Securing messaging services through efficient signcryption with designated equality test

National Research Foundation (NRF) Singapor

Identity-Based Higncryption

Identity-based cryptography (IBC) is fundamental to security and privacy protection. Identity-based authenticated encryption (i.e., signcryption) is an important IBC primitive, which has numerous and promising applications. After two decades of research on signcryption,recently a new cryptographic primitive, named higncryption, was proposed. Higncryption can be viewed as privacy-enhanced signcryption, which integrates public key encryption, entity authentication, and identity concealment (which is not achieved in signcryption) into a monolithic primitive. Here, briefly speaking, identity concealment means that the transcript of protocol runs should not leak participants\u27 identity information. In this work, we propose the first identity-based higncryption (IBHigncryption). The most impressive feature of IBHigncryption, among others, is its simplicity and efficiency. The proposed IBHigncryption scheme is essentially as efficient as the fundamental CCA-secure Boneh-Franklin IBE scheme [18], while offering entity authentication and identity concealment simultaneously. Compared to the identity-based signcryption scheme [11], which is adopted in the IEEE P1363.3 standard, our IBHigncryption scheme is much simpler, and has significant efficiency advantage in total. Besides, our IBHigncryption enjoys forward ID-privacy, receiver deniability and x-security simultaneously. In addition, the proposed IBHigncryption has a much simpler setup stage with smaller public parameters, which in particular does not have the traditional master public key. Higncryption is itself one-pass identity-concealed authenticated key exchange without forward security for the receiver. Finally, by applying the transformation from higncryption to identity-concealed authenticated key exchange (CAKE), we get three-pass identity-based CAKE (IB-CAKE) with explicit mutual authentication and strong security (in particular, perfect forward security for both players). Specifically, the IB-CAKE protocol involves the composition of two runs of IBHigncryption, and has the following advantageous features inherited from IBHigncryption: (1) single pairing operation: each player performs only a single pairingoperation; (2) forward ID-privacy; (3) simple setup without master public key; (4) strong resilience to ephemeral state exposure, i.e., x-security; (5) reasonable deniability

How data will transform industrial processes: crowdsensing, crowdsourcing and big data as pillars of industry 4.0

We are living in the era of the fourth industrial revolution, namely Industry 4.0. This paper presents themain aspects related to Industry 4.0, the technologies thatwill enable this revolution, and the main application domains thatwill be affected by it. The effects that the introduction of Internet of Things (IoT), Cyber-Physical Systems (CPS), crowdsensing, crowdsourcing, cloud computing and big data will have on industrial processeswill be discussed. Themain objectiveswill be represented by improvements in: production efficiency, quality and cost-effectiveness; workplace health and safety, as well as quality of working conditions; products' quality and availability, according to mass customisation requirements. The paper will further discuss the common denominator of these enhancements, i.e., data collection and analysis. As data and information will be crucial for Industry 4.0, crowdsensing and crowdsourcing will introduce new advantages and challenges, which will make most of the industrial processes easier with respect to traditional technologies

Efficient and secure business model for content centric network using elliptic curve cryptography

https://onlinelibrary.wiley.com/doi/full/10.1002/dac.3839Initially, Internet has evolved as a resource sharing model where resources are identified by IP addresses. However, with rapid technological advancement, resources/hardware has become cheap and thus, the need of sharing hardware over Internet is reduced. Moreover, people are using Internet mainly for information exchange and hence, Internet has gradually shifted from resource sharing to information sharing model. To meet the recent growing demand of information exchange, Content Centric Network (CCN) is envisaged as a clean‐slate future network architecture which is specially destined for smooth content distribution over Internet. In CCN, content is easily made available using network caching mechanism which is misaligned with the existing business policy of content providers/publishers in IP‐based Internet. Hence, the transition from contemporary IP‐based Internet to CCN demands attention for redesigning the business policy of the content publishers/providers. In this paper, we have proposed efficient and secure communication protocols for flexible CCN business model to protect the existing business policies of the content publisher while maintaining the salient CCN features like in‐network content caching and Interest packet aggregation. To enhance the efficiency and security, the Elliptic Curve Cryptography (ECC) is used. The proposed ECC‐based scheme is analyzed to show that it is resilient to relevant existing cryptographic attacks. The performance analysis in terms of less computation and communication overheads and increased efficiency is given. Moreover, a formal security verification of the proposed scheme is done using widely used AVISPA simulator and BAN logic that shows our scheme is well secured

