Shared Key Research Articles

Multi-party blind quantum computation protocol with mutual authentication in network

Blind quantum computation (BQC) can ensure a client with limited quantum capability safely delegates computing tasks to a remote quantum server. In order to resist attacks from ignoring identity authentication in BQC protocols, it is necessary to guarantee the legality of both clients and servers in a multi-party BQC network. So we propose a multi-party BQC protocol involving three phases to distribute shared keys and authenticate identities. Firstly, by using the advantages of measurement device independent quantum key distribution (MDI-QKD), the registered client and the assigned server could share the initial key safely in registration phase. Secondly, with the help of semi-honest certificate authority (CA), mutual identity authentication phase realizes the two-way authentication from both sides through the shared key simultaneously. Thirdly, in the blind quantum computing phase, a registered client can complete his computing task by just measuring the qubits from the assigned server rather than preparing the qubits. Moreover, combined with first-in-first-out (FIFO) principle, clients’ authentication and blind quantum computing can be processed in parallel. The protocol can also be applied in other multi-party BQC protocols with the universality of resource states. Compared with other BQC protocols, the reliability of the protocol with identity authentication is guaranteed, and the efficiency will be significantly reflected in real experiments.

Lightweight Aggregated Data Encryption for Wireless Sensor Networks (WSNs)

The primary task of wireless sensor networks (WSNs) is to collect various types of data, for example, weather data, traffic data, etc. Collected data in WSNs are different from most data transmitted in digital communication applications. Most collected data in WSNs contain only few bits of information, but most data in data communication applications contain a large number of bits. All existing data encryptions in WSNs use conventional symmetric-key encryptions (e.g., advanced encryption standard (AES)) in which each large-size key is used to encrypt a block of large-size of data (e.g., a fixed block size of 128 bit in AES), and the security is based on a large-size of pairwise shared key (e.g., 128/192/ 256 bits in AES) between the sender node and the receiver node. Obviously, these conventional encryptions are not suitable for WSNs since the size of keys are much larger than the size of data. We propose a novel data encryption, in which it encrypts only few bits of data, and the security is based on multiple pairwise shared keys with short length. The encryption speed is much faster than conventional symmetric encryptions. Data aggregation is an efficient way to transmit data in a network. In the past, most encrypted data aggregations were designed based on public-key based homomorphic encryption. Public-key encryptions need time-consuming computation, so these schemes are not suitable for applications in WSNs. Most data in WSNs are routed through a path from the source node to the receiver node, which involves multiple sensor nodes. Our encrypted data aggregation is also called path-oriented data encryption. When multiple data are collected in WSNs, our scheme allows sensors in the path to aggregate all collected data in a piggyback ride. Our proposed encrypted data aggregation is a lightweight solution, which is suitable for applications in WSNs.

The Improving properties of Viscose fabric by water repellent finish

Viscose as cellulosic origin, the cheapest of all cellulosic fabrics could be the best alternative. Viscose is manufactured from regenerated cellulose. In order to manufacture viscose, pulp of bamboo is treated with aqueous sodium hydroxide to form alkali cellulose. This alkali cellulose is then treated with carbon disulfide to form sodium cellulose xanthate. The xanthate is then dissolved in aqueous sodium hydroxide and allowed to depolymerize. After depolymerization, rayon fiber is produced from the ripened solution. Viscose is primarily employed in apparels, upholstery fabric, industrial clothing, and medical hygiene. Apparels, upholstery fabric, and industrial clothing segments account for key share of the viscose market. The medical hygiene segment is anticipated to expand during the forecast period. Demand for viscose fiber is anticipated to increase significantly in the near future due to the rise in global population, increase in standard of living, and growth in disposable income. Viscose is an eco-friendly product; thus, increase in awareness about eco-friendly products and decrease in production of cotton are estimated to augment the demand for viscose fiber. Viscose fabric exhibits some similar properties compared to cotton except its poor wet strength due to higher moisture regain. In this study, chemical finishes by different cross-linkers were applied to improve the wet strength of the viscose fabric. For this purpose, water repellent finishes were applied. Water repellent finish helped in reducing the molecular barrier around the individual fibres that lowered the surface tension of the fabric. It reduces the absorbency of viscose fabric hence leads to higher wet strength. Therefore, the treated viscose fabric exhibited better wet strength after applying water repellent finishes on it. Scanning electron microscope (SEM) was used to examine the surface of the fabric treated with chemicals. Tensile strength of viscose was increased 24.6%.

