Location Proof Research Articles

Enhancing Unmanned Aerial Vehicle Security: A Zero-Knowledge Proof Approach with Zero-Knowledge Succinct Non-Interactive Arguments of Knowledge for Authentication and Location Proof.

UAVs are increasingly being used in various domains, from personal and commercial applications to military operations. Ensuring the security and trustworthiness of UAV communications is crucial, and blockchain technology has been explored as a solution. However, privacy remains a challenge, especially in public blockchains. In this work, we propose a novel approach utilizing zero-knowledge proof techniques, specifically zk-SNARKs, which are non-interactive cryptographic proofs. This approach allows UAVs to prove their authenticity or location without disclosing sensitive information. We generated zk-SNARK proofs using the Zokrates tool on a Raspberry Pi, simulating a drone environment, and analyzed power consumption and CPU utilization. The results are promising, especially in the case of larger drones with higher battery capacities. Ethereum was chosen as the public blockchain platform, with smart contracts developed in Solidity and tested on the Sepolia testnet using Remix IDE. This novel proposed approach paves the way for a new path of research in the UAV area.

Navigating the challenges of imposter participants in online qualitative research: lessons learned from a paediatric health services study

BackgroundThe growth in online qualitative research and data collection provides several advantages for health service researchers and participants, including convenience and extended geographic reach. However, these online processes can also present unexpected challenges, including instances of participant fraud or scam behaviour. This study describes an incident of participant fraud identified during online focus group discussions and interviews for a PhD health services research project on paediatric neurodevelopmental care.MethodsWe aimed to recruit carers of Australian children with neurodevelopmental disorders. Potential participants were recruited via a publicly available social media advert on Facebook offering $50 AUD compensation. Those who expressed interest via email (n = 254) were sent a pre-interview Qualtrics survey to complete. We identified imposters at an early stage via inconsistencies in their self-reported geographical location and that captured by the survey as well as recognition of suspicious actions before, during and after focus group discussions and interviews.ResultsInterest in participation was unexpectedly high. We determined that all potential participants were likely imposters, posing as multiple individuals and using different IP addresses across Nigeria, Australia, and the United States. In doing so, we were able to characterise several “red flags” for identifying imposter participants, particularly those posing as multiple individuals. These comprise a combination of factors including large volumes and strange timings of email responses, unlikely demographic characteristics, short or vague interviews, a preference for nonvisual participation, fixation on monetary compensation, and inconsistencies in reported geographical location. Additionally, we propose several strategies to combat this issue such as providing proof of location or eligibility during recruitment and data collection, examining email and consent form patterns, and comparing demographic data with regional statistics.ConclusionsThe emergent risk of imposter participants is an important consideration for those seeking to conduct health services research using qualitative approaches in online environments. Methodological design choices intended to improve equity and access for the target population may have an unintended consequence of improving access for fraudulent actors unless appropriate risk mitigation strategies are also employed. Lessons learned from this experience are likely to be valuable for novice health service researchers involved in online focus group discussions and interviews.

Towards Building a Faster and Incentive Enabled Privacy-Preserving Proof of Location Scheme from GTOTP

In recent years, there has been significant growth in location-based services (LBSs) and applications. These services empower users to transmit their location data to location service providers, thereby facilitating the provisioning of pertinent resources and services. However, in order to prevent malicious users from sending fake location data, users must attest to their location for service providers, namely, through a proof of location (PoL). Such a proof should additionally prevent attackers from being able to obtain users’ identity and location information through it. In this paper, we propose an efficient privacy-preserving proof of location (PPPoL) scheme. The scheme is based on the standard cryptographic primitives, including Group Time-based One-Time Password (GTOTP) and public key encryption, which achieves entity privacy, location privacy, and traceability. Unlike the previous GTOTP-based PPPoL scheme, our scheme enables instant location verification with additional hash operations. To encourage the active participation of witnesses in location proofs, we propose an incentive mechanism based on smart contracts. Additionally, we implement a proof of concept of our PPPoL scheme on an Android device. Our experimental results show that proof generation and verification time are on the order of milliseconds. Meanwhile, the total overhead for the incentive mechanism amounts to 0.0011 ETH. This result is practical for mobile device-based LBSs.

