Privacy Enhanced Mobile User Authentication Method Using Motion Sensors

With the development of hardware devices and the upgrading of smartphones,a large number of users save privacy-related information in mobile devices,mainly smartphones,which puts forward higher demands on the protection of mobile users’privacy information.At present,mobile user authenticationmethods based on humancomputer interaction have been extensively studied due to their advantages of high precision and non-perception,but there are still shortcomings such as low data collection efficiency,untrustworthy participating nodes,and lack of practicability.To this end,this paper proposes a privacy-enhanced mobile user authentication method with motion sensors,which mainly includes:(1)Construct a smart contract-based private chain and federated learning to improve the data collection efficiency of mobile user authentication,reduce the probability of the model being bypassed by attackers,and reduce the overhead of data centralized processing and the risk of privacy leakage;(2)Use certificateless encryption to realize the authentication of the device to ensure the credibility of the client nodes participating in the calculation;(3)Combine Variational Mode Decomposition(VMD)and Long Short-TermMemory(LSTM)to analyze and model the motion sensor data of mobile devices to improve the accuracy of model certification.The experimental results on the real environment dataset of 1513 people show that themethod proposed in this paper can effectively resist poisoning attacks while ensuring the accuracy and efficiency of mobile user authentication.

Internet of Things Authentication Protocols: Comparative Study

Nowadays, devices are connected across all areas, from intelligent buildings and smart cities to Industry 4.0 andsmart healthcare. With the exponential growth of Internet of Things usage in our world, IoT security is still thebiggest challenge for its deployment. The main goal of IoT security is to ensure the accessibility of services providedby an IoT environment, protect privacy, and confidentiality, and guarantee the safety of IoT users, infrastructures,data, and devices. Authentication, as the first line of defense against security threats, becomes the priority ofeveryone. It can either grant or deny users access to resources according to their legitimacy. As a result, studyingand researching authentication issues within IoT is extremely important. As a result, studying and researchingauthentication issues within IoT is extremely important. This article presents a comparative study of recent researchin IoT security;it provides an analysis of recent authentication protocols from2019 to 2023 that cover several areaswithin IoT (such as smart cities, healthcare, and industry). This survey sought to provide an IoT security researchsummary, the biggest susceptibilities, and attacks, the appropriate technologies, and the most used simulators. Itillustrates that the resistance of protocols against attacks, and their computational and communication cost arelinked directly to the cryptography technique used to build it. Furthermore, it discusses the gaps in recent schemesand provides some future research directions.

Correlation Composition AwarenessModel with Pair CollaborativeLocalization for IoT Authentication and Localization

Secure authentication and accurate localization among Internet of Things(IoT)sensors are pivotal for the functionality and integrity of IoT networks.IoT authentication and localization are intricate and symbiotic,impacting both the security and operational functionality of IoT systems.Hence,accurate localization and lightweight authentication on resource-constrained IoT devices pose several challenges.To overcome these challenges,recent approaches have used encryption techniques with well-known key infrastructures.However,these methods are inefficient due to the increasing number of data breaches in their localization approaches.This proposed research efficiently integrates authentication and localization processes in such a way that they complement each other without compromising on security or accuracy.The proposed framework aims to detect active attacks within IoT networks,precisely localize malicious IoT devices participating in these attacks,and establish dynamic implicit authentication mechanisms.This integrated framework proposes a Correlation Composition Awareness(CCA)model,which explores innovative approaches to device correlations,enhancing the accuracy of attack detection and localization.Additionally,this framework introduces the Pair Collaborative Localization(PCL)technique,facilitating precise identification of the exact locations of malicious IoT devices.To address device authentication,a Behavior and Performance Measurement(BPM)scheme is developed,ensuring that only trusted devices gain access to the network.This work has been evaluated across various environments and compared against existing models.The results prove that the proposed methodology attains 96%attack detection accuracy,84%localization accuracy,and 98%device authentication accuracy.

