Abstract: Achieving low latency and providing real-time services are two of several key challenges in conventional cloud-based smart grid systems, and hence, there has been an increasing trend of moving to edge computing. While there have been a number of cryptographic protocols designed to facilitate secure communications in smart grid systems, existing protocols generally do not support conditional anonymity and flexible key management. Thus, in this article, we introduce a blockchain-based mutual authentication and key agreement protocol for edge-computing-based smart grid systems. Specifically, leveraging blockchain, the protocol can support efficient conditional anonymity and key management, without the need for other complex cryptographic primitives. The security analysis shows that the protocol achieves reasonable security assurance, and the comparative summary for security and efficiency also suggests the potential of the proposed protocol in a smart grid deployment.

Abstract: We present CrypTFlow, a first of its kind system that converts TensorFlow inference code into Secure Multi-party Computation (MPC) protocols at the push of a button. To do this, we build three components. Our first component, Athos, is an end-to-end compiler from TensorFlow to a variety of semihonest MPC protocols. The second component, Porthos, is an improved semi-honest 3-party protocol that provides significant speedups for TensorFlow like applications. Finally, to provide malicious secure MPC protocols, our third component, Aramis, is a novel technique that uses hardware with integrity guarantees to convert any semi-honest MPC protocol into an MPC protocol that provides malicious security. The malicious security of the protocols output by Aramis relies on integrity of the hardware and semi-honest security of MPC. Moreover, our system matches the inference accuracy of plaintext TensorFlow.We experimentally demonstrate the power of our system by showing the secure inference of real-world neural networks such as ResNet50 and DenseNet121 over the ImageNet dataset with running times of about 30 seconds for semi-honest security and under two minutes for malicious security. Prior work in the area of secure inference has been limited to semi-honest security of small networks over tiny datasets such as MNIST or CIFAR. Even on MNIST/CIFAR, CrypTFlow outperforms prior work.

Abstract: The Internet of Things (IoT) is leading today’s digital transformation Relying on a combination of technologies, protocols, and devices such as wireless sensors and newly developed wearable and implanted sensors, IoT is changing every aspect of daily life, especially recent applications in digital healthcare IoT incorporates various kinds of hardware, communication protocols, and services This IoT diversity can be viewed as a double-edged sword that provides comfort to users but can lead also to a large number of security threats and attacks In this survey paper, a new compacted and optimized architecture for IoT is proposed based on five layers Likewise, we propose a new classification of security threats and attacks based on new IoT architecture The IoT architecture involves a physical perception layer, a network and protocol layer, a transport layer, an application layer, and a data and cloud services layer First, the physical sensing layer incorporates the basic hardware used by IoT Second, we highlight the various network and protocol technologies employed by IoT, and review the security threats and solutions Transport protocols are exhibited and the security threats against them are discussed while providing common solutions Then, the application layer involves application protocols and lightweight encryption algorithms for IoT Finally, in the data and cloud services layer, the main important security features of IoT cloud platforms are addressed, involving confidentiality, integrity, authorization, authentication, and encryption protocols The paper is concluded by presenting the open research issues and future directions towards securing IoT, including the lack of standardized lightweight encryption algorithms, the use of machine-learning algorithms to enhance security and the related challenges, the use of Blockchain to address security challenges in IoT, and the implications of IoT deployment in 5G and beyond

Abstract: Industrial Internet of Things (IIoT) is revolutionizing many leading industries such as energy, agriculture, mining, transportation, and healthcare. IIoT is a major driving force for Industry 4.0, which heavily utilizes machine learning (ML) to capitalize on the massive interconnection and large volumes of IIoT data. However, ML models that are trained on sensitive data tend to leak privacy to adversarial attacks, limiting its full potential in Industry 4.0. This article introduces a framework named PriModChain that enforces privacy and trustworthiness on IIoT data by amalgamating differential privacy, federated ML, Ethereum blockchain, and smart contracts. The feasibility of PriModChain in terms of privacy, security, reliability, safety, and resilience is evaluated using simulations developed in Python with socket programming on a general-purpose computer. We used Ganache_v2.0.1 local test network for the local experiments and Kovan test network for the public blockchain testing. We verify the proposed security protocol using Scyther_v1.1.3 protocol verifier.