Privacy-Preserving Location Authentication for Low-altitude UAVs: A Blockchain-based Approach

Efficient and trusted regulation of unmanned aerial vehicles (UAVs) is an essential but challenging issue in the future era of Internet of Low-altitude Intelligence, due to the difficulties in UAVs' identity recognition and location matching, potential for falsified information reporting, etc. To address this challenging issue, in this paper, we propose a blockchain-based UAV location authentication scheme, which employs a distance bounding protocol to establish a location proof, ensuring the authenticity of UAV positions. To preserve the privacy of UAVs, anonymous certificates and zero-knowledge proof are used. The security of the proposed scheme is analyzed. Experiments demonstrate the efficiency and feasibility of the proposed scheme.

Proof of location based delivery system using multi-party virtual state channel: a blockchain model

Proof of location based delivery system using multi-party virtual state channel: a blockchain model

PASPORT: A Secure and Private Location Proof Generation and Verification Framework

Abstract: Recently, there has been a rapid growth in locationbased systems and applications in which users submit their location information to service providers in order to gain access to a service, resource, or reward. We have seen that in these applications, dishonest users have an incentive to cheat on their location. Unfortunately, no effective protection mechanism has been adopted by service providers against these fake location submissions. This is a critical issue that causes severe consequences for these applications. Motivated by this, we propose the Privacy-Aware and Secure Proof Of pRoximiTy (PASPORT) scheme in this article to address the problem. Using PASPORT, users submit a location proof (LP) to service providers to prove that their submitted location is true. PASPORT has a decentralized architecture designed for ad hoc scenarios in which mobile users can act as witnesses and generate LPs for each other. It provides user privacy protection as well as security properties, such as unforgeability and non transferability of LPs. Furthermore, the PASPORT scheme is resilient to prover–prover collusions and significantly reduces the success probability of Prover–Witness collusion attacks. To further make the proximity checking process private, we propose P-TREAD, a privacy-aware distance bounding protocol and integrate it into PASPORT. To validate our model, we implement a prototype of the proposed scheme on the Android platform. Extensive experiments indicate that the proposed method can efficiently protect location-based applications against fake submissions

Privacy-Preserving Proof-of-Location With Security Against Geo-Tampering

A Proof-of-Location (POL) system is used to issue a proof-of-location token ( <inline-formula><tex-math notation="LaTeX">$pol$</tex-math></inline-formula> ) to a user who has been present at a location <inline-formula><tex-math notation="LaTeX">$\ell oc$</tex-math></inline-formula> , such that it can be later presented to a verifier to assure the presence of the user at <inline-formula><tex-math notation="LaTeX">$\ell oc$</tex-math></inline-formula> . Basic POL security requirements are <i>unforgeability</i> of <inline-formula><tex-math notation="LaTeX">$pol$</tex-math></inline-formula> , and its <i>non-transferability</i> (a <inline-formula><tex-math notation="LaTeX">$pol$</tex-math></inline-formula> issued to user <inline-formula><tex-math notation="LaTeX">$u_1$</tex-math></inline-formula> cannot be used by <inline-formula><tex-math notation="LaTeX">$u_2$</tex-math></inline-formula> ). An additional important property of POL systems is <i>user privacy</i> against the issuers and verifiers. We make two contributions. First, we formalize the POL security and privacy properties, and construct the first system providing provable security and privacy against the issuer and the verifier, both. Second, we introduce a <i>geo-tampering attack</i> that completely breaks POL system security, by simply changing the location of a <inline-formula><tex-math notation="LaTeX">$pol$</tex-math></inline-formula> issuing node. The attack applies to portable infrastructure nodes that are not continually monitored. We propose an algorithm that is used by a <inline-formula><tex-math notation="LaTeX">$pol$</tex-math></inline-formula> issuer to provide a location integrity “proof”, that will be embedded in a <inline-formula><tex-math notation="LaTeX">$pol$</tex-math></inline-formula> to protect against this attack. The proof relies on a novel application of euclidean Distance Matrices. We implemented our POL on an off-the-shelf Android smartphone to show the practicality of the proposed algorithms.