SIP: An Efficient and Secure Information Propagation Scheme in E-Health Networks

Electronic healthcare (e-health) networks are increasingly popular, particular during pandemics such as COVID-19. This reinforces the importance of ensuring security and privacy for data-in-transit. One such solution is steganography-based schemes that utilize biological signals (e.g., ECG) as cover signals to preserve the privacy of patient personal information without affecting the diagnostic features. There are various limitations in existing steganography-based schemes, and in this study we present an effective privacy protection scheme leveraging both multidimensional steganography and shared keys. To enhance security and accelerate signal processing in our design, the Fast Walsh-Hadamard transform (FWHT) is employed to decompose ECG signals into a set of coefficients, of which the less-significant coefficients are used to construct the multidimensional space. The negotiated shared keys facilitate the embedding of encrypted data in the constructed space. We then evaluate the proposed scheme using different categories of ECG signals in the MIT-BIH database. It is observed that the signal distortion is minimal (i.e., less than 1%), even if the embedded data reaches the maximum embedding capacity. The security analysis also demonstrates that unauthorized retrieval of hidden information is not practical, within a short period of time.

Novel multi-party quantum key agreement protocols under collective noise

Based on the logic Bell states, we present two novel multi-party quantum key agreement (QKA) protocols under collective noise. The proposed protocols make full use of four-qubit logic Bell states as quantum resources and perform the novel encoding operation to generate the shared key. The security analysis shows that these two protocols can resist against both participant and outsider attacks. Furthermore, compared with the other existing multi-party QKA protocols over collective noise, our protocols have higher qubit efficiency. Finally, we perform the simulation of the relationship between efficiency and security, which is completely consistent with the conclusion of the security analysis of the protocols.

Nature Inspired Hybrid Algorithm for Binding Shared Key with User Trait

Increased digital transactions accentuate the need for secure communication over open channels. Confidentiality and safe distribution of shared key is a mandatory requirement in symmetric key-based systems. The work proposes a novel nature inspired optimisation technique for binding secret key with user traits extracted from iris biometrics. Validation of key binding is demonstrated by ensuring that successful decryption happens by authorised user alone. Nature inspired swarm and population algorithms are used to extract optimal feature vectors from user trait. Chicken swarm optimisation and deer hunting optimisation algorithms have been used for the first time with iris traits to achieve optimal key binding. Experiments for different shared key lengths have been carried out with IIT Delhi and Multimedia University iris datasets. Accuracy of the proposed model is 7% better than whale optimisation algorithm and 4% better than grey wolf optimisation.

A Secure and Lightweight Three‐Factor Remote User Authentication Protocol for Future IoT Applications

With the booming integration of IoT technology in our daily life applications such as smart industrial, smart city, smart home, smart grid, and healthcare, it is essential to ensure the security and privacy challenges of these systems. Furthermore, time‐critical IoT applications in healthcare require access from external parties (users) to their real‐time private information via wireless communication devices. Therefore, challenges such as user authentication must be addressed in IoT wireless sensor networks (WSNs). In this paper, we propose a secure and lightweight three‐factor (3FA) user authentication protocol based on feature extraction of user biometrics for future IoT WSN applications. The proposed protocol is based on the hash and XOR operations, including (i) a 3‐factor authentication (i.e., smart device, biometrics, and user password); (ii) shared session key; (iii) mutual authentication; and (iv) key freshness. We demonstrate the proposed protocol’s security using the widely accepted Burrows–Abadi–Needham (BAN) logic, Automated Validation of Internet Security Protocols and Applications (AVISPA) simulation tool, and the informal security analysis that demonstrates its other features. In addition, our simulations prove that the proposed protocol is superior to the existing related authentication protocols, in terms of security and functionality features, along with communication and computation overheads. Moreover, the proposed protocol can be utilized efficiently in most of IoT’s WSN applications, such as wireless healthcare sensor networks.

