An Efficient Three-Party Authenticated Key Exchange Procedure Using Chebyshev Chaotic Maps with Client Anonymity

Internet of Things(IoT)applications can be found in various industry areas,including critical infrastructure and healthcare,and IoT is one of several technological developments.As a result,tens of billions or possibly hundreds of billions of devices will be linked together.These smart devices will be able to gather data,process it,and even come to decisions on their own.Security is the most essential thing in these situations.In IoT infrastructure,authenticated key exchange systems are crucial for preserving client and data privacy and guaranteeing the security of data-in-transit(e.g.,via client identification and provision of secure communication).It is still challenging to create secure,authenticated key exchange techniques.The majority of the early authenticated key agreement procedure depended on computationally expensive and resource-intensive pairing,hashing,or modular exponentiation processes.The focus of this paper is to propose an efficient three-party authenticated key exchange procedure(AKEP)using Chebyshev chaotic maps with client anonymity that solves all the problems mentioned above.The proposed three-party AKEP is protected from several attacks.The proposed three-party AKEP can be used in practice for mobile communications and pervasive computing applications,according to statistical experiments and low processing costs.To protect client identification when transferring data over an insecure public network,our three-party AKEP may also offer client anonymity.Finally,the presented procedure offers better security features than the procedures currently available in the literature.

Generalized synchronization between different chaotic maps via dead-beat control

This paper presents a new scheme to achieve generalized synchronization（GS） between different discrete-time chaotic（hyperchaotic） systems.The approach is based on a theorem,which assures that GS is achieved when a structural condition on the considered class of response systems is satisfied.The method presents some useful features：it enables exact GS to be achieved in finite time（i.e.,dead-beat synchronization）;it is rigorous,systematic,and straightforward in checking GS;it can be applied to a wide class of chaotic maps.Some examples of GS,including the Grassi-Miller map and a recently introduced minimal 2-D quadratic map,are illustrated.

Chaotic maps and biometrics-based anonymous three-party authenticated key exchange protocol without using passwords

In three-party password authenticated key exchange （AKE） protocol, since two users use their passwords to establish a secure session key over an insecure communication channel with the help of the trusted server, such a protocol may suffer the password guessing attacks and the server has to maintain the password table. To eliminate the shortages of password- based AKE protocol, very recently, according to chaotic maps, Lee et al. [2015 Nonlinear Dyn. 79 2485] proposed a first three-party-authenticated key exchange scheme without using passwords, and claimed its security by providing a well- organized BAN logic test. Unfortunately, their protocol cannot resist impersonation attack, which is demonstrated in the present paper. To overcome their security weakness, by using chaotic maps, we propose a biometrics-based anonymous three-party AKE protocol with the same advantages. Further, we use the pi calculus-based formal verification tool ProVerif to show that our AKE protocol achieves authentication, security and anonymity, and an acceptable efficiency.

An efficient three-party password-based key agreement protocol using extended chaotic maps

Three-party password-based key agreement protocols allow two users to authenticate each other via a public channel and establish a session key with the aid of a trusted server. Recently, Farash et al. [Farash M S, Attari M A 2014 ＂An efficient and provably secure three-party password-based authenticated key exchange protocol based on Chebyshev chaotic maps＂, Nonlinear Dynamics 77（7）： 399-411] proposed a three-party key agreement protocol by using the extended chaotic maps. They claimed that their protocol could achieve strong security. In the present paper, we analyze Farash et al.＇s protocol and point out that this protocol is vulnerable to off-line password guessing attack and suffers communication burden. To handle the issue, we propose an efficient three-party password-based key agreement protocol using extended chaotic maps, which uses neither symmetric cryptosystems nor the server＇s public key. Compared with the relevant schemes, our protocol provides better performance in terms of computation and communication. Therefore, it is suitable for practical applications.

