Dense network and quantum key techniques: a novel approach to identity verification and authentication

Density control is a key technique in dense sensor networks for prolonging network's lifetime while providing sufficient sensing coverage. In this paper we present a new density control algorithm called ESSC(Enhanced Sponsored Sector Coverage) based on the SSC(Sponsored Sector Coverage) proposed by Tian Di. ESSC algorithm takes note of the deficiency of the SSC algorithm and modifies the model of SSC to minimize the active node number. Analysis and experimental results show that ESSC can use up to 15%~25% fewer active nodes than SSC while promising the performance of the network surveillance.

The transition from 4G LTE to 5G networks is expected to bring transformative changes to mobile telecommunications, offering higher speeds, lower latencies, and greater capacity. However, the migration to 5G is a gradual process, and 4G LTE networks must continue to serve a significant role during this transition. This paper discusses various optimization techniques to enhance the performance of 4G LTE networks in anticipation of 5G, focusing on Radio Resource Management (RRM), interference management, traffic offloading, and network densification. These techniques will help ensure that existing LTE networks can handle the increasing data demands and facilitate a smooth integration with 5G technologies.

<sec>The absolute security of quantum communication protocols relies on a critical premise: all participating parties are legitimate users. Ensuring the legitimacy of participant identities is paramount in complex real-world communication environments. Quantum identity authentication (QIA), in which fundamental principles of quantum mechanics are used to achieve unilateral or mutual authentication between communicating parties, constitutes an indispensable core component for building a comprehensive quantum secure communication system. It holds significant research value in the field of quantum communication.</sec><sec>This review employs a comparative classification method to systematically outline the research trajectory of QIA protocols. By categorizing protocols based on the required quantum resources and the types of quantum protocols employed, the advantages and disadvantages of various categories are analyzed in terms of efficiency, security, and practicality. Single-photon protocols require low resources, and they are easy to implement, and compatible with existing optical components, but require high-efficiency single-photon detectors and exhibit weak noise resistance. Entangled-state protocols offer high security and strong resistance to eavesdropping, particularly suitable for long-distance or multi-party authentication. However, they greatly depend on the preparation and maintenance of high-precision, stable multi-particle entanglement sources, resulting in high experimental complexity. Continuous-variable (CV) protocols achieve high transmission efficiency in short-distance metropolitan area networks and are compatible with classical optical communication equipment, making experiments relatively straightforward. Yet, they require high-precision modulation technology and are sensitive to channel loss. Hybrid protocols aim to balance resource efficiency and security while reducing reliance on a single quantum source, but their design is complex and may introduce new attack vectors. Quantum key distribution (QKD) framework protocols embed identity authentication in the key distribution process, making them suitable for scenarios requiring long-term secure key distribution, although they often depend on pre-shared keys or trusted third parties. Quantum secure direct communication (QSDC) framework protocols integrate authentication with secure direct information transmission, offering high efficiency for real-time communication, but requiring high channel quality. Measurement-device-independent QSDC (MDI-QSDC) represents a key development direction that can resist attacks on measurement devices. Quantum teleportation (QT) framework protocols achieves cross-node authentication and unconditional security, making it suitable for quantum relay networks despite its high experimental complexity. The entanglement swapping framework protocol can resist conspiracy attacks and is suitable for multi-party joint scenarios, but it consumes a lot of resources and relies on trusted third party. Ping-pong protocol framework supports dynamic key updates and exhibits strong resistance to eavesdropping, making it suitable for temporary authentication on mobile terminals, although it typically only supports unilateral authentication and requires a bidirectional channel.</sec><sec>Subsequently, this review details the latest QIA protocols of our research group, including a multi-party synchronous identity authentication protocol based on Greenberger-Horne-Zeilinger (GHZ) states, and a tripartite QSDC protocol with identity authentication capabilities utilizing polarization-spatial super-coding. The GHZ-based multi-party synchronous authentication protocol leverages the strong correlations inherent in GHZ states to achieve simultaneous authentication among multiple parties. Through a carefully designed two-round decoy-state detection mechanism, it effectively resists both external eavesdropping and internal attacks originating from authenticated users, thereby enhancing the efficiency and security of identity management in large-scale quantum networks. The core innovation of the polarization-spatial super-coding tripartite QSDC protocol lies in its deep integration of the authentication process with information transmission by utilizing the spatial degrees of freedom of single photons. This design accomplishes the identity verification of two senders and the transmission of secret information within a single protocol run, ensuring end-to-end security through a three-stage security check. This “authentication-as-communication” paradigm significantly improves the overall efficiency and practicality of the protocol. Its successful implementation also relies on advancements in quantum memory technology.</sec><sec>Finally, the review outlines future research directions for quantum identity authentication and explores its potential applications in quantum communication. The QIA research needs to focus on reducing resource dependency, exploring more efficient protocol designs, further enhancing protocol integration and robustness, prioritizing the development of protocols adaptable to real-world environments, and actively investigating integration with novel scenarios. This comprehensive review aims to provide theoretical research foundations and technical support for the practical development of future quantum identity authentication.</sec>