Holocene foraminifera from the outer zone of the Bahía Blanca Estuary, Argentina (South America)

In this study, Holocene paleoenvironmental changes were interpreted based on benthic foraminifers from a core (39°20′S-61°27′W) extracted from the Argentine Continental Shelf close to the Bahia Blanca Estuary, in the south of Buenos Aires Province. Foraminiferal fauna was determined, and found to include 44 species of 22 genera. From micropaleontological and sedimentological analysis, paleoenvironmental changes during the middle-late Holocene were recognized. Two stages were determined: from 8319–8045 to 7836-7623 Cal. yrs BP, the sediments reflected a shallow environment with estuarine conditions and low energy, enabling determination of a coastal depositional environment. As from ca. 7836–7623 up to ca. 651-557 Cal. yrs BP, the sediments indicated a passage towards to a shallow shelf environment with great marine influence, displaying a high degree of energy and oxygenation, which may have been related to a rise in sea level ca. 7836 -7623 Cal. yrs BP. The detailed study of the benthic foraminiferal fauna presented herein and the sedimentological and chronological analysis performed on the continental shelf next to the Bahía Blanca Estuary provide further proof of the relative location of the mean sea level during the middle Holocene transgressive hemicycle in Argentina.

Exploiting European GNSS and Ethereum in location proof systems

ABSTRACT Location-Based Services (LBSs) are essential in many application contexts like ride-sharing or navigation apps. There are cases where users could gain an advantage by submitting fake locations. The problem faced in this paper concerns the possibility that the geographic location declared by a user is not the actual location in which the user is placed. Some solutions are based on centralized or distributed verification in the literature, and other solutions are based on witnesses or infrastructure. In this paper, we highlight the limitations of such approaches and propose a new scheme that exploits signals coming from satellites to provide trustworthy location proofs, also respecting users' privacy. The proposed approach is decentralized because location proofs are stored by users in a suitably-encrypted way, and a blockchain is adopted to guarantee data integrity and authenticity. We show that the proposed approach overcomes the state of the art through a detailed analysis.

Robust Decentralized Proof of Location for Blockchain Energy Applications Using Game Theory and Random Selection

To combat the problem of illegal access to a service, several location proof strategies have been proposed in the literature. In blockchain-based decentralized applications, transactions can be issued by IoT nodes or other automated smart devices. Key pair encryption and private key signing have been defined mainly for human identification in blockchain applications, where users are personally and responsibly concerned about the confidentiality of their private key. These methods are not suitable for computing nodes whose private key is implemented in the software they run. Ensuring that transactions are issued by a legitimate sender with the proper credentials is a bigger concern in applications with financial stakes. This is the case with blockchain energy trading platforms, where prosumers are credited with tokens in exchange for their contributions of energy. The tokens are issued by smart meter nodes installed at fixed locations to monitor the energy inputs and outputs of a given prosumer and claim energy tokens on its behalf from a defined smart contract in exchange for the energy it feeds into the grid. To this end, we have developed a decentralized Proof-of-Location (PoL) system tailored to blockchain applications for energy trading. It ensures that automated transactions are issued by the right nodes by using smart contract-based random selection and a game-theoretic scenario suitable for blockchain energy trading.

Brij Niosomes as Carriers for Sustained Drug Delivery─A Fluorescence-Based Approach to Probe the Niosomal Microenvironment.