SBOOSP for Massive Devices in 5G WSNs Using Conformable Chaotic Maps

The commercialization of the fifth-generation(5G)wireless network has begun.Massive devices are being integrated into 5G-enabled wireless sensor networks(5GWSNs)to deliver a variety of valuable services to network users.However,there are rising fears that 5GWSNs will expose sensitive user data to new security vulnerabilities.For secure end-to-end communication,key agreement and user authentication have been proposed.However,when billions of massive devices are networked to collect and analyze complex user data,more stringent security approaches are required.Data integrity,nonrepudiation,and authentication necessitate special-purpose subtree-based signature mechanisms that are pretty difficult to create in practice.To address this issue,this work provides an efficient,provably secure,lightweight subtreebased online/offline signature procedure(SBOOSP)and its aggregation(Agg-SBOOSP)for massive devices in 5G WSNs using conformable chaotic maps.The SBOOSP enables multi-time offline storage access while reducing processing time.As a result,the signer can utilize the pre-stored offline information in polynomial time.This feature distinguishes our presented SBOOSP from previous online/offline-signing procedures that only allow for one signature.Furthermore,the new procedure supports a secret key during the pre-registration process,but no secret key is necessary during the offline stage.The suggested SBOOSP is secure in the logic of unforgeability on the chosen message attack in the random oracle.Additionally,SBOOSP and Agg-SBOOSP had the lowest computing costs compared to other contending schemes.Overall,the suggested SBOOSP outperforms several preliminary security schemes in terms of performance and computational overhead.

Inverse full state hybrid projective synchronization for chaotic maps with different dimensions

A new synchronization scheme for chaotic（hyperchaotic） maps with different dimensions is presented.Specifically,given a drive system map with dimension n and a response system with dimension m,the proposed approach enables each drive system state to be synchronized with a linear response combination of the response system states.The method,based on the Lyapunov stability theory and the pole placement technique,presents some useful features：（i） it enables synchronization to be achieved for both cases of n 〈 m and n 〉 m;（ii） it is rigorous,being based on theorems;（iii） it can be readily applied to any chaotic（hyperchaotic） maps defined to date.Finally,the capability of the approach is illustrated by synchronization examples between the two-dimensional H′enon map（as the drive system） and the three-dimensional hyperchaotic Wang map（as the response system）,and the three-dimensional H′enon-like map（as the drive system） and the two-dimensional Lorenz discrete-time system（as the response system）.

Chaotic Map-Based Authentication and Key Agreement Protocol with Low-Latency for Metasystem

With the rapid advancement in exploring perceptual interactions and digital twins,metaverse technology has emerged to transcend the constraints of space-time and reality,facilitating remote AI-based collaboration.In this dynamic metasystem environment,frequent information exchanges necessitate robust security measures,with Authentication and Key Agreement(AKA)serving as the primary line of defense to ensure communication security.However,traditional AKA protocols fall short in meeting the low-latency requirements essential for synchronous interactions within the metaverse.To address this challenge and enable nearly latency-free interactions,a novel low-latency AKA protocol based on chaotic maps is proposed.This protocol not only ensures mutual authentication of entities within the metasystem but also generates secure session keys.The security of these session keys is rigorously validated through formal proofs,formal verification,and informal proofs.When confronted with the Dolev-Yao(DY)threat model,the session keys are formally demonstrated to be secure under the Real-or-Random(ROR)model.The proposed protocol is further validated through simulations conducted using VMware workstation compiled in HLPSL language and C language.The simulation results affirm the protocol’s effectiveness in resisting well-known attacks while achieving the desired low latency for optimal metaverse interactions.

Intrusion Detection Model Using Chaotic MAP for Network Coding Enabled Mobile Small Cells

Wireless Network security management is difficult because of the ever-increasing number of wireless network malfunctions,vulnerabilities,and assaults.Complex security systems,such as Intrusion Detection Systems(IDS),are essential due to the limitations of simpler security measures,such as cryptography and firewalls.Due to their compact nature and low energy reserves,wireless networks present a significant challenge for security procedures.The features of small cells can cause threats to the network.Network Coding(NC)enabled small cells are vulnerable to various types of attacks.Avoiding attacks and performing secure“peer”to“peer”data transmission is a challenging task in small cells.Due to the low power and memory requirements of the proposed model,it is well suited to use with constrained small cells.An attacker cannot change the contents of data and generate a new Hashed Homomorphic Message Authentication Code(HHMAC)hash between transmissions since the HMAC function is generated using the shared secret.In this research,a chaotic sequence mapping based low overhead 1D Improved Logistic Map is used to secure“peer”to“peer”data transmission model using lightweight H-MAC(1D-LM-P2P-LHHMAC)is proposed with accurate intrusion detection.The proposed model is evaluated with the traditional models by considering various evaluation metrics like Vector Set Generation Accuracy Levels,Key Pair Generation Time Levels,Chaotic Map Accuracy Levels,Intrusion Detection Accuracy Levels,and the results represent that the proposed model performance in chaotic map accuracy level is 98%and intrusion detection is 98.2%.The proposed model is compared with the traditional models and the results represent that the proposed model secure data transmission levels are high.