Recent Developments in Authentication Schemes Used in Machine-Type Communication Devices in Machine-to-Machine Communication: Issues and Challenges

Machine-to-machine (M2M) communication plays a fundamental role in autonomous IoT (Internet of Things)-based infrastructure, a vital part of the fourth industrial revolution. Machine-type communication devices(MTCDs) regularly share extensive data without human intervention while making all types of decisions. Thesedecisions may involve controlling sensitive ventilation systems maintaining uniform temperature, live heartbeatmonitoring, and several different alert systems. Many of these devices simultaneously share data to form anautomated system. The data shared between machine-type communication devices (MTCDs) is prone to risk dueto limited computational power, internal memory, and energy capacity. Therefore, securing the data and devicesbecomes challenging due to factors such as dynamic operational environments, remoteness, harsh conditions,and areas where human physical access is difficult. One of the crucial parts of securing MTCDs and data isauthentication, where each devicemust be verified before data transmission. SeveralM2Mauthentication schemeshave been proposed in the literature, however, the literature lacks a comprehensive overview of current M2Mauthentication techniques and the challenges associated with them. To utilize a suitable authentication schemefor specific scenarios, it is important to understand the challenges associated with it. Therefore, this article fillsthis gap by reviewing the state-of-the-art research on authentication schemes in MTCDs specifically concerningapplication categories, security provisions, and performance efficiency.

A Post-Quantum Cross-Domain Authentication Scheme Based on Multi-Chain Architecture

Due to the rapid advancements in network technology,blockchain is being employed for distributed data storage.In the Internet of Things(IoT)scenario,different participants manage multiple blockchains located in different trust domains,which has resulted in the extensive development of cross-domain authentication techniques.However,the emergence of many attackers equipped with quantum computers has the potential to launch quantum computing attacks against cross-domain authentication schemes based on traditional cryptography,posing a significant security threat.In response to the aforementioned challenges,our paper demonstrates a post-quantum cross-domain identity authentication scheme to negotiate the session key used in the cross-chain asset exchange process.Firstly,our paper designs the hiding and recovery process of user identity index based on lattice cryptography and introduces the identity-based signature from lattice to construct a post-quantum cross-domain authentication scheme.Secondly,our paper utilizes the hashed time-locked contract to achieves the cross-chain asset exchange of blockchain nodes in different trust domains.Furthermore,the security analysis reduces the security of the identity index and signature to Learning With Errors(LWE)and Short Integer Solution(SIS)assumption,respectively,indicating that our scheme has post-quantum security.Last but not least,through comparison analysis,we display that our scheme is efficient compared with the cross-domain authentication scheme based on traditional cryptography.

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.

Joint Authentication Public Network Cryptographic Key Distribution Protocol Based on Single Exposure Compressive Ghost Imaging

In the existing ghost-imaging-based cryptographic key distribution(GCKD)protocols,the cryptographic keys need to be encoded by using many modulated patterns,which undoubtedly incurs long measurement time and huge memory consumption.Given this,based on snapshot compressive ghost imaging,a public network cryptographic key distribution protocol is proposed,where the cryptographic keys and joint authentication information are encrypted into several color block diagrams to guarantee security.It transforms the previous single-pixel sequential multiple measurements into multi-pixel single exposure measurements,significantly reducing sampling time and memory storage.Both simulation and experimental results demonstrate the feasibility of this protocol and its ability to detect illegal attacks.Therefore,it takes GCKD a big step closer to practical applications.

A Hybrid and Lightweight Device-to-Server Authentication Technique for the Internet of Things

