to the existing encryption schemes that support the same scope of access policies.
KP-ABE mechanism emerges as one of the most suitable security scheme for asymmetric encryption. It has been widely used to implement access control solutions. However, due to its expensive overhead, it is difficult to consider this cryptographic scheme in resource-limited networks, such as the IoT. As the cloud has become a key infrastructural support for IoT applications, it is interesting to exploit cloud resources to perform heavy operations. In this paper, a collaborative variant of KP-ABE named C-KP-ABE for cloud-based IoT applications is proposed. Our proposal is based on the use of computing power and storage capacities of cloud servers and trusted assistant nodes to run heavy operations. A performance analysis is conducted to show the effectiveness of the proposed solution.
The Internet of Things (IoT) is a new paradigm in which every-day objects are interconnected between each other and to the Internet. This paradigm is receiving much attention of the scientific community and it is applied in many fields. In some applications, it is useful to prove that a number of objects are simultaneously present in a group. For example, an individual might want to authorize NFC payment with his mobile only if k of his devices are present to ensure that he is the right person. This principle is known as Grouping-Proofs. However, existing Grouping-Proofs schemes are mostly designed for RFID systems and don't fulfill the IoT characteristics. In this paper, we propose a Threshold Grouping-Proofs for IoT applications. Our scheme uses the Key-Policy Attribute-Based Encryption (KP-ABE) protocol to encrypt a message so that it can be decrypted only if at least k objects are simultaneously present in the same location. A security analysis and performance evaluation is conducted to show the effectiveness of our proposal solution.
In many hostile military environments for instance war zone, unfriendly nature, etc., the systems perform on the specially promoted mode and nature which they tolerate the defined system network architecture. Preparation of Disruption-Tolerant systems (DTN) enhances the network between the remote devices which provided to the soldiers in the war zone, this situation conveys the reliable data transmission under scanner. Cipher text approach are based on the attribute based encryption which mainly acts on the attributes or role of the users, which is a successful cryptographic strategy to maintain the control issues and also allow reliable data transfer. Specially, the systems are not centralized and have more data constrained issues in the systems, implementing the Ciphertext-Policy Attribute-Based Encryption (CP-ABE) was an important issue, where this strategy provides the new security and data protection approach with the help of the Key Revocation, Key Escrows and collaboration of the certain attributes with help of main Key Authorities. This paper mainly concentrates on the reliable data retrieval system with the help of CP-ABE for the Disruption-Tolerant Networks where multiple key authorities deal with respective attributes safely and securely. We performed comparison analysis on existing schemes with the recommended system components which are configured in the respective decentralized tolerant military system for reliable data retrieval.
With the rapid development of mobile internet, mobile devices are requiring more complex authorization policy to ensure an secure access control on mobile data. However mobiles have limited resources (computing, storage, etc.) and are not suitable to execute complex operations. Cloud computing is an increasingly popular paradigm for accessing powerful computing resources. Intuitively we can solve that problem by moving the complex access control process to the cloud and implement a fine-grained access control relying on the powerful cloud. However the cloud computation may not be trusted, a crucial problem is how to verify the correctness of such computations. In this paper, we proposed a public verifiable cloud access control scheme based on Parno's public verifiable computation protocol. For the first time, we proposed the conception and concrete construction of verifiable cloud access control. Specifically, we firstly design a user private key revocable Key Policy Attribute Based Encryption (KP-ABE) scheme with non-monotonic access structure, which can be combined with the XACML policy perfectly. Secondly we convert the XACML policy into the access structure of KP-ABE. Finally we construct a security provable public verifiable cloud access control scheme based on the KP-ABE scheme we designed.
