Attribute-based Encryption (ABE) is an information centric security solution that moves beyond traditional restrictions of point-to-point encryption by allowing for flexible, fine-grain policy-based and content-based access control that is cryptographically enforced. As the original ABE systems are managed by a single authority, several efforts have decentralized different ABE schemes to address the key escrow problem, where the authority can issue secret keys to itself to decrypt all the ciphertext. However, decentralized ABE (DABE) schemes raise the issue of collusion attacks. In this paper, we review two existing types of collusion attacks on DABE systems, and introduce a new type of collusion among authorities and data users. We show that six existing DABE systems are vulnerable to the newly introduced collusion and propose a model to secure one of the DABE schemes.
Recent trend towards cloud computing paradigm, smart devices and 4G wireless technologies has enabled seamless data sharing among users. Cloud computing environment is distributed and untrusted, hence data owners have to encrypt their data to enforce data confidentiality. The data confidentiality in a distributed environment can be achieved by using attribute-based encryption technique. Decentralized attribute-based encryption technique is a variant of multiple authority based attribute-based encryption whereby any attribute authority can independently join and leave the system without collabo…
The concept of proxy re-encryption (PRE) dates back to the work of Blaze, Bleumer, and Strauss in 1998. PRE offers delegation of decryption rights, i.e., it securely enables the re-encryption of ciphertexts from one key to another, without relying on trusted parties. PRE allows a semi-trusted third party termed as a ``proxy" to securely divert encrypted files of user A (delegator) to user B (delegatee) without revealing any information about the underlying files to the proxy. To eliminate the necessity of having a costly certificate verification process, Green and Ateniese introduced an identi…
Collusion occurs when multiple malicious participants of a distributed protocol work together to sabotage or spy on honest participants. Decentralized protocols often rely on a subset of participants called workers for critical operations. Collusion between workers can be particularly harmful to the security of the protocol. We propose two protocols that select a subset of workers from the set of participants such that the probability of the workers colluding together is minimized. Our first solution is a decentralized protocol that randomly selects workers in a verifiable manner without any t…
FL-DABE-BC: A Privacy-Enhanced, Decentralized Authentication, and Secure Communication for Federated Learning Framework with Decentralized Attribute-Based Encryption and Blockchain for IoT Scenarios
Zoom Meeting is an enterprise online video conferencing solution with real-time messaging and content sharing. However, it's lack of privacy protection since centralized Zoom servers are capable of monitoring user's messages. Thereby, to solve the privacy problem, in May 2020, Zoom acquired Keybase so that Keybase's team can help it to build end-to-end encryption meeting while remaining Zoom's current scalability and high-performance. Nonetheless, according to the latest released Zoom's whitepaper, even with the new design of E2E (end to end) encryption meeting, the security threats can't be e…
Energy storage units (ESUs) including EVs and home batteries enable several attractive features of the modern smart grids such as effective demand response and reduced electric bills. However, uncoordinated charging of ESUs stresses the power system. In this paper, we propose privacy-preserving and collusion-resistant charging coordination centralized and decentralized schemes for the smart grid. The centralized scheme is used in case of robust communication infrastructure that connects the ESUs to the utility, while the decentralized scheme is useful in case of infrastructure not available or…
Attribute-based encryption (ABE) is a promising tool for implementing fine-grained access control.To solve the matters of security in single authority, access policy public, not traceable of malicious user,we proposed a scheme of multi-authority. Moreover, multi-authority may bring about the collusion of different authorities.In order to solve these problem,we proposed a scheme of access tree structure with policy hidden and access complex.Once the private key is leaked, our scheme can extract the user ID and find it.If the authorities share their information with each other,the scheme avoid t…
Decentralized deep learning plays a key role in collaborative model training due to its attractive properties, including tolerating high network latency and less prone to single-point failures. Unfortunately, such a training mode is more vulnerable to data privacy leaks compared to other distributed training frameworks. Existing efforts exclusively use differential privacy as the cornerstone to alleviate the data privacy threat. However, it is still not clear whether differential privacy can provide a satisfactory utility-privacy trade-off for model training, due to its inherent contradictions…
Secure linear aggregation is to linearly aggregate private inputs of different users with privacy protection. The server in a federated learning (FL) environment can fulfill any linear computation on private inputs of users through the secure linear aggregation. At present, based on pseudo-random number generator and one-time padding technique, one can efficiently compute the sum of user inputs in FL, but linear calculations of user inputs are not well supported. Based on decentralized threshold additive homomorphic encryption (DTAHE) schemes, this paper provides a secure linear aggregation pr…
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). A location proof is a digital certificate of the geographical location of a user, which can be used to access various LBS. However, a user full control over a device allows the tampering of location proof. Initially, to resist false proofs, two-party trusted centralized location proof systems (LPS) were introduced to aid the users in generating secure location proofs mutually. However, two-party protocols …