Niosomes were prepared using a triad of polyoxyethylene alkyl ether surfactants. The focus was to elucidate the effects of varying alkyl chain length and varying hydrophilic headgroups on the structure of the niosomes, with an aim to design niosomes for efficient encapsulation and release of both hydrophobic and hydrophilic drugs. The phase transitions of the surfactants were ascertained by differential scanning calorimetry. It was found that the headgroup has a profound influence on the niosomal bilayer. Fluorescent probes Coumarin 153 (C-153) and 1,6-diphenyl-1,3,5-hexatriene were used to probe the structural integrity of the niosomal bilayer under stress conditions. Other aspects of the niosomes were probed by following the aggregation of the dyes fluorescein (FL) and Nile Red, red edge excitation shift, and fluorescence resonance energy transfer (FRET) between them. Fluorescence lifetime imaging microscopy provides proof of the exact location of the donor and acceptor dyes in the niosomes under FRET condition. It was also shown that the niosomes are efficient "carriers" for entrapment and controlled release of the chemotherapeutic drug 5-fluorouracil. It was found that a rigid niosomal bilayer leads to controlled drug release. The present work is relevant for the future use of these niosomes for cargo entrapment.

Machine Learning-Blockchain Based Autonomic Peer-to-Peer Energy Trading System

This paper introduces a blockchain-based P2P energy trading platform, where prosumers can trade energy autonomously with no central authority interference. Multiple prosumers can collaborate in producing energy to form a single provider. Clients’ power consumption is monitored using a smart meter that interfaces with an IoT node connected to a blockchain private network. The smart contracts, invoked on the blockchain, enable the autonomous trading interactions between parties and govern accounts behavior within the Ethereum state. The decentralized P2P trading platform utilizes autonomous pay-per-use billing and energy routing, monitored by a smart contract. A Gated Recurrent Unit (GRU) deep learning-based model, predicts future consumption based on past data aggregated to the blockchain. Predictions are then used to set Time of Use (ToU) ranges using the K-mean clustering. The data used to train the GRU model are shared between all parties within the network, making the predictions transparent and verifiable. Implementing the K-mean clustering in a smart contract on the blockchain allows the set of ToU to be independent and incontestable. To secure the validity of the data uploaded to the blockchain, a consensus algorithm is suggested to detect fraudulent nodes along with a Proof of Location (PoL), ensuring that the data are uploaded from the expected nodes. The paper explains the proposed platform architecture, functioning as well as implementation in vivid details. Results are presented in terms of smart contract gas consumption and transaction latency under different loads.

Blockchain localization spoofing detection based on fuzzy AHP in IoT systems

Location spoof detection is a major component of location proofing mechanisms in internet of things (IoT), and it is significant for the system to assess the trustworthiness of the location data associated with the user. Unlike the work that employs physical layer features, we interest in building the infrastructure for a solution to establish location spoofing detection capabilities in blockchain-based IoT systems. In detail, at the node and the mobile trajectory level, we create an IoT system for evaluating the trustworthiness of location proofs with blockchain location system features. A blockchain-based multilayer fuzzy hierarchical analysis process (AHP) evaluation method is contemplated to detect location spoofing in the IoT system. Simulation results indicate the proposed method has a superior performance and provides a basis for the trustworthiness assessment of location proofs.

A context-aware information-based clone node attack detection scheme in Internet of Things