Verifiable Quantum Key Exchange with Authentication

Key exchange is an important primitive protocol to establish and agree a shared session key between two legitimate users over a public channel. In this paper, we first review the parity properties of the characteristics of Bell states via entanglement swapping to form several interesting equations. Then we give a definition of verifiable quantum key exchange with authentication (VQKEA) and present a novel VQKEA protocol based on the parity properties of Bell states via entanglement swapping. Compared with most existing quantum key exchange protocols, our proposed protocol can meet more secure requirements, e.g., authentication, verifiability, fairness and forward secrecy. In addition, it is feasible to implement our proposed protocol with the present quantum processing technologies.

Collusion Attack and Counterattack on the Quantum Key Agreement Via Non-maximally Entangled Cluster States

Recently, Li et al. (Int J Theor Phys: DOI: 10.1007/s10773-020-04588-w, 2020) proposed a multiparty quantum key agreement protocol via non-maximally entangled cluster states. They claimed that the proposed protocol can help all the involved participants have equal influence on the final shared key. However, this study points out a loophole that makes Li et al.'s protocol suffer from a collusion attack, i.e. several dishonest participants can conspire to manipulate the final shared key without being detected by others. To avoid this loophole, an improvement is proposed here.

Provably Secure Symmetric Private Information Retrieval with Quantum Cryptography.

Private information retrieval (PIR) is a database query protocol that provides user privacy in that the user can learn a particular entry of the database of his interest but his query would be hidden from the data centre. Symmetric private information retrieval (SPIR) takes PIR further by additionally offering database privacy, where the user cannot learn any additional entries of the database. Unconditionally secure SPIR solutions with multiple databases are known classically, but are unrealistic because they require long shared secret keys between the parties for secure communication and shared randomness in the protocol. Here, we propose using quantum key distribution (QKD) instead for a practical implementation, which can realise both the secure communication and shared randomness requirements. We prove that QKD maintains the security of the SPIR protocol and that it is also secure against any external eavesdropper. We also show how such a classical-quantum system could be implemented practically, using the example of a two-database SPIR protocol with keys generated by measurement device-independent QKD. Through key rate calculations, we show that such an implementation is feasible at the metropolitan level with current QKD technology.

Anonymous Quantum Conference Key Agreement

Conference Key Agreement (CKA) is a cryptographic effort of multiple parties to establish a shared secret key. In future quantum networks, generating secret keys in an anonymous way is of tremendous importance for parties that want to keep their shared key secret and at the same time protect their own identity. We provide a definition of anonymity for general protocols and present a CKA protocol that is provably anonymous under realistic adversarial scenarios. We base our protocol on shared Greenberger-Horne-Zeilinger states, which have been proposed as more efficient resources for CKA protocols, compared to bipartite entangled resources. The existence of secure and anonymous protocols based on multipartite entangled states provides a new insight on their potential as resources and paves the way for further applications.

Blockchain privacy‐preserving smart contract centric multiplemultipartykey agreement over largeWANETs

AbstractWith the rapid increase in the popularity of groupware applications whose security mainly relied on the key being used, which made multi‐party/group secret key agreements significant. However, the brute‐force attacks to interpret the group key made group communication vulnerable. The logical solution to overcome this is changing the group key frequently. In this direction, we propose blockchain‐based multiple shared keys agreement among a group of participants. As with conventional methods, the proposed protocol does not rely on strong random number generation and/or master key. In this technique, the privacy‐preserving smart contract acts as group controller (GC) and forms two parties with each of the other nodes. The GC, while generating these two‐party keys in the first round instead of exchanging one public key, it exchanges “m” public keys with each of the other nodes and generatesm2shared two‐party keys with each of the respective nodes. Now in the second round, GC generatesm2sequential products of two‐party shared keys and stores them securely as private data objects in the privacy‐preserving smart contract. Next GC computesm2sequential public keys to each of the respective nodes by multiplying these products with the inverse of individual members shared keys sequentially of the group nodes in trusted execution environment and shares them with respective group nodes. On receiving respective public keys, each group node computes the multiple multiparty shared keys by multiplying it with their individual shared keys. Furthermore, an upper limit for the number of shared keys obtained in terms of the number of keys exchanged.

