In this research, we introduce MIND-Crypt, a novel attack framework that uses deep learning (DL) and transfer learning (TL) to challenge the indistinguishability of block ciphers, specifically SPECK32/64 encryption algorithm in CBC mode (Cipher Block Chaining) against Known Plaintext Attacks (KPA). Our methodology includes training a DL model with ciphertexts of two messages encrypted using the same key. The selected messages have the same byte-length and differ by only one bit at the binary...

In [1], two generic constructions for biometric-based non-transferable Attribute Based Credentials (biometric ABC) are presented, which offer different trade-offs between efficiency and trust assumptions. In this paper, we focus on the second scheme denoted as BioABC-ZK that tries to remove the strong (and unrealistic) trust assumption on the Reader R, and show that BioABC-ZK has a security flaw for a colluding R and Verifier V. Besides, BioABC-ZK lacks GDPR-compliance, which requires secure...

Previous studies on deep-learning-based side-channel attacks (DL-SCAs) have shown that traditional performance evaluation metrics commonly used in DL, like accuracy and F1 score, are not effective in evaluating DL-SCA performance. Therefore, some previous studies have proposed new alternative metrics for evaluating the performance of DL-SCAs. Notably, perceived information (PI) and effective perceived information (EPI) are major metrics based on information theory. While it has been...

Despite decades of effort, a stubborn chasm exists between the theory and practice of device-level biometric authentication. Deployed authentication algorithms rely on data that overtly leaks private information about the biometric; thus systems rely on externalized security measures such as trusted execution environments. The authentication algorithms have no cryptographic guarantees. This is particularly frustrating given the long line of research that has developed theoretical...

On CRYPTO2021, Nishanth Chandran, Bhavana Kanukurthi, Sai Lakshmi Bhavana Obattu, and Sruthi Sekar presented a novel secret sharing scheme, called CKO+21 scheme. This scheme makes use of Shamir secret sharing schemes and randomness extractors as its basic components, to generate a multi-layer encapsulation structure. The authors claimed that CKO+21 scheme satisfied “leakage resilience”, that is, the privacy still held under both “not enough revealing” and “appropriate leakage”. More...

With the growing adoption of facial recognition worldwide as a popular authentication method, there is increasing concern about the invasion of personal privacy due to the lifetime irrevocability of facial features. In principle, {\it Fuzzy Extractors} enable biometric-based authentication while preserving the privacy of biometric templates. Nevertheless, to our best knowledge, most existing fuzzy extractors handle binary vectors with Hamming distance, and no explicit construction is known...

Among the various authentication methods, biometrics provide good user friendliness. However, the non-renewability of biometrics leads to the problem that it might be stolen. The emergence of fuzzy extractors is a promising solution to this problem. The fuzzy extractors can extract uniformly distributed keys from various noise random sources (such as biometrics, physical unclonable functions and quantum bits). However, the research on fuzzy extractors mainly focuses on the theoretical level,...

With the development of side-channel attacks, a necessity arises to invent authenticated key exchange protocols in a leakage-resilient manner. Constructing authenticated key exchange protocols using existing cryptographic schemes is an effective method, as such construction can be instantiated with any appropriate scheme in a way that the formal security argument remains valid. In parallel, constructing authenticated key exchange protocols that are proven to be secure in the standard model...

Biometric databases collect people’s information and allow users to perform proximity searches (finding all records within a bounded distance of the query point) with few cryptographic protections. This work studies proximity searchable encryption applied to the iris biometric. Prior work proposed inner product functional encryption as a technique to build proximity biometric databases (Kim et al., SCN 2018). This is because binary Hamming distance is computable using an inner product. This...

Physical Unclonable Functions (PUFs) are used in various key-generation schemes and protocols. Such schemes are deemed to be secure even for PUFs with challenge-response behavior, as long as no responses and no reliability information about the PUF are exposed. This work, however, reveals a pitfall in these constructions: When using state-of-the-art helper data algorithms to correct noisy PUF responses, an attacker can exploit the publicly accessible helper data and challenges. We show that...

Two-source non-malleable extractors are pseudorandom objects which extract randomness even when an adversary is allowed to learn the behavior of the extractor on tamperings of the input weak sources, and they have found important applications in non-malleable coding and secret sharing. We begin by asking how hard it is to improve upon the best known constructions of such objects (Chattopadhyay, Goyal, Li, STOC 2016, and Li, STOC 2017). We show that even small improvements to these...

We introduce a natural generalization of two-source non-malleable extractors (Cheragachi and Guruswami, TCC 2014) called as \textit{multi-source non-malleable extractors}. Multi-source non-malleable extractors are special independent source extractors which satisfy an additional non-malleability property. This property requires that the output of the extractor remains close to uniform even conditioned on its output generated by tampering {\it several sources together}. We formally define...

A number of works have focused on the setting where an adversary tampers with the shares of a secret sharing scheme. This includes literature on verifiable secret sharing, algebraic manipulation detection(AMD) codes, and, error correcting or detecting codes in general. In this work, we initiate a systematic study of what we call non-malleable secret sharing. Very roughly, the guarantee we seek is the following: the adversary may potentially tamper with all of the shares, and still, either...

We are at the dawn of a hyper connectivity age otherwise known as the Internet of Things (IoT). It is widely accepted that to be able to reap all benefits from the IoT promise, device security will be of paramount importance. A key requirement for most security solutions is the ability to provide secure cryptographic key storage in a way that will easily scale in the IoT age. In this paper, we focus on providing such a solution based on Physical Unclonable Functions (PUFs). To this end,...