- 标题
- 摘要
- 关键词
- 实验方案
- 产品
-
[IEEE 2019 IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC) - Macao, Macao (2019.12.1-2019.12.4)] 2019 IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC) - Plasmon Enhanced Semitransparent Planar Perovskite Solar Cells with Copper Nanocubes: FDTD Study
摘要： According to the growth of mobile devices equipped with a GPS receiver, a variety of location-based services (LBSs) have been launched. Since location information may reveal private information, preserving location privacy has become a significant issue. Previous studies proposed methods to preserve a users’ privacy; however, most of them do not take physical constraints into consideration. In this paper, we focus on such constraints and propose a location privacy preservation method that can be applicable to a real environment. In particular, our method anonymizes the user’s location by generating dummies which we simulate to behave like real human. It also considers traceability of the user’s locations to quickly recover from an accidental reveal of the user’s location. We conduct an experiment using five users’ real GPS trajectories and compared our method with previous studies. The results show that our method ensures to anonymize the user’s location within a pre-determined range. It also avoids fixing the relative positions of the user and dummies, which may give a hint for an LBS provider to identify the real user. In addition, we conducted a user experiment with 22 participants to evaluate the robustness of our method against humans. We asked participants to observe movements of a user and dummies and try to find the real user. As a result, we confirmed that our method can anonymize the users’ locations even against human’s observation.
关键词： Location-based service,pervasive computing,privacy
更新于2025-09-23 15:19:57
-
[IEEE 2019 21st International Conference on Transparent Optical Networks (ICTON) - Angers, France (2019.7.9-2019.7.13)] 2019 21st International Conference on Transparent Optical Networks (ICTON) - Compact and Tunable Room Temperature THz Source from Quantum Dot Based Ultrafast Photoconductive Antennae
摘要： Several approaches have been proposed to anonymize relational databases using the criterion of k-anonymity, to avoid the disclosure of sensitive information by re-identification attacks. A relational database is said to meet the criterion of k-anonymity if each record is identical to at least (k ? 1) other records in terms of quasi-identifier attribute values. To anonymize a transactional database and satisfy the constraint of k-anonymity, each item must successively be considered as a quasi-identifier attribute. But this process greatly increases dimensionality, and thus also the computational complexity of anonymization, and information loss. In this paper, a novel efficient anonymization system called PTA is proposed to not only anonymize transactional data with a small information loss but also to reduce the computational complexity of the anonymization process. The PTA system consists of three modules, which are the Pre-processing module, the TSP module, and the Anonymity model, to anonymize transactional data and guarantees that at least k-anonymity is achieved: a pre-processing module, a traveling salesman problem module, and an anonymization module. Extensive experiments have been carried to compare the efficiency of the designed approach with the state-of-the-art anonymization algorithms in terms of scalability, runtime, and information loss. Results indicate that the proposed PTA system outperforms the compared algorithms in all respects.
关键词： Anonymity,privacy preserving data mining,TSP,divide-and-conquer,Gray sort
更新于2025-09-23 15:19:57
-
[IEEE 2019 National Power Electronics Conference (NPEC) - Tiruchirappalli, India (2019.12.13-2019.12.15)] 2019 National Power Electronics Conference (NPEC) - Input Regulated Soft Switched Ripple Free Current LED Driver
摘要： The main contribution of this paper is the construction of the efficient privacy-preserving protocol for smart metering systems (EPPP4SMS), which brings together features of the best privacy-preserving protocols in the literature for smart grids. In addition, EPPP4SMS is faster on the meter side—and in the whole round (encryption, aggregation, and decryption)—than other protocols based on homomorphic encryption and it is still scalable. Moreover, EPPP4SMS enables energy suppliers and customers to verify the billing information and measurements without leaking private information. Since the energy supplier knows the amount of generated electricity and its flow throughout electrical substations, the energy supplier can use this verification to detect energy loss and fraud. Different from verification based on digital signature, our verification enables new features; for example, smart meters and their energy supplier can compute the verification without storing the respective encrypted measurements. Furthermore, EPPP4SMS may be suitable to many other scenarios that need aggregation of time-series data keeping privacy protected, including electronic voting, reputation systems, and sensor networks. In this paper, we present theoretical results of EPPP4SMS and their validation by implementation of algorithms and simulation using real-world measurement data.