A Novel Machine Learning-Based Approach for Security Analysis of Authentication and Key Agreement Protocols

The application of machine learning in the security analysis of authentication and key agreement protocol was first launched by Ma et al. in 2018. Although they received remarkable results with an accuracy of 72% for the first time, their analysis is limited to replay attack and key confirmation attack. In addition, their suggested framework is based on a multiclassification problem in which every protocol or dataset instance is either secure or prone to a security attack such as replay attack, key confirmation, or other attacks. In this paper, we show that multiclassification is not an appropriate framework for such analysis, since authentication protocols may suffer different attacks simultaneously. Furthermore, we consider more security properties and attacks to analyze protocols against. These properties include strong authentication and Unknown Key Share (UKS) attack, key freshness, key authentication, and password guessing attack. In addition, we propose a much more efficient dataset construction model using a tenth number of features, which improves the solving speed to a large extent. The results indicate that our proposed model outperforms the previous models by at least 10–20 percent in all of the machine learning solving algorithms such that upper-bound performance reaches an accuracy of over 80% in the analysis of all security properties and attacks. Despite the previous models, the classification accuracy of our proposed dataset construction model rises in a rational manner along with the increase of the dataset size.

An efficient quantum identity authentication key agreement protocol without entanglement

Quantum identity authentication key agreement (QIAKA) protocols are designed to allow two nodes to establish a secure secret key when they require few resources, such as a few shared secret bits, and it is technologically feasible. However, the existing studies have two main flaws: they divided quantum identity authentication and key agreement into two realms to research, not integrated them. On the other side, the existing quantum identity authentication has many safety loopholes with inefficiency. In this paper, we firstly devise a quantum identity authentication key agreement protocol without entanglement to improve the efficiency and wipe out any node to know the session key expect the involved parties. In our proposed protocol, through revising the mode and parameters, both the security and efficiency are improved greatly. Furthermore, the short shared secret key is dynamic change at the end of the proposed protocol. Compared with the related literature recently, our proposed scheme can not only own high efficiency and unique functionality, but is also robust to various attacks and the security proof is suitable for the single-state QIAKA protocol.

Optimal Cryptography Scheme and Efficient Neutrosophic C-Means Clustering for Anomaly Detection in Cloud Environment

This paper introduces an efficient and scalable cloud-based privacy preserving model using a new optimal cryptography scheme for anomaly detection in large-scale sensor data. Our proposed privacy preserving model has maintained a better tradeoff between reliability and scalability of the cloud computing resources by means of detecting anomalies from the encrypted data. Conventional data analysis methods have used complex and large numerical computations for the anomaly detection. Also, a single key used by the symmetric key cryptographic scheme to encrypt and decrypt the data has faced large computational complexity because the multiple users can access the original data simultaneously using this single shared secret key. Hence, a classical public key encryption technique called RSA is adopted to perform encryption and decryption of secure data using different key pairs. Furthermore, the random generation of public keys in RSA is controlled in the proposed cloud-based privacy preserving model through optimizing a public key using a new hybrid local pollination-based grey wolf optimizer (LPGWO) algorithm. For ease of convenience, a single private server handling the organization data within a collaborative public cloud data center when requiring the decryption of secure sensor data are allowed to decrypt the optimal secure data using LPGWO-based RSA optimal cryptographic scheme. The data encrypted using an optimal cryptographic scheme are then encouraged to perform data clustering computations in collaborative public servers of cloud platform using Neutrosophic c-Means Clustering (NCM) algorithm. Hence, this NCM algorithm mainly focuses for data partitioning and classification of anomalies. Experimental validation was conducted using four datasets obtained from Intel laboratory having publicly available sensor data. The experimental outcomes have proved the efficiency of the proposed framework in providing data privacy with high anomaly detection accuracy.

Refining image steganography distribution for higher security multimedia counting-based secret-sharing

Counting-based secret sharing is becoming a vital efficient multimedia technique for raising the security of sensitive data especially when collective access to data are essential. Secret sharing distributes shares to participants forcing their joint availability in order to give permission. The share keys of the system deserve to be remembered and highly protected against intruders, presenting a challenging issue, noticing that shares are normally produced without giving participants any preference. Therefore, this research adds image steganography technique to the counting-based secret-sharing system to gain more applicable security. The paper proposes redistribution of LSB image steganography to embed share keys in colour cover image. The proposed method ensured that the shares hiding locations differ within cover images to increase the level of security. The paper analysis show that stego-image quality and security is attractive. It showed interesting results in terms of performance and payload capacity motivating this research to be a direction for coming improvements.