The Internet of Things(IoT)is a smart networking infrastructure of physical devices,i.e.,things,that are embedded with sensors,actuators,software,and other technologies,to connect and share data with the respective server module.Although IoTs are cornerstones in different application domains,the device’s authenticity,i.e.,of server(s)and ordinary devices,is the most crucial issue and must be resolved on a priority basis.Therefore,various field-proven methodologies were presented to streamline the verification process of the communicating devices;however,location-aware authentication has not been reported as per our knowledge,which is a crucial metric,especially in scenarios where devices are mobile.This paper presents a lightweight and location-aware device-to-server authentication technique where the device’s membership with the nearest server is subjected to its location information along with other measures.Initially,Media Access Control(MAC)address and Advance Encryption Scheme(AES)along with a secret shared key,i.e.,λ_(i) of 128 bits,have been utilized by Trusted Authority(TA)to generate MaskIDs,which are used instead of the original ID,for every device,i.e.,server and member,and are shared in the offline phase.Secondly,TA shares a list of authentic devices,i.e.,server S_(j) and members C_(i),with every device in the IoT for the onward verification process,which is required to be executed before the initialization of the actual communication process.Additionally,every device should be located such that it lies within the coverage area of a server,and this location information is used in the authentication process.A thorough analytical analysis was carried out to check the susceptibility of the proposed and existing authentication approaches against well-known intruder attacks,i.e.,man-in-the-middle,masquerading,device,and server impersonations,etc.,especially in the IoT domain.Moreover,proposed authentication and existing state-of-the-art approaches have been simulated in the real environment of IoT to verify their performance,particularly in terms of various evaluation metrics,i.e.,processing,communication,and storage overheads.These results have verified the superiority of the proposed scheme against existing state-of-the-art approaches,preferably in terms of communication,storage,and processing costs.

Efficient Authentication Scheme for UAV-Assisted Mobile Edge Computing

Preserving privacy is imperative in the new unmanned aerial vehicle(UAV)-assisted mobile edge computing(MEC)architecture to ensure that sensitive information is protected and kept secure throughout the communication.Simultaneously,efficiency must be considered while developing such a privacy-preserving scheme because the devices involved in these architectures are resource constrained.This study proposes a lightweight and efficient authentication scheme for theUAV-assistedMECenvironment.The proposed scheme is a hardware-based password-less authentication mechanism that is based on the fact that temporal and memory-related efficiency can be significantly improved while maintaining the data security by adopting a hardwarebased solution with a simple implementation.The proposed scheme works in four stages:system initialization,EU registration,EU authentication,and session establishment.It is implemented as a single hardware chip comprising registers and XOR gates,and it can run the entire process in one clock cycle.Consequently,the proposed scheme has significantly higher efficiency in terms of runtime and memory consumption compared to other prevalent methods in the area.Simulations are conducted to evaluate the proposed authentication algorithm.The results show that the scheme has an average execution time of 0.986 ms and consumes average memory of 34 KB.The hardware execution time is approximately 0.39 ns,which is a significantly less than the prevalent schemes,whose execution times range in milliseconds.Furthermore,the security of the proposed scheme is examined,and it is resistant to brute-force attacks.Around 1.158×10^(77) trials are required to overcome the system’s security,which is not feasible using fastest available processors.

Grey Wolf-Based Method for an Implicit Authentication of Smartphone Users

Smartphones have now become an integral part of our everyday lives.User authentication on smartphones is often accomplished by mechanisms(like face unlock,pattern,or pin password)that authenticate the user’s identity.These technologies are simple,inexpensive,and fast for repeated logins.However,these technologies are still subject to assaults like smudge assaults and shoulder surfing.Users’touch behavior while using their cell phones might be used to authenticate them,which would solve the problem.The performance of the authentication process may be influenced by the attributes chosen(from these behaviors).The purpose of this study is to present an effective authentication technique that implicitly offers a better authentication method for smartphone usage while avoiding the cost of a particular device and considering the constrained capabilities of smartphones.We began by concentrating on feature selection methods utilizing the grey wolf optimization strategy.The random forest classifier is used to evaluate these tactics.The testing findings demonstrated that the grey wolf-based methodology works as a better optimum feature selection for building an implicit authentication mechanism for the smartphone environment when using a public dataset.It achieved a 97.89%accuracy rate while utilizing just 16 of the 53 characteristics like utilizing minimum mobile resources mainly;processing power of the device and memory to validate individuals.Simultaneously,the findings revealed that our approach has a lower equal error rate(EER)of 0.5104,a false acceptance rate(FAR)of 1.00,and a false rejection rate(FRR)of 0.0209 compared to the methods discussed in the literature.These promising results will be used to create a mobile application that enables implicit validation of authorized users yet avoids current identification concerns and requires fewer mobile resources.