Securing 3D Point and Mesh Fog Data Using Novel Chaotic Cat Map

With the rapid evolution of Internet technology,fog computing has taken a major role in managing large amounts of data.The major concerns in this domain are security and privacy.Therefore,attaining a reliable level of confidentiality in the fog computing environment is a pivotal task.Among different types of data stored in the fog,the 3D point and mesh fog data are increasingly popular in recent days,due to the growth of 3D modelling and 3D printing technologies.Hence,in this research,we propose a novel scheme for preserving the privacy of 3D point and mesh fog data.Chaotic Cat mapbased data encryption is a recently trending research area due to its unique properties like pseudo-randomness,deterministic nature,sensitivity to initial conditions,ergodicity,etc.To boost encryption efficiency significantly,in this work,we propose a novel Chaotic Cat map.The sequence generated by this map is used to transform the coordinates of the fog data.The improved range of the proposed map is depicted using bifurcation analysis.The quality of the proposed Chaotic Cat map is also analyzed using metrics like Lyapunov exponent and approximate entropy.We also demonstrate the performance of the proposed encryption framework using attacks like brute-force attack and statistical attack.The experimental results clearly depict that the proposed framework produces the best results compared to the previous works in the literature.

Security analysis of image encryption based on twodimensional chaotic maps and improved algorithm

The article proposes a new algorithm to improve the security of image encryption based on twodimensional chaotic maps.Chaotic maps are often used in encrypting images.However,the encryption has periodicity,no diffusion,and at the same time,the real keys space of encryption are fewer than the theoretical keys space,which consequently results in potential security problems.Thus,this article puts forward several ways to solve the problems including adding diffusion mechanism,changing the design of keys and developing a composite encryption system.It designs an algorithm for the version B of the discretized baker map,which is one of the most prevalent chaotic maps,based on which a new image encryption is proposed to avoid the above problems.The simulation results show that the new encryption algorithm is valid and the result can be applied to other two-dimensional chaotic maps,such as the cat map.

Asymmetric image encryption algorithm based on a new three-dimensional improved logistic chaotic map

Based on some analyses of existing chaotic image encryption frameworks and a new designed three-dimensional improved logistic chaotic map(3D-ILM),an asymmetric image encryption algorithm using public-key Rivest–Shamir–Adleman(RSA)is presented in this paper.In the first stage,a new 3D-ILM is proposed to enhance the chaotic behavior considering analysis of time sequence,Lyapunov exponent,and Shannon entropy.In the second stage,combined with the public key RSA algorithm,a new key acquisition mathematical model(MKA)is constructed to obtain the initial keys for the 3D-ILM.Consequently,the key stream can be produced depending on the plain image for a higher security.Moreover,a novel process model(NPM)for the input of the 3D-ILM is built,which is built to improve the distribution uniformity of the chaotic sequence.In the third stage,to encrypt the plain image,a pre-process by exclusive OR(XOR)operation with a random matrix is applied.Then,the pre-processed image is performed by a permutation for rows,a downward modulo function for adjacent pixels,a permutation for columns,a forward direction XOR addition-modulo diffusion,and a backward direction XOR addition-modulo diffusion to achieve the final cipher image.Moreover,experiments show that the the proposed algorithm has a better performance.Especially,the number of pixels change rate(NPCR)is close to ideal case 99.6094%,with the unified average changing intensity(UACI)close to 33.4634%,and the information entropy(IE)close to 8.

Dynamic S-Box Generation Using Novel Chaotic Map with Nonlinearity Tweaking

A substitution box(S-Box)is a crucial component of contemporary cryptosystems that provide data protection in block ciphers.At the moment,chaotic maps are being created and extensively used to generate these SBoxes as a chaotic map assists in providing disorder and resistance to combat cryptanalytical attempts.In this paper,the construction of a dynamic S-Box using a cipher key is proposed using a novel chaotic map and an innovative tweaking approach.The projected chaotic map and the proposed tweak approach are presented for the first time and the use of parameters in their workingmakes both of these dynamic in nature.The tweak approach employs cubic polynomials while permuting the values of an initial S-Box to enhance its cryptographic fort.Values of the parameters are provided using the cipher key and a small variation in values of these parameters results in a completely different unique S-Box.Comparative analysis and exploration confirmed that the projected chaoticmap exhibits a significant amount of chaotic complexity.The security assessment in terms of bijectivity,nonlinearity,bits independence,strict avalanche,linear approximation probability,and differential probability criteria are utilized to critically investigate the effectiveness of the proposed S-Box against several assaults.The proposed S-Box’s cryptographic performance is comparable to those of recently projected S-Boxes for its adaption in real-world security applications.The comparative scrutiny pacifies the genuine potential of the proposed S-Box in terms of its applicability for data security.