关键词： Homomorphic encryption,privacy,smart grid,time series,security,protocol
更新于2025-09-23 15:19:57
-
[IEEE 2019 IEEE International Symposium on Radio-Frequency Integration Technology (RFIT) - Nanjing, China (2019.8.28-2019.8.30)] 2019 IEEE International Symposium on Radio-Frequency Integration Technology (RFIT) - Continuous Frequency-Sweep Covering Normal Direction Using Spoof Plasmonic Waveguide
摘要： One of the biggest concerns of big data is privacy. However, the study on big data privacy is still at a very early stage. We believe the forthcoming solutions and theories of big data privacy root from the in place research output of the privacy discipline. Motivated by these factors, we extensively survey the existing research outputs and achievements of the privacy ?eld in both application and theoretical angles, aiming to pave a solid starting ground for interested readers to address the challenges in the big data case. We ?rst present an overview of the battle ground by de?ning the roles and operations of privacy systems. Second, we review the milestones of the current two major research categories of privacy: data clustering and privacy frameworks. Third, we discuss the effort of privacy study from the perspectives of different disciplines, respectively. Fourth, the mathematical description, measurement, and modeling on privacy are presented. We summarize the challenges and opportunities of this promising topic at the end of this paper, hoping to shed light on the exciting and almost uncharted land.
关键词： privacy,differential privacy,Big data,data clustering
更新于2025-09-19 17:13:59
-
[IEEE 2019 IEEE 8th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP) - Le gosier, Guadeloupe (2019.12.15-2019.12.18)] 2019 IEEE 8th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP) - Performance Bounds for Coupled CP Model in the Framework of Hyperspectral Super-Resolution
摘要： One of the biggest concerns of big data is privacy. However, the study on big data privacy is still at a very early stage. We believe the forthcoming solutions and theories of big data privacy root from the in place research output of the privacy discipline. Motivated by these factors, we extensively survey the existing research outputs and achievements of the privacy ?eld in both application and theoretical angles, aiming to pave a solid starting ground for interested readers to address the challenges in the big data case. We ?rst present an overview of the battle ground by de?ning the roles and operations of privacy systems. Second, we review the milestones of the current two major research categories of privacy: data clustering and privacy frameworks. Third, we discuss the effort of privacy study from the perspectives of different disciplines, respectively. Fourth, the mathematical description, measurement, and modeling on privacy are presented. We summarize the challenges and opportunities of this promising topic at the end of this paper, hoping to shed light on the exciting and almost uncharted land.
关键词： data clustering,differential privacy,Big data,privacy
更新于2025-09-19 17:13:59
-
[IEEE 2019 22nd European Microelectronics and Packaging Conference & Exhibition (EMPC) - Pisa, Italy (2019.9.16-2019.9.19)] 2019 22nd European Microelectronics and Packaging Conference & Exhibition (EMPC) - Picosecond Laser Structuring Technology for LTCC - the Improvement of Fine Line Structuring
摘要： Biometrics is commonly used in many automated verification systems offering several advantages over traditional verification methods. Since biometric features are associated with individuals, their leakage will violate individuals’ privacy, which can cause serious and continued problems as the biometric data from a person are irreplaceable. To protect the biometric data containing privacy information, a number of privacy-preserving biometric schemes (PPBSs) have been developed over the last decade, but they have various drawbacks. The aim of this paper is to provide a comprehensive overview of the existing PPBSs and give guidance for future privacy-preserving biometric research. In particular, we explain the functional mechanisms of popular PPBSs and present the state-of-the-art privacy-preserving biometric methods based on these mechanisms. Furthermore, we discuss the drawbacks of the existing PPBSs and point out the challenges and future research directions in PPBSs.
关键词： biometric data,automated verification system,Privacy protection
更新于2025-09-19 17:13:59
-
[IEEE 2018 International Conference on Recent Innovations in Electrical, Electronics & Communication Engineering (ICRIEECE) - Bhubaneswar, India (2018.7.27-2018.7.28)] 2018 International Conference on Recent Innovations in Electrical, Electronics & Communication Engineering (ICRIEECE) - Performance Analysis Of P-V And Q-F Droop Control Strategy In An Islanded Resistive Microgrid During Partial Shading On Photovoltaic Plant
摘要： Statistics from security firms, research institutions and government organizations show that the number of data-leak instances have grown rapidly in recent years. Among various data-leak cases, human mistakes are one of the main causes of data loss. There exist solutions detecting inadvertent sensitive data leaks caused by human mistakes and to provide alerts for organizations. A common approach is to screen content in storage and transmission for exposed sensitive information. Such an approach usually requires the detection operation to be conducted in secrecy. However, this secrecy requirement is challenging to satisfy in practice, as detection servers may be compromised or outsourced. In this paper, we present a privacy-preserving data-leak detection (DLD) solution to solve the issue where a special set of sensitive data digests is used in detection. The advantage of our method is that it enables the data owner to safely delegate the detection operation to a semihonest provider without revealing the sensitive data to the provider. We describe how Internet service providers can offer their customers DLD as an add-on service with strong privacy guarantees. The evaluation results show that our method can support accurate detection with very small number of false alarms under various data-leak scenarios.