Security and Privacy Preservation in Mobile Crowdsensing

Mobile crowdsensing (MCS) is a compelling paradigm that enables a crowd of individuals to cooperatively collect and share data to measure phenomena or record events of common interest using their mobile devices. Pairing with inherent mobility and intelligence, mobile users can collect, produce and upload large amounts of data to service providers based on crowdsensing tasks released by customers, ranging from general information, such as temperature, air quality and traffic condition, to more specialized data, such as recommended places, health condition and voting intentions. Compared with traditional sensor networks, MCS can support large-scale sensing applications, improve sensing data trustworthiness and reduce the cost on deploying expensive hardware or software to acquire high-quality data. Despite the appealing benefits, however, MCS is also confronted with a variety of security and privacy threats, which would impede its rapid development. Due to their own incentives and vulnerabilities of service providers, data security and user privacy are being put at risk. The corruption of sensing reports may directly affect crowdsensing results, and thereby mislead customers to make irrational decisions. Moreover, the content of crowdsensing tasks may expose the intention of customers, and the sensing reports might inadvertently reveal sensitive information about mobile users. Data encryption and anonymization techniques can provide straightforward solutions for data security and user privacy, but there are several issues, which are of significantly importance to make MCS practical. First of all, to enhance data trustworthiness, service providers need to recruit mobile users based on their personal information, such as preferences, mobility pattern and reputation, resulting in the privacy exposure to service providers. Secondly, it is inevitable to have replicate data in crowdsensing reports, which may possess large communication bandwidth, but traditional data encryption makes replicate data detection and deletion challenging. Thirdly, crowdsensed data analysis is essential to generate crowdsensing reports in MCS, but the correctness of crowdsensing results in the absence of malicious mobile users and service providers become a huge concern for customers. Finally yet importantly, even if user privacy is preserved during task allocation and data collection, it may still be exposed during reward distribution. It further discourage mobile users from task participation. In this thesis, we explore the approaches to resolve these challenges in MCS. Based on the architecture of MCS, we conduct our research with the focus on security and privacy protection without sacrificing data quality and users' enthusiasm. Specifically, the main contributions are, i) to enable privacy preservation and task allocation, we propose SPOON, a strong privacy-preserving mobile crowdsensing scheme supporting accurate task allocation. In SPOON, the service provider recruits mobile users based on their locations, and selects proper sensing reports according to their trust levels without invading user privacy. By utilizing the blind signature, sensing tasks are protected and reports are anonymized. In addition, a privacy-preserving credit management mechanism is introduced to achieve decentralized trust management and secure credit proof for mobile users; ii) to improve communication efficiency while guaranteeing data confidentiality, we propose a fog-assisted secure data deduplication scheme, in which a BLS-oblivious pseudo-random function is developed to enable fog nodes to detect and delete replicate data in sensing reports without exposing the content of reports. Considering the privacy leakages of mobile users who report the same data, the blind signature is utilized to hide users' identities, and chameleon hash function is leveraged to achieve contribution claim and reward retrieval for anonymous greedy mobile users; iii) to achieve data statistics with privacy preservation, we propose a privacy-preserving data statistics scheme to achieve end-to-end security and integrity protection, while enabling the aggregation of the collected data from multiple sources. The correctness verification is supported to prevent the corruption of the aggregate results during data transmission based on the homomorphic authenticator and the proxy re-signature. A privacy-preserving verifiable linear statistics mechanism is developed to realize the linear aggregation of multiple crowdsensed data from a same device and the verification on the correctness of aggregate results; and iv) to encourage mobile users to participating in sensing tasks, we propose a dual-anonymous reward distribution scheme to offer the incentive for mobile users and privacy protection for both customers and mobile users in MCS. Based on the dividable cash, a new reward sharing incentive mechanism is developed to encourage mobile users to participating in sensing tasks, and the randomization technique is leveraged to protect the identities of customers and mobile users during reward claim, distribution and deposit