In some situations the communications of a place can be affected, totally lost, or not even exist. In these cases, the MANETs play an important role, allowing to establish a communications point using the different nodes of the network to reach the destination using decentralized communications. This paper proposes the implementation of a Robotic MANET, a decentralized network using robots as its nodes, which allows to move the network nodes to the desired location remotely. For this, each robot has as a core a Raspberry Pi with the capabilities to perform audio and video streaming, remote con…
NuCypher KMS is a decentralized Key Management System (KMS) that addresses the limitations of using consensus networks to securely store and manipulate private, encrypted data. It provides encryption and cryptographic access controls, performed by a decentralized network, leveraging proxy re-encryption. Unlike centralized KMS as a service solutions, it doesn't require trusting a service provider. NuCypher KMS enables sharing of sensitive data for both decentralized and centralized applications, providing security infrastructure for applications from healthcare to identity management to decentr…
Information-Theoretic Decentralized Secure Aggregation with Passive Collusion Resilience
Department of Electrical Engineering and Computer Science, Technical University of Berlin（技术大学柏林电气工程与计算机科学系）；Guangxi Key Laboratory of Multimedia Communications and Network Technology, Guangxi University（广西多媒体通信与网络技术重点实验室，广西大学）；School of Electronic Information and Communications, Huazhong University of Science and Technology（华中科技大学电子信息与通信学院）；School of Electrical Engineering and Telecommunications, University of New South Wales（新南威尔士大学电子工程与电信学院）
At present, the cloud storage used in searchable symmetric encryption schemes (SSE) is provided in a private way, which cannot be seen as a true cloud. Moreover, the cloud server is thought to be credible, because it always returns the search result to the user, even they are not correct. In order to really resist this malicious adversary and accelerate the usage of the data, it is necessary to store the data on a public chain, which can be seen as a decentralized system. As the increasing amount of the data, the search problem becomes more and more intractable, because there does not exist an…
Cooperative Decentralized Backdoor Attacks on Vertical Federated Learning
Elmore Family School of Electrical and Computer Engineering, Purdue University（电子工程学院，普渡大学）；Department of Electrical and Computer Engineering, University of Akron（电气与计算机工程系，阿克隆大学）；Department of Electrical Engineering, University at Buffalo-SUNY（电气工程系，布法罗大学）
Attribute-Based Encryption (ABE) has emerged as an information-centric public-key cryptographic system which allows a data owner to share data, according to access policy, with multiple data users based on the attributes they possess, without knowing their identities. In the original ABE schemes, a central authority administrates the system and issues secret keys to data users based on their attributes and both the owner and users need to trust a specific CA. However, in certain real-world applications, the data users would not trust anyone but themselves. For such situations, we introduce a n…
Federated learning has emerged as a privacy-preserving machine learning approach where multiple parties can train a single model without sharing their raw training data. Federated learning typically requires the utilization of multi-party computation techniques to provide strong privacy guarantees by ensuring that an untrusted or curious aggregator cannot obtain isolated replies from parties involved in the training process, thereby preventing potential inference attacks. Until recently, it was thought that some of these secure aggregation techniques were sufficient to fully protect against in…
AdeptHEQ-FL: Adaptive Homomorphic Encryption for Federated Learning of Hybrid Classical-Quantum Models with Dynamic Layer Sparing
University of Southern California（南加州大学）；Islamic University of Technology（伊斯兰科技大学）；American International University-Bangladesh（孟加拉国美国国际大学）；Multimedia University（多媒体大学）
University of Florida（佛罗里达大学）；Northeastern University（东北大学）
Scientific collaborations benefit from collaborative learning of distributed sources, but remain difficult to achieve when data are sensitive. In recent years, privacy preserving techniques have been widely studied to analyze distributed data across different agencies while protecting sensitive information. Most existing privacy preserving techniques are designed to resist semi-honest adversaries and require intense computation to perform data analysis. Secure collaborative learning is significantly difficult with the presence of malicious adversaries who may deviates from the secure protocol.…
Searchable symmetric encryption (SSE) allows the data owner to outsource an encrypted database to a remote server in a private manner while maintaining the ability for selectively search. So far, most existing solutions focus on an honest-but-curious server, while security designs against a malicious server have not drawn enough attention. A few recent works have attempted to construct verifiable SSE that enables the data owner to verify the integrity of search results. Nevertheless, these verification mechanisms are highly dependent on specific SSE schemes, and fail to support complex queries…
An Efficient and Multi-private Key Secure Aggregation for Federated Learning
Southwest Jiaotong University（西南交通大学）；Canadian Institute of Cybersecurity（加拿大网络安全研究所）；University of New Brunswick（新不伦瑞克大学）；DBAPPSecurity Ltd（杭州迪普科技股份有限公司）
QuanCrypt-FL: Quantized Homomorphic Encryption with Pruning for Secure Federated Learning
The Knight Foundation School of Computing and Information Sciences, Florida International University（佛罗里达国际大学骑士基金会计算与信息科学学院）；Sustainability, Optimization, and Learning for InterDependent networks laboratory（相互依赖网络的可持续性、优化与学习实验室）
UNESCO Chair in Data Privacy（联合国教科文组织数据隐私教席）；CYBERCAT-Center for Cybersecurity Research of Catalonia（CYBERCAT-加泰罗尼亚网络安全研究中心）；Universitat Rovira i Virgili（罗维拉-威尔吉利大学）
The decentralized nature of federated learning, that often leverages the power of edge devices, makes it vulnerable to attacks against privacy and security. The privacy risk for a peer is that the model update she computes on her private data may, when sent to the model manager, leak information on those private data. Even more obvious are security attacks, whereby one or several malicious peers return wrong model updates in order to disrupt the learning process and lead to a wrong model being learned. In this paper we build a federated learning framework that offers privacy to the participati…