Abstract: With the rapid development of technologies such as artificial intelligence, blockchain, cloud computing, and big data, Medical Cyber Physical Systems (MCPS) are increasingly demanding data security, while cloud storage solves the storage problem of complex medical data. However, it is difficult to realize data security sharing. The decentralization feature of blockchain is helpful to solve the problem that the secure authentication process is highly dependent on the trusted third party and implement data security transmission. In this paper, the blockchain technology is used to describe the security requirements in authentication process, and a network model of MCPS based on blockchain is proposed. Through analysis of medical data storage architecture, it can ensure that data can't be tampered and untrackable. In the security authentication phase, bilinear mapping and intractable problems can be used to solve the security threat in the authentication process of medical data providers and users. It can avoid the credibility problem of the trusted third party, and also can realize the ?thyc=10?>two-way authentication between the hospital and blockchain node. Then, BAN logic is used to analyze security protocols, and formal analysis and comparison of security protocols are also made. The results show that the MCPS based on blockchain not only realizes medical treatment data sharing, but also meet the various security requirements in the security authentication phase. In addition, the storage and computing overhead costs is ideal. Therefore, the proposed scheme is more suitable for secure sharing of medical big data.

Abstract: In this work, we discuss our successful efforts for industry deployment of a cryptographic secure computation protocol. The problem we consider is privately computing aggregate conversion rate of advertising campaigns. This underlying functionality can be abstracted as Private Intersection-Sum (PI-Sum) with Cardinality. In this setting two parties hold datasets containing user identifiers, and one of the parties additionally has an integer value associated with each of its user identifiers. The parties want to learn the number of identifiers they have in common and the sum of the integer values associated with these users without revealing any more information about their private inputs. We identify the major properties and enabling factors which make the deployment of a cryptographic protocol possible, practical, and uniquely positioned as a solution for the task at hand. We describe our deployment setting and the most relevant efficiency measure, which in our setting is communication overhead rather than computation. We also present a monetary cost model that can be used as a unifying cost measure and the computation model which reflect out use-case: a low-priority batch computing. We present three PI-Sum with cardinality protocols: our currently deployed protocol, which relies on a Diffie-Hellman style double masking, and two new protocols which leverage more recent techniques for private set intersection (PSI) that use Random Oblivious Transfer and encrypted Bloom filters. We compare the later two protocol with our original solution when instantiated with different additively homomorphic encryption schemes. We implement our constructions and compare their costs. We also compare with recent generic approaches for computing on the intersection of two datasets and show that our best protocol has monetary cost that is 20× less than the best known generic approach.

Abstract: In many industry Internet of Things applications, resources like CPU, memory, and battery power are limited and cannot afford the classic cryptographic security solutions. Silicon physical unclonable function (PUF) is a lightweight security primitive that exploits manufacturing variations during the chip fabrication process for key generation and/or device authentication. However, traditional weak PUFs such as ring oscillator (RO) PUF generate chip-unique key for each device, which restricts their application in security protocols where the same key is required to be shared in resource-constrained devices. In this article, in order to address this issue, we propose a PUF-based key sharing method for the first time. The basic idea is to implement one-to-one input–output mapping with lookup table (LUT)-based interstage crossing structures in each level of inverters of RO PUF. Individual customization on configuration bits of interstage crossing structure and different RO selections with challenges bring high flexibility. Therefore, with the flexible configuration of interstage crossing structures and challenges, crossover RO PUF can generate the same shared key for resource-constrained devices, which enables a new application for lightweight key sharing protocols.