In the modern security-conscious world, Deep Packet Inspection (DPI) proxies are increasingly often used on industrial and enterprise networks to perform TLS unwrapping on all outbound connections. However, enabling TLS unwrapping requires local devices to have the DPI proxy Certificate Authority certificates installed. While for conventional computing devices this is addressed via enterprise management, it's a difficult problem for Internet of Things ("IoT") devices which are generally not under enterprise management, and may not even be capable of it due to their resource-constrained nature. Thus, for typical IoT devices, being installed on a network with DPI requires either manual device configuration or custom DPI proxy configuration, both of which solutions have significant shortcomings. This poses a serious challenge to the deployment of IoT devices on DPI-enabled intranets. The authors propose a solution to this problem: a method of installing on IoT devices the CA certificates for DPI proxy CAs, as well as other security configuration ("security bootstrapping"). The proposed solution respects the DPI policies, while allowing the commissioning of IoT and IIoT devices without the need for additional manual configuration either at device scope or at network scope. This is accomplished by performing the bootstrap operation over unsecured connection, and downloading certificates using TLS validation at application level. The resulting solution is light-weight and secure, yet does not require validation of the DPI proxy's CA certificates in order to perform the security bootstrapping, thus avoiding the chicken-and-egg problem inherent in using TLS on DPI-enabled intranets.
Cloud Computing is the most promising paradigm in recent times. It offers a cost-efficient service to individual and industries. However, outsourcing sensitive data to entrusted Cloud servers presents a brake to Cloud migration. Consequently, improving the security of data access is the most critical task. As an efficient cryptographic technique, Ciphertext Policy Attribute Based Encryption(CP-ABE) develops and implements fine-grained, flexible and scalable access control model. However, existing CP-ABE based approaches suffer from some limitations namely revocation, data owner overhead and computational cost. In this paper, we propose a sliced revocable solution resolving the aforementioned issues abbreviated RS-CPABE. We applied splitting algorithm. We execute symmetric encryption with Advanced Encryption Standard (AES)in large data size and asymmetric encryption with CP-ABE in constant key length. We re-encrypt in case of revocation one single slice. To prove the proposed model, we expose security and performance evaluation.
This work takes a novel approach to classifying the behavior of devices by exploiting the single-purpose nature of IoT devices and analyzing the complexity and variance of their network traffic. We develop a formalized measurement of complexity for IoT devices, and use this measurement to precisely tune an anomaly detection algorithm for each device. We postulate that IoT devices with low complexity lead to a high confidence in their behavioral model and have a correspondingly more precise decision boundary on their predicted behavior. Conversely, complex general purpose devices have lower confidence and a more generalized decision boundary. We show that there is a positive correlation to our complexity measure and the number of outliers found by an anomaly detection algorithm. By tuning this decision boundary based on device complexity we are able to build a behavioral framework for each device that reduces false positive outliers. Finally, we propose an architecture that can use this tuned behavioral model to rank each flow on the network and calculate a trust score ranking of all traffic to and from a device which allows the network to autonomously make access control decisions on a per-flow basis.
Despite bringing many benefits of global network configuration and control, Software Defined Networking (SDN) also presents potential challenges for both digital forensics and cybersecurity. In fact, there are various attacks targeting a range of vulnerabilities on vital elements of this paradigm such as controller, Northbound and Southbound interfaces. In addition to solutions of security enhancement, it is important to build mechanisms for digital forensics in SDN which provide the ability to investigate and evaluate the security of the whole network system. It should provide features of identifying, collecting and analyzing log files and detailed information about network devices and their traffic. However, upon penetrating a machine or device, hackers can edit, even delete log files to remove the evidences about their presence and actions in the system. In this case, securing log files with fine-grained access control in proper storage without any modification plays a crucial role in digital forensics and cybersecurity. This work proposes a blockchain-based approach to improve the security of log management in SDN for network forensics, called SDNLog-Foren. This model is also evaluated with different experiments to prove that it can help organizations keep sensitive log data of their network system in a secure way regardless of being compromised at some different components of SDN.
Advanced metering infrastructure (AMI) is a key component in the smart grid. Transmitting data robustly and reliably between the tremendous smart meters in the AMI is one of the most crucial tasks for providing various services in smart grid. Among the many efforts for designing practical routing protocols for the AMI, the Routing Protocol for Low-Power and Lossy Networks (RPL) proposed by the IETF ROLL working group is considered the most consolidated candidate. Resent research has shown cyber attacks such as blackhole attack and version number attack can seriously damage the performance of the network implementing RPL. The main reason that RPL is vulnerable to these kinds of attacks is the lack an authentication mechanism. In this paper, we study the impact of blackhole attacks on the performance of the AMI network and proposed a new blackhole attack that can bypass the existing defense mechanism. Then, we propose a cuckoo filter based RPL to defend the AMI network from blackhole attacks. We also give the security analysis of the proposed method.