In today's society, the rapid development of the Internet makes People's Daily life become more intelligent and diversified. Today's society has entered a multifaceted era where everything is interconnected. Artificial intelligence technology is gradually replacing some traditional human services, such as intelligent robot customer service instead of traditional human customer service, intelligent face scanning security check in railway stations instead of traditional manual ticket checking, unmanned supermarket automatic checkout has liberated some social labor costs. All these changes are the result of the development of artificial intelligence technology in today's society. In recent years, unicorn startups focused on biometrics have sprung up all around us, such as BTU and its MEG VII (Face ++). Thanks to the development of Internet and artificial intelligence technology, in many application fields, the traditional access control and identity authentication technology based on password verification is gradually transforming to the scheme based on biometric identification verification. Secure identity authentication is very important to the application of Internet. Face recognition is the most popular technology among all biometric identification technologies. In the field of biometric identification technology, it has become the most widely used technology in the field of identity authentication because of its unique non-invasive, support for infrared and visible light, no need for user cooperation and many other advantages. In the field of education, examinee identification, pedestrian identification detection at the entrance of railway stations, face electronic payment, intelligent video surveillance system, intelligent attendance and access control system, intelligent unmanned supermarkets and customs clearance ports become the pioneer fields of face recognition applications. It can be seen that the era of “national face brushing” has arrived, and the application of face recognition technology will only be more and more widespread in the current era and in the future. However, due to the sensitivity of biometric data and the heterogeneity and openness of network environment, the privacy leakage of biometric data is difficult to avoid. At present, fog computing and edge computing have been paid more and more attention in many fields. In the case that cloud service providers are unable to provide sufficient security, edge computing shows its advantages. In this paper, mobile edge computing is introduced for the first time into the face privacy protection identity authentication system based on cloud server outsourcing computing. It can not only greatly reduce the interaction frequency between users and cloud server, improve the availability and fault tolerance of the system, but also contribute to the implementation of privacy protection scheme. A deep constitutional neural network for face feature extraction is trained using deep learning framework Cafe. Cosine similarity is used to complete face verification. A privacy protection scheme based on the secure nearest neighbor algorithm is proposed, which can not only protect the security of the face feature data at the edge computing node, but also allow the edge computing node to complete the face recognition operation against the encrypted face feature data. In addition, the encryption scheme does not require large computing resources, and the accuracy of face recognition in cipher text is exactly the same as that in explain. At present, most of the solutions either have high computational complexity or poor security performance. How to reduce the computational complexity and improve the real-time performance of the system while ensuring the high security of the private data has important research significance and value. Therefore, in the cloud server outsourcing computing environment, how to complete biometric identification on the premise of protecting the privacy of biological data has become a research hot spot.

In the domain of smart devices, biometric identity authentication has become a leading and crucial technology, mainly because of its improved security and user convenience. Traditional methods frequently depend on complex activities, facial recognition, or passwords, which can be cumbersome and error-prone. This paper presents GrasOpen, an innovative biometric authentication system tailored for door-opening scenarios, utilizing the natural reach-and-grasp motion linked to door handles. The system employs smartwatches with accelerometers and gyroscopes to track and analyze arm movements, ensuring a seamless and intuitive user experience. GrasOpen tackles key challenges by leveraging the unique characteristics of the reach-and-grasp motion, eliminating the necessity for users to remember complex motions, and avoiding redundant actions like waiting for facial recognition. Specifically, GrasOpen initially proposes a lightweight model to discern door-opening actions from daily activities. Then, to realize the robust authentication system, GrasOpen integrates a complementary filter (CF) method to capture diversity-dependent features in door-opening actions. These features are subsequently processed through a modified ConvBoost model for precise user authentication. Experimental results reveal an impressive accuracy of 98.78% for activity recognition and 98.65% for identity authentication, highlighting GrasOpen’s excellence in function and performance. The system’s security and robustness are validated across diverse authentication environments.