The rapidly expanding nature of the Internet of Things (IoT) networks is beginning to attract interest across a range of applications, including smart homes, smart transportation, smart health, and industrial contexts such as smart robotics. This cutting-edge technology enables individuals to track and control their integrated environment in real-time and remotely via a thousands of IoT devices comprised of sensors and actuators that actively participate in sensing, processing, storing and sharing information. Nonetheless, IoT devices are frequently deployed in hostile environments, wherein adversaries attempt to capture them in order to seize control of the entire network. One such example of potentially malicious behaviour is the cloning of IoT devices, in which an attacker can physically capture the devices, obtain some sensitive information, duplicate the devices, and intelligently deploy them in desired locations to conduct various insider attacks. A device cloning attack on IoT networks is a significant security concern since it allows for selective forwarding, sink-hole, black-hole, and warm-hole attacks. To address this issue, this paper provides an efficient scheme for detecting clone node attack on mobile IoT networks that uses semantic information of IoT devices known as context information to locate them securely. We design the location proof mechanism by combining location proofs and batch verification of the extended elliptic curve digital signature technique (ECDSA*) to accelerate the verification process at selected trusted nodes. Furthermore, we present a model for selecting trustworthy IoT devices based on their profile capabilities, enabling them to be chosen from the other IoT devices for the location proof-verification procedure. Compared with existing studies, the performance analysis and experimental results suggest that our proposed scheme provides a high degree of detection accuracy with minimal detection time and significantly reduces the computation, communication, energy and storage overheads.

MobChain: Three-Way Collusion Resistance in Witness-Oriented Location Proof Systems Using Distributed Consensus.

Smart devices have accentuated the importance of geolocation information. Geolocation identification using smart devices has paved the path for incentive-based location-based services (LBS). However, a user’s full control over a smart device can allow tampering of the location proof. Witness-oriented location proof systems (LPS) have emerged to resist the generation of false proofs and mitigate collusion attacks. However, witness-oriented LPS are still susceptible to three-way collusion attacks (involving the user, location authority, and the witness). To overcome the threat of three-way collusion in existing schemes, we introduce a decentralized consensus protocol called MobChain in this paper. In this scheme the selection of a witness and location authority is achieved through a distributed consensus of nodes in an underlying P2P network that establishes a private blockchain. The persistent provenance data over the blockchain provides strong security guarantees; as a result, the forging and manipulation of location becomes impractical. MobChain provides secure location provenance architecture, relying on decentralized decision making for the selection of participants of the protocol thereby addressing the three-way collusion problem. Our prototype implementation and comparison with the state-of-the-art solutions show that MobChain is computationally efficient and highly available while improving the security of LPS.

Dynamic Membership Management in Anonymous and Deniable Distance Bounding

For secure location proof in many applications, distance bounding protocols are considered as one of the useful tools that can be used in practice. In distance bounding protocols, a prover and a verifier can measure the distance between them by performing an interactive protocol. In general, the verifier is regarded as an honest service provider, and thus, an adversarial verifier is not considered for security analysis. However, we cannot ignore the possibility of the corruption of the verifier, which can spoil the prover’s privacy. To handle the security problem, a prover-anonymous and deniable distance bounding protocol is proposed, which can guarantee the privacy of the prover even though the verifier is corrupted. In this paper, we review the prover-anonymous and deniable distance bounding protocol in terms of the membership management, and we show that the communication overhead in the protocol for each membership change is O(n) where n is the number of users. Then, we propose an improved membership management technique, which can efficiently support membership change in terms of the communication overhead. The improved technique requires O(1) for each membership change instead of O(n), as in the existing protocol.

Lightweight blockchain framework for location-aware peer-to-peer energy trading

Peer-to-peer (P2P) energy trading, as a new approach for energy management in smart grids, facilitates integration of a large number of small-scale producers and consumers into energy markets. Decentralized management of these new market participants is challenging in terms of market settlement, participant reputation and consideration of grid constraints. This paper proposes a blockchain-enabled framework for P2P energy trading among producer and consumer agents in a smart grid. A fully decentralized market settlement mechanism is designed, which does not rely on a centralized entity to settle the market and encourages producers and consumers to negotiate on energy trading with their nearby agents truthfully. To this end, the electrical distance of agents is considered in the pricing mechanism to encourage agents to trade with their neighboring agents. In addition, a reputation factor is considered for each agent, reflecting its past performance in delivering the committed energy. Before starting the negotiation, agents select their trading partners based on their preferences over the reputation and proximity of the trading partners. An Anonymous Proof of Location (A-PoL) algorithm is proposed that allows agents to prove their location without revealing their real identity. The practicality of the proposed framework is illustrated through several case studies, and its security and privacy are analyzed in detail.