关键词： privacy,network security,Data leak,collection intersection
更新于2025-09-19 17:13:59
-
[IEEE 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC) - Chicago, IL, USA (2019.6.16-2019.6.21)] 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC) - Reduction of Operating Temperatures of PV Modules using Thermally Conductive Backsheets: Site Dependence
摘要： According to the growth of mobile devices equipped with a GPS receiver, a variety of location-based services (LBSs) have been launched. Since location information may reveal private information, preserving location privacy has become a significant issue. Previous studies proposed methods to preserve a users’ privacy; however, most of them do not take physical constraints into consideration. In this paper, we focus on such constraints and propose a location privacy preservation method that can be applicable to a real environment. In particular, our method anonymizes the user’s location by generating dummies which we simulate to behave like real human. It also considers traceability of the user’s locations to quickly recover from an accidental reveal of the user’s location. We conduct an experiment using five users’ real GPS trajectories and compared our method with previous studies. The results show that our method ensures to anonymize the user’s location within a pre-determined range. It also avoids fixing the relative positions of the user and dummies, which may give a hint for an LBS provider to identify the real user. In addition, we conducted a user experiment with 22 participants to evaluate the robustness of our method against humans. We asked participants to observe movements of a user and dummies and try to find the real user. As a result, we confirmed that our method can anonymize the users’ locations even against human’s observation.
关键词： privacy,Location-based service,pervasive computing
更新于2025-09-19 17:13:59
-
A real-time monitoring system based on ZigBee and 4G communications for photovoltaic generation
摘要： With the advent of big data era, clients lack of computational and storage resources tends to outsource data mining tasks to cloud computing providers in order to improve efficiency and save costs. Generally, different clients choose different cloud companies for the sake of security, business cooperation, location, and so on. However, due to the rise of privacy leakage issues, the data contributed by clients should be encrypted under their own keys. This paper focuses on privacy-preserving k-nearest neighbor (kNN) computation over the databases distributed among multiple cloud environments. Unfortunately, existing secure outsourcing protocols are either restricted to a single key setting or quite inefficient because of frequent client-to-server interactions, making it impractical for wide application. To address these issues, we propose a set of secure building blocks and outsourced collaborative kNN protocol. Theoretical analysis shows that our scheme not only preserves the privacy of distributed databases and kNN query but also hides access patterns in the semi-honest model. Experimental evaluation demonstrates its significant efficiency improvements compared with existing methods.
关键词： multiple clouds,k-nearest neighbor,Big data,multiple keys,privacy-preserving data mining
更新于2025-09-19 17:13:59
-
[IEEE 2019 Compound Semiconductor Week (CSW) - Nara, Japan (2019.5.19-2019.5.23)] 2019 Compound Semiconductor Week (CSW) - Lateral electronic coupling among self-assembled semiconductor quantum dots promoted by adjoining tunnel-coupled quantum-well potentials
摘要： Effective emergency (such as a hurricane, a building on fire, and so on) response requires accurate, relevant, timely, and location-aware information (e.g., environmental information, health records, and so on). Acquiring information in such critical situations encounters substantial challenges, such as large volume of data processing, unstructured data, privacy, authorized data access, and so forth. Among the issues, access authorization has received little attention. Existing solutions for data authorization either do not scale well or merely consider a Break-the-Glass concept in which a master key is provided to the first responders (FRs) to decrypt the corresponding ciphertext. This may not only enable unauthorized users to access information, but it may also overwhelm FRs by the large volume of accessible data. To jointly address the aforementioned issues, this paper proposes a location-aware authorization scheme that enables FRs to access information provided that they are within a predefined distance from data owners at the time of an emergency. We innovatively integrate attribute-based encryption with broadcast encryption to incorporate dynamic attributes (i.e., location and time) into an access policy. Such attributes act as filters to eliminate data irrelevant to an ongoing emergency. As a result, our scheme provides authorized access to accurate, relevant, timely, and location-aware information. We provide extensive security analysis and performance evaluations to demonstrate the effectiveness of our scheme. The analysis shows that the scheme imposes constant communication and decryption computation overheads. Furthermore, the proposed scheme is proven chosen plain-text attack selectively secure based on m?bilinear Diffie–Hellman exponent assumption. It also addresses the key escrow problem.
关键词： access authorization,Emergency response,location-aware data filtering,data privacy
更新于2025-09-19 17:13:59