Abstract: Many companies provide neural network prediction services to users for a wide range of applications. However, current prediction systems compromise one party's privacy: either the user has to send sensitive inputs to the service provider for classification, or the service provider must store its proprietary neural networks on the user's device. The former harms the personal privacy of the user, while the latter reveals the service provider's proprietary model.We design, implement, and evaluate Delphi, a secure prediction system that allows two parties to execute neural network inference without revealing either party's data. Delphi approaches the problem by simultaneously co-designing cryptography and machine learning. We first design a hybrid cryptographic protocol that improves upon the communication and computation costs over prior work. Second, we develop a planner that automatically generates neural network architecture configurations that navigate the performance-accuracy trade-offs of our hybrid protocol. Together, these techniques allow us to achieve a 22x improvement in online prediction latency compared to the state-of-the-art prior work.

Abstract: While traditional symmetric algorithms like AES and SHA3 are optimized for efficient hardware and software implementations, a range of emerging applications using advanced cryptographic protocols such as multi-party computation and zero-knowledge proofs require optimization with respect to a different metric: arithmetic complexity. In this paper we study the design of secure cryptographic algorithms optimized to minimize this metric. We begin by identifying the differences in the design space between such arithmetization-oriented ciphers and traditional ones, with particular emphasis on the available tools, efficiency metrics, and relevant cryptanalysis. This discussion highlights a crucial point --- the considerations for designing arithmetization-oriented ciphers are oftentimes different from the considerations arising in the design of software- and hardware-oriented ciphers. The natural next step is to identify sound principles to securely navigate this new terrain, and to materialize these principles into concrete designs. To this end, we present the Marvellous design strategy which provides a generic way to easily instantiate secure and efficient algorithms for this emerging domain. We then show two examples for families following this approach. These families --- Vision and Rescue --- are benchmarked with respect to three use cases: the ZK-STARK proof system, proof systems based on Rank-One Constraint Satisfaction (R1CS), and Multi-Party Computation (MPC). These benchmarks show that our algorithms achieve a highly compact algebraic description, and thus benefit the advanced cryptographic protocols that employ them. Evidence is provided that this is the case also in real-world implementations.

Abstract: Many blockchain consensus protocols have been proposed recently to scale the throughput of a blockchain with available bandwidth. However, these protocols are becoming increasingly complex, making it more and more difficult to produce proofs of their security guarantees. We propose a novel permissionless blockchain protocol OHIE which explicitly aims for simplicity. OHIE composes as many parallel instances of Bitcoin’s original (and simple) backbone protocol as needed to achieve excellent throughput. We formally prove the safety and liveness properties of OHIE. We demonstrate its performance with a prototype implementation and large-scale experiments with up to 50,000 nodes. In our experiments, OHIE achieves linear scaling with available bandwidth, providing about 4-10Mbps transaction throughput (under 8-20Mbps per-node available bandwidth configurations) and at least about 20x better decentralization over prior works.

Abstract: Consensus is arguably one of the most fundamental problems in distributed computing, playing also an important role in the area of cryptographic protocols as the enabler of a secure broadcast functionality. While the problem has a long and rich history and has been analyzed from many different perspectives, recently, with the advent of blockchain protocols like Bitcoin, it has experienced renewed interest from a much wider community of researchers and has seen its application expand to various novel settings.

Abstract: Adversary models have been fundamental to the various cryptographic protocols and methods. However, their use in most of the branches of research in computer science is comparatively restricted, primarily in case of the research in cyberphysical security (e.g., vulnerability studies, position confidentiality). In this article, we propose an energy-aware green adversary model for its use in smart industrial environment through achieving confidentiality. Even though, mutually the hardware and the software parts of cyberphysical systems can be improved to decrease its energy consumption, this article focuses on aspects of conserving position and information confidentiality. On the basis of our findings (assumptions, adversary goals, and capabilities) from the literature, we give some testimonials to help practitioners and researchers working in cyberphysical security. The proposed model that runs on real-time anticipatory position-based query scheduling in order to minimize the communication and computation cost for each query, thus, facilitating energy consumption minimization. Moreover, we calculate the transferring/acceptance slots required for each query to avoid deteriorating slots. The experimental results confirm that the proposed approach can diminish energy consumption up to five times in comparison to existing approaches