Location Proof Systems for Smart Internet of Things: Requirements, Taxonomy, and Comparative Analysis

In the current hyper-connected, data-driven era, smart devices are providing access to geolocation information, enabling a paradigm shift in diverse domains. Location proof systems utilize smart devices to provide witnessed proof of location to enable secure location-based services (LBS). Applications of location proof systems include safety, asset management and operations monitoring in health care, supply chain tracking, and Internet-of-Things (IoT)-based location intelligence in businesses. In this paper, we investigate the state of the art in location proof systems, examining design challenges and implementation considerations for application in the real world. To frame the analysis, we have developed a taxonomy of location proof systems and performed a comparative analysis over the common attributes, highlighting their strength and weaknesses. Furthermore, we have identified future trends for this increasingly important area of investigation and development.

Eigenvalues and delay differential equations: periodic coefficients, impulses and rigorous numerics

We develop validated numerical methods for the computation of Floquet multipliers of equilibria and periodic solutions of delay differential equations, as well as impulsive delay differential equations. Using our methods, one can rigorously count the number of Floquet multipliers outside a closed disc centered at zero or the number of multipliers contained in a compact set bounded away from zero. We consider systems with a single delay where the period is at most equal to the delay, and the latter two are commensurate. We first represent the monodromy operator (period map) as an operator acting on a product of sequence spaces that represent the Chebyshev coefficients of the state-space vectors. Truncation of the number of modes yields the numerical method, and by carefully bounding the truncation error in addition to some other technical operator norms, this leads to the method being suitable to computer-assisted proofs of Floquet multiplier location. We demonstrate the computer-assisted proofs on two example problems. We also test our discretization scheme in floating point arithmetic on a gamut of randomly-generated high-dimensional examples with both periodic and constant coefficients to inspect the precision of the spectral radius estimation of the monodromy operator (i.e. stability/instability check for periodic systems) for increasing numbers of Chebyshev modes.

Detecting Sybil Attacks Using Proofs of Work and Location in VANETs

Vehicular Ad Hoc Networks (VANETs) have the potential to enable the next-generation Intelligent Transportation Systems (ITS). In ITS, data contributed by vehicles can build a spatio-temporal view of traffic statistics, which can improve road safety and reduce slow traffic and jams. To preserve drivers&#x2019; privacy, vehicles should use multiple pseudonyms instead of only one identity. However, vehicles may exploit this abundance of pseudonyms and launch Sybil attacks by pretending to be multiple vehicles. Then, these Sybil (or fake) vehicles report false data, e.g., to create fake congestion or pollute traffic management data. In this article, we propose a Sybil attack detection scheme using proofs of work and location. The idea is that each road side unit (RSU) issues a signed time-stamped tag as a proof for the vehicle&#x2019;s anonymous location. Proofs sent from multiple consecutive RSUs are used to create a trajectory which is used as vehicle anonymous identity. Also, contributions from one RSU are not enough to create trajectories, rather the contributions of several RSUs are needed. By this way, attackers need to compromise an infeasible number of RSUs to create fake trajectories. Moreover, upon receiving the proof of location from an RSU, the vehicle should solve a computational puzzle by running proof of work (PoW) algorithm. Then, it should provide a valid solution (proof of work) to the next RSU before it can obtain a proof of location. Using the PoW can prevent the vehicles from creating multiple trajectories in case of low-dense RSUs. To report an event, the vehicle has to send the latest trajectory to an event manager. Then, the event manager uses a matching technique to identify the trajectories sent from Sybil vehicles. The scheme depends on the fact that the Sybil trajectories are bounded physically to one vehicle, and therefore, their trajectories should overlap. Extensive experiments and simulations demonstrate that our scheme achieves high detection rate of Sybil attacks with low false negative and acceptable communication and computation overhead.