Identity-Based Edge Computing Anonymous Authentication Protocol

With the development of sensor technology and wireless communication technology,edge computing has a wider range of applications.The privacy protection of edge computing is of great significance.In the edge computing system,in order to ensure the credibility of the source of terminal data,mobile edge computing(MEC)needs to verify the signature of the terminal node on the data.During the signature process,the computing power of edge devices such as wireless terminals can easily become the bottleneck of system performance.Therefore,it is very necessary to improve efficiency through computational offloading.Therefore,this paper proposes an identitybased edge computing anonymous authentication protocol.The protocol realizes mutual authentication and obtains a shared key by encrypting the mutual information.The encryption algorithm is implemented through a thresholded identity-based proxy ring signature.When a large number of terminals offload computing,MEC can set the priority of offloading tasks according to the user’s identity and permissions,thereby improving offloading efficiency.Security analysis shows that the scheme can guarantee the anonymity and unforgeability of signatures.The probability of a malicious node forging a signature is equivalent to cracking the discrete logarithm puzzle.According to the efficiency analysis,in the case of MEC offloading,the computational complexity is significantly reduced,the computing power of edge devices is liberated,and the signature efficiency is improved.

Challenge-Response Emotion Authentication Algorithm Using Modified Horizontal Deep Learning

Face authentication is an important biometric authentication method commonly used in security applications.It is vulnerable to different types of attacks that use authorized users’facial images and videos captured from social media to perform spoofing attacks and dynamic movements for penetrating secur-ity applications.This paper presents an innovative challenge-response emotions authentication model based on the horizontal ensemble technique.The proposed model provides high accurate face authentication process by challenging the authorized user using a random sequence of emotions to provide a specific response for every authentication trial with a different sequence of emotions.The proposed model is applied to the KDEF dataset using 10-fold cross-valida-tions.Several improvements are made to the proposed model.First,the VGG16 model is applied to the seven common emotions.Second,the system usability is enhanced by analyzing and selecting only the four common and easy-to-use emotions.Third,the horizontal ensemble technique is applied to enhance the emotion recognition accuracy and minimize the error during authen-tication processes.Finally,the Horizontal Ensemble Best N-Losses(HEBNL)is applied using challenge-response emotion to improve the authentication effi-ciency and minimize the computational power.The successive improvements implemented on the proposed model led to an improvement in the accuracy from 92.1%to 99.27%.

Implicit Continuous User Authentication for Mobile Devices based on Deep Reinforcement Learning

The predominant method for smart phone accessing is confined to methods directing the authentication by means of Point-of-Entry that heavily depend on physiological biometrics like,fingerprint or face.Implicit continuous authentication initiating to be loftier to conventional authentication mechanisms by continuously confirming users’identities on continuing basis and mark the instant at which an illegitimate hacker grasps dominance of the session.However,divergent issues remain unaddressed.This research aims to investigate the power of Deep Reinforcement Learning technique to implicit continuous authentication for mobile devices using a method called,Gaussian Weighted Cauchy Kriging-based Continuous Czekanowski’s(GWCK-CC).First,a Gaussian Weighted Non-local Mean Filter Preprocessing model is applied for reducing the noise pre-sent in the raw input face images.Cauchy Kriging Regression function is employed to reduce the dimensionality.Finally,Continuous Czekanowski’s Clas-sification is utilized for proficient classification between the genuine user and attacker.By this way,the proposed GWCK-CC method achieves accurate authen-tication with minimum error rate and time.Experimental assessment of the pro-posed GWCK-CC method and existing methods are carried out with different factors by using UMDAA-02 Face Dataset.The results confirm that the proposed GWCK-CC method enhances authentication accuracy,by 9%,reduces the authen-tication time,and error rate by 44%,and 43%as compared to the existing methods.