Abstract: This work presents a general framework for describing cryptographic protocols and analyzing their security. The framework allows specifying the security requirements of practically any cryptographic task in a unified and systematic way. Furthermore, in this framework the security of protocols is preserved under a general composition operation, called universal composition. The proposed framework with its security-preserving composition operation allows for modular design and analysis of complex cryptographic protocols from simpler building blocks. Moreover, within this framework, protocols are guaranteed to maintain their security in any context, even in the presence of an unbounded number of arbitrary protocol sessions that run concurrently in an adversarially controlled manner. This is a useful guarantee, which allows arguing about the security of cryptographic protocols in complex and unpredictable environments such as modern communication networks.

Abstract: We define the notion of one-shot signatures, which are signatures where any secret key can be used to sign only a single message, and then self-destructs. While such signatures are of course impossible classically, we construct one-shot signatures using quantum no-cloning. In particular, we show that such signatures exist relative to a classical oracle, which we can then heuristically obfuscate using known indistinguishability obfuscation schemes. We show that one-shot signatures have numerous applications for hybrid quantum/classical cryptographic tasks, where all communication is required to be classical, but local quantum operations are allowed. Applications include one-time signature tokens, quantum money with classical communication, decentralized blockchain-less cryptocurrency, signature schemes with unclonable secret keys, non-interactive certifiable min-entropy, and more. We thus position one-shot signatures as a powerful new building block for novel quantum cryptographic protocols.

Abstract: In the traditional electronic health record (EHR) management system, each medical service center manages their own health records, respectively, which are difficult to share on the different medical platforms. Recently, blockchain technology is one of the popular alternatives to enable medical service centers based on different platforms to share EHRs. However, it is hard to store whole EHR data in blockchain because of the size and the price of blockchain. To resolve this problem, cloud computing is considered as a promising solution. Cloud computing offers advantageous properties such as storage availability and scalability. Unfortunately, the EHR system with cloud computing can be vulnerable to various attacks because the sensitive data is sent over a public channel. We propose the secure protocol for cloud-assisted EHR system using blockchain. In the proposed scheme, blockchain technology is used to provide data integrity and access control using log transactions and the cloud server stores and manages the patient's EHRs to provide secure storage resources. We use an elliptic curve cryptosystems (ECC) to provide secure health data sharing with cloud computing. We demonstrate that the proposed EHR system can prevent various attacks by using informal security analysis and automated validation of internet security protocols and applications (AVISPA) simulation. Furthermore, we prove that the proposed EHR system provides secure mutual authentication using BAN logic analysis. We then compare the computation overhead, communication overhead, and security properties with existing schemes. Consequently, the proposed EHR system is suitable for the practical healthcare system considering security and efficiency.

Abstract: As a kind of point-to-point distributed public ledger technology, blockchain has been widely concerned in recent years. The privacy protection of blockchain technology has always been the core issue of people's attention. In this paper, some existing solutions to the current problems of user identity and transaction privacy protection are surveyed, including coin mixing mechanism, zero knowledge proof, ring signature and other technologies. Secondly, five typical applications of privacy protection technology based on blockchain are proposed and analyzed, which are mainly divided into technology applications based on coin mixing protocol, encryption protocol, secure channel protocol and so on. Finally, in view of the shortages of the existing blockchain privacy protection technology, we explore future research challenges that need to be studied in order to preserve privacy in blockchain system, and looks forward to the future development direction.

Abstract: We propose AriaNN, a low-interaction privacy-preserving framework for private neural network training and inference on sensitive data. Our semi-honest 2-party computation protocol leverages function secret sharing, a recent lightweight cryptographic protocol that allows us to achieve an efficient online phase. We design optimized primitives for the building blocks of neural networks such as ReLU, MaxPool and BatchNorm. For instance, we perform private comparison for ReLU operations with a single message of the size of the input during the online phase, and with preprocessing keys close to 4X smaller than previous work. Last, we propose an extension to support n-party private federated learning. We implement our framework as an extensible system on top of PyTorch that leverages CPU and GPU hardware acceleration for cryptographic and machine learning operations. We evaluate our end-to-end system for private inference and training on standard neural networks such as AlexNet, VGG16 or ResNet18 between distant servers. We show that computation rather than communication is the main bottleneck and that using GPUs together with reduced key size is a promising solution to overcome this barrier.