Quantum Key Agreement Via Non-maximally Entangled Cluster States

In this paper, we present a quantum key agreement (QKA) protocol with non-maximally entangled four-qubit cluster states. In our scheme, each participant carries out two unitary operations on the same photons of each cluster state according to its own encryption key. Then, all participants generate identical four-bit shared keys by positive operator-valued measurement (POVM). Since POVM is probabilistic, it is necessary to prepare a longer raw key, and we only select sub-keys in public locations of qubit sequences where all participants succeed in POVMs as the final negotiation key. The advantage of our protocol is that non-maximally entangled cluster states are firstly utilized as the carrier of quantum information in quantum key agreement protocol. It also ensures that the shared key is decided by all participants, not by someone alone. In addition, it is proved that our protocol can resist external attacks and participant attacks, which demonstrates a high security.

A Secure Scheme Based on One-Way Associated Key Management Model in Wireless Sensor Networks

To achieve security in wireless sensor networks (WSNs), it is important to be able to encrypt messages sent among sensor nodes by using shared keys between them. Due to resource constraints, achieving such key agreement in WSNs is nontrivial. Previous research indicates that key management schemes using deployment knowledge can significantly improve the performance of WSNs. Nevertheless, in these schemes, resilient local connectivity and resilient global connectivity become unstable when deployment error changes. To resolve the above problem, in this article, a one-way associated key management model is proposed. In this model, the key pool consists of two layers: 1) the global layer and 2) the local layer. According to different deployment errors, the number of keys allocated from the global key pool and local key pools can be dynamically adjusted, thereby improving the stability of networks' performance. In multiphase sensor networks, analysis and simulation indicate that our scheme has better adaptability in applications where deployment error changes as compared with related schemes.

Analysis of achievable distances of BB84 and KMB09 QKD protocols

Quantum key distribution (QKD) is a proven secured way to transmit shared secret keys using quantum particles. Any adversarial attempt to intercept and eavesdrop secret key results in generating errors alerting the legitimate users. Since QKD is constrained by quantum mechanics principles, the practical transmission of the key at a greater distance is an issue. In this paper, we discover and analyze the key factors associated with transmission media, hardware components and protocol implementation of the QKD system that causes hindrance in distance range. Practical implementation of BB84 and KMB09 protocols is discussed to determine the achievable distance given current technology. We find that by using ultra low loss fiber, short-pulse laser and superconducting nanowire single photon detector the maximum achievable distance for both of the quantum protocols is 250[Formula: see text]km.

Extended visual cryptography-based copyright protection scheme for multiple images and owners using LBP–SURF descriptors

Existing visual cryptography (VC)-based copyright protection schemes (Amiri and Mohaddam in Multimed Tools Appl 75(14):8527–8543, 2016; Liu and Wu in IET Inf Secur 5(2):121–128, 2011) for multiple images provide meaningless shares to the owners. These shares create a suspicion that some secret information is shared. Also, these schemes require the share of every owner to prove the copyright. If any of the ownership share is not available, the copyright of these owners cannot be verified. This makes the usage of schemes restricted. To address these issues, an extended visual cryptography-based copyright protection scheme is proposed for multiple images with multiple owners. This scheme provides meaningful ownership shares to the owners, and their copyright can be verified by using a qualified set of owner shares. In this scheme, three types of shares are used, i.e., master share, ownership share and key share. The proposed scheme ensures robustness against different geometrical attacks, especially the rotation attack, as LBP and SURF together represent the host image efficiently. There is no restriction on watermark size, as SURF gives a flexibility to select any number of feature points. Usage of LBP ensures no false positive cases. Each of the ownership shares is created using the master share and the watermark. The ownership share is used to create a key share which is stored with the Trusting Authority (TA). To prove the copyright of multiple images, the ownership images and key share are superimposed to retrieve the watermark. The experimental results show that the scheme clearly verifies the copyright of digital images and is robust against several image processing attacks while having high imperceptibility. Comparisons with the existing copyright protection schemes show better performance of the proposed scheme.