VLSI Implementation of Optimized 2D SIMM Chaotic Map for Image Encryption

The current research work proposed a novel optimization-based 2D-SIMM(Two-Dimensional Sine Iterative chaotic map with infinite collapse Mod-ulation Map)model for image encryption.The proposed 2D-SIMM model is derived out of sine map and Iterative Chaotic Map with Infinite Collapse(ICMIC).In this technique,scrambling effect is achieved with the help of Chaotic Shift Transform(CST).Chaotic Shift Transform is used to change the value of pixels in the input image while the substituted value is cyclically shifted according to the chaotic sequence generated by 2D-SIMM model.These chaotic sequences,generated using 2D-SIMM model,are sensitive to initial conditions.In the proposed algorithm,these initial conditions are optimized using JAYA optimization algorithm.Correlation coefficient and entropy are considered asfitness functions in this study to evaluate the best solution for initial conditions.The simulation results clearly shows that the proposed algorithm achieved a better performance over existing algorithms.In addition,the VLSI implementation of the proposed algorithm was also carried out using Xilinx system generator.With optimization,the correlation coefficient was-0.014096 and without optimization,it was 0.002585.

Applying and Comparison of Chaotic-Based Permutation Algorithms for Audio Encryption

This research presents,and claries the application of two permutation algorithms,based on chaotic map systems,and applied to a le of speech signals.They are the Arnold cat map-based permutation algorithm,and the Baker’s chaotic map-based permutation algorithm.Both algorithms are implemented on the same speech signal sample.Then,both the premier and the encrypted le histograms are documented and plotted.The speech signal amplitude values with time signals of the original le are recorded and plotted against the encrypted and decrypted les.Furthermore,the original le is plotted against the encrypted le,using the spectrogram frequencies of speech signals with the signal duration.These permutation algorithms are used to shufe the positions of the speech les signals’values without any changes,to produce an encrypted speech le.A comparative analysis is introduced by using some of sundry statistical and experimental analyses for the procedures of encryption and decryption,e.g.,the time of both procedures,the encrypted audio signals histogram,the correlation coefcient between specimens in the premier and encrypted signals,a test of the Spectral Distortion(SD),and the Log-Likelihood Ratio(LLR)measures.The outcomes of the different experimental and comparative studies demonstrate that the two permutation algorithms(Baker and Arnold)are sufcient for providing an efcient and reliable voice signal encryption solution.However,the Arnold’s algorithm gives better results in most cases as compared to the results of Baker’s algorithm.

A Multi-Strategy-Improved Northern Goshawk Optimization Algorithm for Global Optimization and Engineering Design

Optimization algorithms play a pivotal role in enhancing the performance and efficiency of systems across various scientific and engineering disciplines.To enhance the performance and alleviate the limitations of the Northern Goshawk Optimization(NGO)algorithm,particularly its tendency towards premature convergence and entrapment in local optima during function optimization processes,this study introduces an advanced Improved Northern Goshawk Optimization(INGO)algorithm.This algorithm incorporates a multifaceted enhancement strategy to boost operational efficiency.Initially,a tent chaotic map is employed in the initialization phase to generate a diverse initial population,providing high-quality feasible solutions.Subsequently,after the first phase of the NGO’s iterative process,a whale fall strategy is introduced to prevent premature convergence into local optima.This is followed by the integration of T-distributionmutation strategies and the State Transition Algorithm(STA)after the second phase of the NGO,achieving a balanced synergy between the algorithm’s exploitation and exploration.This research evaluates the performance of INGO using 23 benchmark functions alongside the IEEE CEC 2017 benchmark functions,accompanied by a statistical analysis of the results.The experimental outcomes demonstrate INGO’s superior achievements in function optimization tasks.Furthermore,its applicability in solving engineering design problems was verified through simulations on Unmanned Aerial Vehicle(UAV)trajectory planning issues,establishing INGO’s capability in addressing complex optimization challenges.