Abstract: Sensor nodes play a major role in IoT environment, and each sensor is a peer to peer networking. Due to limited physical size, IoT sensor nodes must have light-weight authentication protocol. The Internet of Things (IoT) is a collection of various technical elements. It is expected that interworking between heterogeneous terminals, networks, and applications. They will accelerate through the liberalization of the IoT platform. As a result, many technical and administrative security threats will arise in the IoT environment. Sensor node protocols must be light-weight and secure. As IoT devices are used for various purposes, for some devices that require performance, the OS with a high-performance chipset that works, most passwords protocol. However, to turn on / off the lights IoT devices that perform simple tasks such as based on a low-performance chipset with no OS running. If it does not support encryption protocol or certificate, then it is vulnerable, and it does not have enough performance to handle. Therefore, in this paper, Block-chain-based IoT device is proposed to get a more secure authentication scheme.

Abstract: Extensive use of unmanned aerial vehicles (commonly referred to as a “drone”) has posed security and safety challenges. To mitigate security threats caused by flights of unauthorized drones, we present a framework called SENTINEL (Secure and Efficient autheNTIcation for uNmanned aErial vehicLes) under the Internet of Drones (IoD) infrastructure. SENTINEL is specifically designed to minimize the computational and traffic overheads caused by certificate exchanges and asymmetric cryptography computations that are typically required for authentication protocols. SENTINEL initially generates a flight session key for a drone having a flight plan and registers the flight session key and its flight plan into a centralized database that can be accessed by ground stations. The registered flight session key is then used as the message authentication code key to authenticate the drone by any ground station while the drone is flying. To demonstrate the feasibility of the proposed scheme, we implemented a prototype of SENTINEL with ECDSA, PBKDF2 and HMAC-SHA256. The experiment results demonstrated that the average execution time of the authentication protocol in SENTINEL was about 3.1 times faster than the “TLS for IoT” protocol. We also formally proved the security of SENTINEL using ProVerif that is an automatic cryptographic protocol verifier.

Abstract: Communication in modern cars is managed by a controller area network (CAN) bus protocol and its extensions for electronic control units (ECUs). The CAN bus is a preferred method for reliable real-time broadcast communication. However, unprotected CAN communications make the vehicles vulnerable to a variety of practical malicious wired/wireless attacks. In this work, we analyze the existing frame-level authentication protocol and identify weaknesses and limitations. To address this, we provide a protocol suite for entity authentication, key management, a secure message flow for remote transmission request frames and session key update to be applied for vehicle connection with external devices. We prove the security of our protocol in the random oracle model and assess its resistance against known attacks. We formally verify the security of our protocol using the Tamarin tool. Our simulation results indicate that our protocol improves efficiency.

Abstract: Confidentiality is an indispensable requirement in financial applications of blockchain technology, and supporting it along with high performance and friendly programmability is technically challenging. In this paper, we present a system design called CONFIDE to support on-chain confidentiality by leveraging Trust Execution Environment (TEE). CONFIDE's secure data transmission protocol and data encryption protocol, together with a highly efficient virtual machine run in TEE, guarantee the confidentiality in the life cycle of a transaction from end to end. CONFIDE proposes a secure data model along with an application-driven secure protocol to guarantee data confidentiality and integrity. Its smart contract language extension offers users the flexibility to define complex confidentiality models. CONFIDE is implemented as a plugin module to Antfin Blockchain's proprietary platform, and can be plugged into other blockchain platforms as well with its universal interface design. Nowadays, CONFIDE is supporting millions of commercial transactions daily on consortium blockchain running financial applications including supply chain finance, ABS, commodity provenance, and cold-chain logistics.