Amassing the Security:An Enhanced Authentication and Key Agreement Protocol for Remote Surgery in Healthcare Environment

The development of the Internet of Things has facilitated the rapid development of various industries.With the improvement in people’s living standards,people’s health requirements are steadily improving.However,owing to the scarcity of medical and health care resources in some areas,the demand for remote surgery has gradually increased.In this paper,we investigate remote surgery in the healthcare environment.Surgeons can operate robotic arms to perform remote surgery for patients,which substantially facilitates successful surgeries and saves lives.Recently,Kamil et al.proposed a secure protocol for surgery in the healthcare environment.However,after cryptanalyzing their protocol,we deduced that their protocols are vulnerable to temporary value disclosure and insider attacks.Therefore,we design an improved authentication and key agreement protocol for remote surgeries in the healthcare environment.Accordingly,we adopt the real or random(ROR)model and an automatic verification tool Proverif to verify the security of our protocol.Via security analysis and performance comparison,it is confirmed that our protocol is a relatively secure protocol.

OTFS-Based Efficient Handover Authentication Scheme with Privacy-Preserving for High Mobility Scenarios

Handover authentication in high mobility scenarios is characterized by frequent and shortterm parallel execution.Moreover,the penetration loss and Doppler frequency shift caused by high speed also lead to the deterioration of network link quality.Therefore,high mobility scenarios require handover schemes with less handover overhead.However,some existing schemes that meet this requirement cannot provide strong security guarantees,while some schemes that can provide strong security guarantees have large handover overheads.To solve this dilemma,we propose a privacy-preserving handover authentication scheme that can provide strong security guarantees with less computational cost.Based on Orthogonal Time Frequency Space(OTFS)link and Key Encapsulation Mechanism(KEM),we establish the shared key between protocol entities in the initial authentication phase,thereby reducing the overhead in the handover phase.Our proposed scheme can achieve mutual authentication and key agreement among the user equipment,relay node,and authentication server.We demonstrate that our proposed scheme can achieve user anonymity,unlinkability,perfect forward secrecy,and resistance to various attacks through security analysis including the Tamarin.The performance evaluation results show that our scheme has a small computational cost compared with other schemes and can also provide a strong guarantee of security properties.

Secure ticket-based authentication method for IoT applications

The recent surge in the number of machines,appliances,and services connected to the Internet demands secure processing and transmission of sensory data.Authentication plays a crucial role in a typical security model used in the Internet of Things(IoT),and it protects data communications from various attacks,such as impersonation and denial of service,by verifying and allowing legitimate users to access the IoT resources.However,recent authentication literature has not addressed the need for developing a scalable and efficient authentication method in this field.This paper proposes a secure and anonymous ticket-based authentication method for the IoT.The proposed method protects the network from various security and privacy threats such as data alternation and denial of service while also offering mutual authentication and sensor anonymity.Our security and performance evaluations confirm the improvement.

A Secure Multi-factor Authentication Protocol for Healthcare Services Using Cloud-based SDN

Cloud-based SDN(Software Defined Network)integration offers new kinds of agility,flexibility,automation,and speed in the network.Enterprises and Cloud providers both leverage the benefits as networks can be configured and optimized based on the application requirement.The integration of cloud and SDN paradigms has played an indispensable role in improving ubiquitous health care services.It has improved the real-time monitoring of patients by medical practitioners.Patients’data get stored at the central server on the cloud from where it is available to medical practitioners in no time.The centralisation of data on the server makes it more vulnerable to malicious attacks and causes a major threat to patients’privacy.In recent days,several schemes have been proposed to ensure the safety of patients’data.But most of the techniques still lack the practical implementation and safety of data.In this paper,a secure multi-factor authentication protocol using a hash function has been proposed.BAN(Body Area Network)logic has been used to formally analyse the proposed scheme and ensure that no unauthenticated user can steal sensitivepatient information.Security Protocol Animator(SPAN)–Automated Validation of Internet Security Protocols and Applications(AVISPA)tool has been used for simulation.The results prove that the proposed scheme ensures secure access to the database in terms of spoofing and identification.Performance comparisons of the proposed scheme with other related historical schemes regarding time complexity,computation cost which accounts to only 423 ms in proposed,and security parameters such as identification and spoofing prove its efficiency.