MFSSIA: Ontology of blockchain-based multi-factor challenge set self-sovereign identity authentication

With the continuous speed-up of society informatization, the action of E-commerce is more and more extensive. Meanwhile safety troubles increase steadily, it severely restrict the development of E-commerce. How to handle and keep away the safety problems is becoming the vita points of Internet trading. This paper is mainly to investigate the identity authentication technology in commerce, analyse the advantage & disadvantage of identity authentication technology based on PKT and identity authentication technology based on biometric characters. Consequently it integrates these two technologies and puts forward the protection password of biometric authentication. Via the password protection of biometric authentication, it settles the identity authentication in E-commerce trust management thoroughly.KeywordsE-commerceInternet tradingtrust managementidentity authentication

According to recent research, attacks on USIM cards are on the rise. In a 5G setting, attackers can also employ counterfeit USIM cards to circumvent the identity authentication of specified standard applications and steal user information. Under the assumption that the USIM can be replicated, the identity authentication process of common mobile platform applications is investigated. The identity authentication tree is generated by examining the application behavior of user login, password reset, and sensitive operations. We tested 58 typical applications in 7 categories, including social communication and personal health. We found that 29 of them only needed the SMS verification code received by the USIM card to pass the authentication. In response to this problem, it is recommended to enable two-step verification and use USIM anti-counterfeiting methods to complete the verification.

Global mobile communication necessitates improved capacity and proper quality assurance for services. To achieve these requirements, small cells have been deployed intensively by long term evolution (LTE) networks operators beside conventional base station structure to provide customers with better service and capacity coverage. Accomplishment of seamless handover between Macrocell layer (first tier) and Femtocell layer (second tier) is one of the key challenges to attain the QoS requirements. Handover related information gathering becomes very hard in high dense femtocell networks, effective handover decision techniques are important to minimize unnecessary handovers occurred and avoid Ping-Pong effect. In this work, we proposed and implemented an efficient handover decision procedure based on users’ profiles using Q-learning technique in an LTE-A macrocell-femtocell networks. New multi-criterion handover decision parameters are proposed in typical/dense femtocells in microcells environment to estimate the target cell for handover. The proposed handover algorithms are validated using the LTE-Sim simulator under an urban environment. The simulation results showed noteworthy reduction in the average number of handovers.

Current anonymity techniques for mobile opportunistic networks typically use obfuscation algorithms to hide node's identity behind other nodes. These algorithms are not well suited to sparse and disconnection prone networks with large number of malicious nodes and new opportunistic, adaptive. So, new, opportunistic, adaptive fully localized mechanisms are needed for improving user anonymity. This paper proposes reputation aware localized adaptive obfuscation for mobile opportunistic networks that comprises of two complementary techniques: opportunistic collaborative testing of nodes' obfuscation behaviour (OCOT) and multidimensional adaptive anonymisation (AA). OCOT-AA is driven by both explicit and implicit reputation building, complex graph connectivity analytics and obfuscation history analyses. We show that OCOT-AA is very efficient in terms of achieving high levels of node identity obfuscation and managing low delays for answering queries between sources and destinations while enabling fast detection and avoidance of malicious nodes typically within the fraction of time within the experiment duration. We perform extensive experiments to compare OCOT-AA with several other competitive and benchmark protocols and show that it outperforms them across a range of metrics over a one month real-life GPS trace. To demonstrate our proposal more clearly, we propose new metrics that include best effort biggest length and diversity of the obfuscation paths, the actual percentage of truly anonymised sources' IDs at the destinations and communication quality of service between source and destination.