Abstract: Physical unclonable function (PUF) is hardware-specific security primitive for providing cryptographic functionalities that are applicable for secure communication among the embedded devices. The physical structure of PUF is considered to be easy to manufacture but hard or impossible to replicate due to variations in its manufacturing process. However, a large community of analytics believes hardware-based PUF has paved the way for its realisation in providing dependable security. In this study, the authors have thoroughly explored the architecture, applications, requirements, and challenges of PUF that provide security solutions. For presenting the literature, they have designed a taxonomy where PUFs are divided under two main categories, including non-silicon and silicon-based PUF. Currently, there is no comprehensive survey that highlights the comparison and usability of memory-based and analogue/mixed-signal based PUF that are considered to be suitable as compared to counterparts. In a similar vein, they have presented the network-specific application scenarios in wireless sensor network, wireless body area network and Internet of Things and then identified the strong, weak and controlled PUF in a categorical manner. Moreover, they have presented a number of prospective limitations that are identified in PUF structures and then identified the open research challenges to meet the desired security levels.

Abstract: The Scytl/SwissPost e-voting solution was intended to provide complete verifiability for Swiss government elections. We show failures in both individual verifiability and universal verifiability (as defined in Swiss Federal Ordinance 161.116), based on mistaken implementations of cryptographic components. These failures allow for the construction of "proofs" of an accurate election outcome that pass verification though the votes have been manipulated. Using sophisticated cryptographic protocols without a proper consideration of what properties they offer, and under which conditions, can introduce opportunities for undetectable fraud even though the system appears to allow verification of the outcome.Our findings are immediately relevant to systems in use in Switzerland and Australia, and probably also elsewhere.

Abstract: \(\varSigma \)-Protocols provide a well-understood basis for secure algorithmics. Recently, Bulletproofs (Bootle et al., EUROCRYPT 2016, and Bunz et al., S&P 2018) have been proposed as a drop-in replacement in case of zero-knowledge (ZK) for arithmetic circuits, achieving logarithmic communication instead of linear. Its pivot is an ingenious, logarithmic-size proof of knowledge BP for certain quadratic relations. However, reducing ZK for general relations to it forces a somewhat cumbersome “reinvention” of cryptographic protocol theory.

Abstract: The rapid development of low-power integrated circuits, wireless communication, intelligent sensors and microelectronics has allowed the realization of wireless body area networks (WBANs), which can monitor patients' vital body parameters remotely in real time to offer timely treatment. These vital body parameters are related to patients' life and health; and these highly private data are subject to many security threats. To guarantee privacy, many secure communication protocols have been proposed. However, most of these protocols have a one-to-one structure in extra-body communication and cannot support multidisciplinary team (MDT). Hence, we propose a lightweight and certificateless multi-receiver secure data transmission protocol for WBANs to support MDT treatment in this paper. In particular, a novel multi-receiver certificateless generalized signcryption (MR-CLGSC) scheme is proposed that can adaptively use only one algorithm to implement one of three cryptographic primitives: signature, encryption or signcryption. Then, a multi-receiver secure data transmission protocol based on the MR-CLGSC scheme with many security properties, such as data integrity and confidentiality, non-repudiation, anonymity, forward and backward secrecy, unlinkability and data freshness, is designed. Both security analysis and performance analysis show that the proposed protocol for WBANs is secure, efficient and highly practical.

Abstract: In a smart grid, fine-grained usage reports of consumers are gathered using some computationally constrained smart measurement devices. One of the most challenging requirements in the data aggregation is how to securely read the consumption data, while putting the least possible overhead on smart meters. For this reason, recently, two efficient security protocols have been proposed to be used for subsequent secure consumption reports gathered from isolated smart measurement devices. Nonetheless, in both protocols, for each key establishment, the smart reader requires to connect to the electricity service provider (ESP) via the Internet. This paper proposes a novel key establishment protocol, which is free from the ESP involvement during the key agreement and benefits from notable reduction in the communication cost. Our thorough efficiency and security analyses indicate the eminence of the proposed security protocol.