Rapid authentication of different herbal medicines by heating online extraction electrospray ionization mass spectrometry

The rapid and accurate authentication of traditional Chinese medicines(TCMs)has always been a key scientific and technical problem in the field of pharmaceutical analysis.Herein,a novel heating online extraction electrospray ionization mass spectrometry(H-oEESI-MS)was developed for the rapid and direct analysis of extremely complex substances without the requirement for any sample pretreatment or pre-separation steps.The overall molecular profile and fragment structure features of various herbal medicines could be completely captured within 10–15 s,with minimal sample(<0.5 mg)and solvent consumption(<20μL for one sample).Furthermore,a rapid differentiation and authentication strategy for TCMs based on H-oEESI-MS was proposed,including metabolic profile characterization,characteristic marker screening and identification,and multivariate statistical analysis model validation.In an analysis of 52 batches of seven types of Aconitum medicinal materials,20 and 21 key compounds were screened out as the characteristic markers of raw and processed Aconitum herbal medicines,respectively,and the possible structures of all the characteristic markers were comprehensively identified based on Compound Discoverer databases.Finally,multivariate statistical analysis showed that all the different types of herbal medicines were well differentiated and identified(R^(2)X>0.87,R^(2)Y>0.91,and Q^(2)>0.72),which further verified the feasibility and reliability of this comprehensive strategy for the rapid authentication of different TCMs based on H-oEESI-MS.In summary,this rapid authentication strategy realized the ultra-high-throughput,low-cost,and standardized detection of various complex TCMs for the first time,thereby demonstrating wide applicability and value for the development of quality standards for TCMs.

A Provably Secure and PUF-Based Authentication Key Agreement Scheme for Cloud-Edge IoT

With the exponential growth of intelligent Internet of Things(IoT)applications,Cloud-Edge(CE)paradigm is emerging as a solution that facilitates resource-efficient and timely services.However,it remains an underlying issue that frequent end-edgecloud communication is over a public or adversarycontrolled channel.Additionally,with the presence of resource-constrained devices,it’s imperative to conduct the secure communication mechanism,while still guaranteeing efficiency.Physical unclonable functions(PUF)emerge as promising lightweight security primitives.Thus,we first construct a PUF-based security mechanism for vulnerable IoT devices.Further,a provably secure and PUF-based authentication key agreement scheme is proposed for establishing the secure channel in end-edge-cloud empowered IoT,without requiring pre-loaded master keys.The security of our scheme is rigorously proven through formal security analysis under the random oracle model,and security verification using AVISPA tool.The comprehensive security features are also elaborated.Moreover,the numerical results demonstrate that the proposed scheme outperforms existing related schemes in terms of computational and communication efficiency.

PSAP-WSN:A Provably Secure Authentication Protocol for 5G-Based Wireless Sensor Networks

Nowadays,the widespread application of 5G has promoted rapid development in different areas,particularly in the Internet of Things(IoT),where 5G provides the advantages of higher data transfer rate,lower latency,and widespread connections.Wireless sensor networks(WSNs),which comprise various sensors,are crucial components of IoT.The main functions of WSN include providing users with real-time monitoring information,deploying regional information collection,and synchronizing with the Internet.Security in WSNs is becoming increasingly essential because of the across-the-board nature of wireless technology in many fields.Recently,Yu et al.proposed a user authentication protocol forWSN.However,their design is vulnerable to sensor capture and temporary information disclosure attacks.Thus,in this study,an improved protocol called PSAP-WSNis proposed.The security of PSAP-WSN is demonstrated by employing the ROR model,BAN logic,and ProVerif tool for the analysis.The experimental evaluation shows that our design is more efficient and suitable forWSN environments.