Batch Verification of Short Signatures

With computer networks spreading into a variety of new environments, the need to authenticate and secure communication grows. Many of these new environments have particular requirements on the applicable cryptographic primitives. For instance, several applications require that communication overhead be small and that many messages be processed at the same time. In this paper we consider the suitability of public key signatures in the latter scenario. That is, we consider signatures that are 1) short and 2) where many signatures from (possibly) different signers on (possibly) different messages can be verified quickly. Prior work focused almost exclusively on batching signatures from the same signer. We propose the first batch verifier for messages from many (certified) signers without random oracles and with a verification time where the dominant operation is independent of the number of signatures to verify. We further propose a new signature scheme with very short signatures, for which batch verification for many signers is also highly efficient. Combining our new signatures with the best known techniques for batching certificates from the same authority, we get a fast batch verifier for certificates and messages combined. Although our new signature scheme has some restrictions, it is very efficient and still practical for some communication applications

Short One-Time Signatures

We present a new one-time signature scheme having short signatures. Our new scheme supports aggregation, batch verification, and admits efficient proofs of knowledge. It has a fast signing algorithm, requiring only modular additions, and its verification cost is comparable to ECDSA verification. These properties make our scheme suitable for applications on resource-constrained devices such as smart cards and sensor nodes. Along the way, we give a unified description of five previous one-time signature schemes and improve parameter selection for these schemes, and as a corollary we give a fail-stop signature scheme with short signatures

Integrating identity-based cryptography in IMS service authentication

Nowadays, the IP Multimedia Subsystem (IMS) is a promising research field. Many ongoing works related to the security and the performances of its employment are presented to the research community. Although, the security and data privacy aspects are very important in the IMS global objectives, they observe little attention so far. Secure access to multimedia services is based on SIP and HTTP digest on top of IMS architecture. The standard deploys AKA-MD5 for the terminal authentication. The third Generation Partnership Project (3GPP) provided Generic Bootstrapping Architecture (GBA) to authenticate the subscriber before accessing multimedia services over HTTP. In this paper, we propose a new IMS Service Authentication scheme using Identity Based cryptography (IBC). This new scheme will lead to better performances when there are simultaneous authentication requests using Identity-based Batch Verification. We analyzed the security of our new protocol and we presented a performance evaluation of its cryptographic operationsComment: 13Page

Learning Representations from Persian Handwriting for Offline Signature Verification, a Deep Transfer Learning Approach

Offline Signature Verification (OSV) is a challenging pattern recognition task, especially when it is expected to generalize well on the skilled forgeries that are not available during the training. Its challenges also include small training sample and large intra-class variations. Considering the limitations, we suggest a novel transfer learning approach from Persian handwriting domain to multi-language OSV domain. We train two Residual CNNs on the source domain separately based on two different tasks of word classification and writer identification. Since identifying a person signature resembles identifying ones handwriting, it seems perfectly convenient to use handwriting for the feature learning phase. The learned representation on the more varied and plentiful handwriting dataset can compensate for the lack of training data in the original task, i.e. OSV, without sacrificing the generalizability. Our proposed OSV system includes two steps: learning representation and verification of the input signature. For the first step, the signature images are fed into the trained Residual CNNs. The output representations are then used to train SVMs for the verification. We test our OSV system on three different signature datasets, including MCYT (a Spanish signature dataset), UTSig (a Persian one) and GPDS-Synthetic (an artificial dataset). On UT-SIG, we achieved 9.80% Equal Error Rate (EER) which showed substantial improvement over the best EER in the literature, 17.45%. Our proposed method surpassed state-of-the-arts by 6% on GPDS-Synthetic, achieving 6.81%. On MCYT, EER of 3.98% was obtained which is comparable to the best previously reported results

MoPS: A Modular Protection Scheme for Long-Term Storage

Current trends in technology, such as cloud computing, allow outsourcing the storage, backup, and archiving of data. This provides efficiency and flexibility, but also poses new risks for data security. It in particular became crucial to develop protection schemes that ensure security even in the long-term, i.e. beyond the lifetime of keys, certificates, and cryptographic primitives. However, all current solutions fail to provide optimal performance for different application scenarios. Thus, in this work, we present MoPS, a modular protection scheme to ensure authenticity and integrity for data stored over long periods of time. MoPS does not come with any requirements regarding the storage architecture and can therefore be used together with existing archiving or storage systems. It supports a set of techniques which can be plugged together, combined, and migrated in order to create customized solutions that fulfill the requirements of different application scenarios in the best possible way. As a proof of concept we implemented MoPS and provide performance measurements. Furthermore, our implementation provides additional features, such as guidance for non-expert users and export functionalities for external verifiers.Comment: Original Publication (in the same form): ASIACCS 201