The fuzzy vault algorithm is mainly used for data privacy protection in fault-tolerant environments, It binds biometric features and secret data together safely to form a vault, which can realize "fuzzy" unlocking. in the real-life, fuzzy vault is mainly used in biometric authentication, image capture, recognition, etc. However, At present, most fuzzy vault schemes have the problems of high computational complexity and low communication efficiency. To solve the problems of high computational complexity and low communication efficiency in identity authentication, we based on the fuzzy vault scheme and construct a multi-secret sharing fuzzy vault scheme. which splits the big secret value into multiple sub-secret values and uses the RS code multi-secret sharing decoding method to improve the efficiency of biological identity authentication. Firstly, splits the big secret value into multiple sub-secret values. Then, We construct a multi-secret sharing scheme. our scheme supports the sharing of multi-secret information. Finally, we analyze the computational complexity and communication complexity of the scheme. The analysis shows that our scheme can reduce the computational complexity and communication complexity by an order of magnitude.

This study proposes a Blockchain-based Student Identity Management System (BSIMS) to address critical challenges in current identity management systems in higher education, such as trust deficits, data confidentiality breaches, and lack of interoperability. BSIMS is designed to enhance the personal learning environment (PLE) in higher education by providing secure, reliable, transparent, and efficient identity verification and data management services. The model was developed based on insights from semi-structured interviews with seven ICT experts from both academia and industry, focusing on personal data confidentiality within the PLE. Thematic analysis identified key challenges, including data security, control, circulation, trust, user needs and experience, and system performance and scalability. BSIMS comprises modules such as PLE participants, platform, identity authentication, blockchain verification, shared learning content, blockchain technology, and a Learning Record Store (LRS) verification system. These modules are characterized by autonomy, security, flexibility, and efficiency. The study details the functionality and interactions of these components while acknowledging the model’s limitations and suggesting future research directions. This research highlights the potential of blockchain technology to create an autonomous, secure, and efficient identity management mechanism within higher education's PLE. The innovation lies in applying blockchain to the PLE's identity verification process and introducing a feature to record user behavior using blockchain, thereby enhancing personal data confidentiality and demonstrating blockchain’s potential in education.

We report here on progress made for the period from December 1, 1992 (the date of submission of our latest progress report) to November 30, 1993 for DOE Grant No. DE-FG05-92ER40717. The new results from the SMC experiment have generated a buzz of theoretical activity. Our involvement with the D0 experiment and the upgrade has increased substantially during the past two years so that we now have six people heavily committed and making what can only be described as a large and disproportionate impact on D0 physics output. Some of the new developments made here at Rice in Neural Network and Probability Density Estimation techniques for data analysis promise to have applications both in D0 and beyond. We report a load of new results from our high-p{sub t} jet photoproduction experiment. In addition we have been working on KTeV, albeit without having adequate funding for this work. Progress on the theoretical front has been nothing short of amazing, as is reported herein. In a grand lecture tour during this sabbatical year, Paul Stevenson has already reported his breakthroughs at ten institutions, including CERN, Oxford, Cambridge, Rutherford Lab, Imperial College, and Durham University. The group at Rice University has had an exceptionally productive year and we are justifiably proud of the progress which is reported here.

The authentication and verification of user and device identities require cost-effective solutions. As two emerging approaches, biometric authentication and digital fingerprint, allow users and device to prove their identity efficiently and securely. Most of the existing methods focus on the authentication propose for users and devices separately and do not consider the authentication problem for user-device pairing. Furthermore, users are more inclined to register multiple services with the same secret information. Therefore, the potential risks brought by the reuse of secret information need to be taken seriously. This study proposes the RUDBA scheme, a novel reusable user-device biometric authentication scheme that captures the user's biometrics and the device's fingerprint. The extracted confidential is fused as authentication information for the user-device pair's identity and can be reused among multiple service providers. This scheme is implemented using the public biometric dataset and the intrinsic SRAM PUF data. The experimental results and analysis show that the RUDBA scheme leads to a reliable and reusable users-device authentication system.

This chapter gives an overview over visualization techniques beyond the node-link diagram. Node-link diagrams are by far the most common visual representation to visualize networks, showing nodes as points, and links as lines or arcs between them. However, with increasing size of a network, as well as data about time and temporal change, geography, or other attributes about node and links, alternative representations are required. Starting from a discussion of the problems of visualizing dense networks through node-link diagrams (i.e. hairballs), this chapter discusses a range of alternatives to node-link diagrams: adjacency matrices to compare networks and visualize multivariate networks; techniques for networks with different node and link types; networks with quantitative attributes on nodes, Ontologies, networks changing over time, and geographic networks. The chapter concludes with a pointer to common network visualization tools and a discussion of how to choose among the wide range of visualization techniques.