133 research outputs found

    Cryptanalysis and improvement of certificateless aggregate signature with conditional privacy-preserving for vehicular sensor networks

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    Secure aggregate signature schemes have attracted more concern due to their wide application in resource constrained environment. Recently, Horng et al. [S. J. Horng et al., An efficient certificateless aggregate signature with conditional privacy-preserving for vehicular sensor networks, Information Sciences 317 (2015) 48-66] proposed an efficient certificateless aggregate signature with conditional privacy-preserving for vehicular sensor networks. They claimed that their scheme was provably secure against existential forgery on adaptively chosen message attack in the random oracle model. In this paper, we show that their scheme is insecure against a malicious-but-passive KGC under existing security model. Further, we propose an improved certificateless aggregate signature

    Practical Certificateless Aggregate Signatures From Bilinear Maps

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    Aggregate signature is a digital signature with a striking property that anyone can aggregate n individual signatures on n different messages which are signed by n distinct signers, into a single compact signature to reduce computational and storage costs. In this work, two practical certificateless aggregate signature schemes are proposed from bilinear maps. The first scheme CAS-1 reduces the costs of communication and signer-side computation but trades off the storage, while CAS-2 minimizes the storage but sacrifices the communication costs. One can choose either of the schemes by consideration of the application requirement. Compare with ID-based schemes, our schemes do not entail public key certificates as well and achieve the trust level 3, which imply the frauds of the authority are detectable. Both of the schemes are proven secure in the random oracle model by assuming the intractability of the computational Diffie-Hellman problem over the groups with bilinear maps, where the forking lemma technique is avoided

    Aggregatable Certificateless Designated Verifier Signature

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    In recent years, the Internet of Things (IoT) devices have become increasingly deployed in many industries and generated a large amount of data that needs to be processed in a timely and efficient manner. Using aggregate signatures, it provides a secure and efficient way to handle large numbers of digital signatures with the same message. Recently, the privacy issue has been concerned about the topic of data sharing on the cloud. To provide the integrity, authenticity, authority, and privacy on the data sharing in the cloud storage, the notion of an aggregatable certificateless designated verifier signature scheme (ACLDVS) was proposed. ACLDVS also is a perfect tool to enable efficient privacy-preserving authentication systems for IoT and or the vehicular ad hoc networks (VANET). Our concrete scheme was proved to be secured underling of the Computational Diffie-Hellman assumption. Compared to other related schemes, our scheme is efficient, and the signature size is considerably short

    APEX2S: A Two-Layer Machine Learning Model for Discovery of host-pathogen protein-protein Interactions on Cloud-based Multiomics Data

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    Presented by the avalanche of biological interactions data, computational biology is now facing greater challenges on big data analysis and solicits more studies to mine and integrate cloud-based multiomics data, especially when the data are related to infectious diseases. Meanwhile, machine learning techniques have recently succeeded in different computational biology tasks. In this article, we have calibrated the focus for host-pathogen protein-protein interactions study, aiming to apply the machine learning techniques for learning the interactions data and making predictions. A comprehensive and practical workflow to harness different cloud-based multiomics data is discussed. In particular, a novel two-layer machine learning model, namely APEX2S, is proposed for discovery of the protein-protein interactions data. The results show that our model can better learn and predict from the accumulated host-pathogen protein-protein interactions

    Cryptanalysis of an online/offline certificateless signature scheme for Internet of Health Things

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    Recently, Khan et al. [An online-offline certificateless signature scheme for internet of health things,ā€ Journal of Healthcare Engineering, vol. 2020] presented a new certificateless offline/online signature scheme for Internet of Health Things (IoHT) to fulfill the authenticity requirements of the resource-constrained environment of (IoHT) devices. The authors claimed that the newly proposed scheme is formally secured against Type-I adversary under the Random Oracle Model (ROM). Unfortunately, their scheme is insecure against adaptive chosen message attacks. It is demonstrated that an adversary can forge a valid signature on a message by replacing the public key. Furthermore, we performed a comparative analysis of the selective parameters including computation time, communication overhead, security, and formal proof by employing Evaluation based on Distance from Average Solution (EDAS). The analysis shows that the designed scheme of Khan et al. doesnā€™t have any sort of advantage over the previous schemes. Though, the authors utilized a lightweight hyperelliptic curve cryptosystem with a smaller key size of 80-bits. Finally, we give some suggestions on the construction of a concrete security scheme under ROM
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