Prediction Model of Wax Deposition Rate in Waxy Crude Oil Pipelines by Elman Neural Network Based on Improved Reptile Search Algorithm

A hard problem that hinders the movement of waxy crude oil is wax deposition in oil pipelines.To ensure the safe operation of crude oil pipelines,an accurate model must be developed to predict the rate of wax deposition in crude oil pipelines.Aiming at the shortcomings of the ENN prediction model,which easily falls into the local minimum value and weak generalization ability in the implementation process,an optimized ENN prediction model based on the IRSA is proposed.The validity of the new model was confirmed by the accurate prediction of two sets of experimental data on wax deposition in crude oil pipelines.The two groups of crude oil wax deposition rate case prediction results showed that the average absolute percentage errors of IRSA-ENN prediction models is 0.5476% and 0.7831%,respectively.Additionally,it shows a higher prediction accuracy compared to the ENN prediction model.In fact,the new model established by using the IRSA to optimize ENN can optimize the initial weights and thresholds in the prediction process,which can overcome the shortcomings of the ENN prediction model,such as weak generalization ability and tendency to fall into the local minimum value,so that it has the advantages of strong implementation and high prediction accuracy.

Multi-objective optimization design of anti-roll torsion bar using improved beluga whale optimization algorithm

Purpose – This study aims to reduce the redundant weight of the anti-roll torsion bar brought by thetraditional empirical design and improving its strength and stiffness.Design/methodology/approach – Based on the finite element approach coupled with the improved belugawhale optimization (IBWO) algorithm, a collaborative optimization method is suggested to optimize the designof the anti-roll torsion bar structure and weight. The dimensions and material properties of the torsion bar weredefined as random variables, and the torsion bar’s mass and strength were investigated using finite elements.Then, chaotic mapping and differential evolution (DE) operators are introduced to improve the beluga whaleoptimization (BWO) algorithm and run case studies.Findings – The findings demonstrate that the IBWO has superior solution set distribution uniformity,convergence speed, solution correctness and stability than the BWO. The IBWO algorithm is used to optimizethe anti-roll torsion bar design. The error between the optimization and finite element simulation results wasless than 1%. The weight of the optimized anti-roll torsion bar was lessened by 4%, the maximum stress wasreduced by 35% and the stiffness was increased by 1.9%.Originality/value – The study provides a methodological reference for the simulation optimization process ofthe lateral anti-roll torsion bar.

Prediction on Failure Pressure of Pipeline Containing Corrosion Defects Based on ISSA-BPNNModel

Oil and gas pipelines are affected by many factors,such as pipe wall thinning and pipeline rupture.Accurate prediction of failure pressure of oil and gas pipelines can provide technical support for pipeline safety management.Aiming at the shortcomings of the BP Neural Network(BPNN)model,such as low learning efficiency,sensitivity to initial weights,and easy falling into a local optimal state,an Improved Sparrow Search Algorithm(ISSA)is adopted to optimize the initial weights and thresholds of BPNN,and an ISSA-BPNN failure pressure prediction model for corroded pipelines is established.Taking 61 sets of pipelines blasting test data as an example,the prediction model was built and predicted by MATLAB software,and compared with the BPNN model,GA-BPNN model,and SSA-BPNN model.The results show that the MAPE of the ISSA-BPNN model is 3.4177%,and the R2 is 0.9880,both of which are superior to its comparison model.Using the ISSA-BPNN model has high prediction accuracy and stability,and can provide support for pipeline inspection and maintenance.

An Improved Harris Hawk Optimization Algorithm

Aiming at the problems that the original Harris Hawk optimization algorithm is easy to fall into local optimum and slow in finding the optimum,this paper proposes an improved Harris Hawk optimization algorithm(GHHO).Firstly,we used a Gaussian chaotic mapping strategy to initialize the positions of individuals in the population,which enriches the initial individual species characteristics.Secondly,by optimizing the energy parameter and introducing the cosine strategy,the algorithm's ability to jump out of the local optimum is enhanced,which improves the performance of the algorithm.Finally,comparison experiments with other intelligent algorithms were conducted on 13 classical test function sets.The results show that GHHO has better performance in all aspects compared to other optimization algorithms.The improved algorithm is more suitable for generalization to real optimization problems.

Digital image encryption with chaotic map lattices

This paper proposes a secure approach for encryption and decryption of digital images with chaotic map lattices. In the proposed encryption process, eight different types of operations are used to encrypt the pixels of an image and one of them will be used for particular pixels decided by the outcome of the chaotic map lattices. To make the cipher more robust against any attacks, the secret key is modified after encrypting each block of sixteen pixels of the image. The experimental results and security analysis show that the proposed image encryption scheme achieves high security and efficiency.