Biblio

This paper deals with how to implement a system that extends insider threat behavior data using private blockchain technology to overcome the limitations of insider threat datasets. Currently, insider threat data is completely undetectable in existing datasets for new methods of insider threat due to the lack of insider threat scenarios and abstracted event behavior. Also, depending on the size of the company, it was difficult to secure a sample of data with the limit of a small number of leaks among many general users in other organizations. In this study, we consider insiders who pose a threat to all businesses as public enemies. In addition, we proposed a system that can use a private blockchain to expand insider threat behavior data between network participants in real-time to ensure reliability and transparency.

Cryptocurrencies such as Bitcoin and Ethereum achieve decentralized payment by maintaining a globally distributed and append-only ledger. Recently, several researchers have sought to achieve privacy-preserving auditing, which is a crucial function for scenarios that require regulatory compliance, for decentralized payment systems. However, those proposed schemes usually cost much time for the cooperation between the auditor and the user due to leveraging complex cryptographic tools such as zero-knowledge proof. To tackle the problem, we present T-PPA, a privacy-preserving decentralized payment system, which provides customizable and efficient auditability by leveraging trusted execution environments (TEEs). T-PPA demands the auditor construct audit programs based on request and execute them in the TEE to protect the privacy of transactions. Then, identity-based encryption (IBE) is employed to construct the separation of power between the agency nodes and the auditor and to protect the privacy of transactions out of TEE. The experimental results show that T-PPA can achieve privacy-preserving audits with acceptable overhead.

Frauds in supply chain finance not only result in substantial loss for financial institutions (e.g., banks, trust company, private funds), but also are detrimental to the reputation of the ecosystem. However, such frauds are hard to detect due to the complexity of the operating environment in supply chain finance such as involvement of multiple parties under different agreements. Traditional instruments of financial institutions are time-consuming yet insufficient in countering fraudulent supply chain financing. In this study, we propose a novel blockchain-driven framework for deterring fraud in supply chain finance. Specifically, we use inventory financing in jewelry supply chain as an illustrative scenario. The blockchain technology enables secure and trusted data sharing among multiple parties due to its characteristics of immutability and traceability. Consequently, information on manufacturing, brand license, and warehouse status are available to financial institutions in real time. Moreover, we develop a novel rule-based fraud check module to automatically detect suspicious fraud cases by auditing documents shared by multiple parties through a blockchain network. To validate the effectiveness of the proposed framework, we employ agent-based modeling and simulation. Experimental results show that our proposed framework can effectively deter fraudulent supply chain financing as well as improve operational efficiency.

As the COVID-19 continues to spread globally, more and more companies are transforming into remote online offices, leading to the expansion of electronic signatures. However, the existing electronic signatures platform has the problem of data-centered management. The system is subject to data loss, tampering, and leakage when an attack from outside or inside occurs. In response to the above problems, this paper designs an electronic signature solution and implements a prototype system based on the consortium blockchain. The solution divides the contract signing process into four states: contract upload, initiation signing, verification signing, and confirm signing. The signing process is mapped with the blockchain-linked data. Users initiate the signature transaction by signing the uploaded contract's hash. The sign state transition is triggered when the transaction is uploaded to the blockchain under the consensus mechanism and the smart contract control, which effectively ensures the integrity of the electronic contract and the non-repudiation of the electronic signature. Finally, the blockchain performance test shows that the system can be applied to the business scenario of contract signing.

Systems for relative localization in multi-robot systems based on ultra-wideband (UWB) ranging have recently emerged as robust solutions for GNSS-denied environments. Scalability remains one of the key challenges, particularly in adhoc deployments. Recent solutions include dynamic allocation of active and passive localization modes for different robots or nodes in the system. with larger-scale systems becoming more distributed, key research questions arise in the areas of security and trustability of such localization systems. This paper studies the potential integration of collaborative-decision making processes with distributed ledger technologies. Specifically, we investigate the design and implementation of a methodology for running an UWB role allocation algorithm within smart contracts in a blockchain. In previous works, we have separately studied the integration of ROS2 with the Hyperledger Fabric blockchain, and introduced a new algorithm for scalable UWB-based localization. In this paper, we extend these works by (i) running experiments with larger number of mobile robots switching between different spatial configurations and (ii) integrating the dynamic UWB role allocation algorithm into Fabric smart contracts for distributed decision-making in a system of multiple mobile robots. This enables us to deliver the same functionality within a secure and trustable process, with enhanced identity and data access management. Our results show the effectiveness of the UWB role allocation for continuously varying spatial formations of six autonomous mobile robots, while demonstrating a low impact on latency and computational resources of adding the blockchain layer that does not affect the localization process.

Smart cities deploy large numbers of sensors and collect a tremendous amount of data from them. For example, Advanced Metering Infrastructures (AMIs), which consist of physical meters that collect usage data about public utilities such as power and water, are an important building block in a smart city. In a typical sensor network, the measurement devices are connected through a computer network, which exposes them to cyber attacks. Furthermore, the data is centrally managed at the operator’s servers, making it vulnerable to insider threats.Our goal is to protect the integrity of data collected by large-scale sensor networks and the firmware in measurement devices from cyber attacks and insider threats. To this end, we first develop a comprehensive threat model for attacks against data and firmware integrity, which can target any of the stakeholders in the operation of the sensor network. Next, we use our threat model to analyze existing defense mechanisms, including signature checks, remote firmware attestation, anomaly detection, and blockchain-based secure logs. However, the large size of the Trusted Computing Base and a lack of scalability limit the applicability of these existing mechanisms. We propose the Feather-Light Blockchain Infrastructure (FLBI) framework to address these limitations. Our framework leverages a two-layer architecture and cryptographic threshold signature chains to support large networks of low-capacity devices such as meters and data aggregators. We have fully implemented the FLBI’s end-to-end functionality on the Hyperledger Fabric and private Ethereum blockchain platforms. Our experiments show that the FLBI is able to support millions of end devices.

Blockchain has the potential to enhance supply chain management systems by providing stronger assurance in transparency and traceability of traded commodities. However, blockchain does not overcome the inherent issues of data trust in IoT enabled supply chains. Recent proposals attempt to tackle these issues by incorporating generic trust and reputation management methods, which do not entirely address the complex challenges of supply chain operations and suffers from significant drawbacks. In this paper, we propose DeTRM, a decentralised trust and reputation management solution for supply chains, which considers complex supply chain operations, such as splitting or merging of product lots, to provide a coherent trust management solution. We resolve data trust by correlating empirical data from adjacent sensor nodes, using which the authenticity of data can be assessed. We design a consortium blockchain, where smart contracts play a significant role in quantifying trustworthiness as a numerical score from different perspectives. A proof-of-concept implementation in Hyperledger Fabric shows that DeTRM is feasible and only incurs relatively small overheads compared to the baseline.

Counterfeit drugs are an immense threat for the pharmaceutical industry worldwide due to limitations of supply chain. Our proposed solution can overcome many challenges as it will trace and track the drugs while in transit, give transparency along with robust security and will ensure legitimacy across the supply chain. It provides a reliable certification process as well. Fabric architecture is permissioned and private. Hyperledger is a preferred framework over Ethereum because it makes use of features like modular design, high efficiency, quality code and open-source which makes it more suitable for B2B applications with no requirement of cryptocurrency in Hyperledger Fabric. QR generation and scanning are provided as a functionality in the application instead of bar code for its easy accessibility to make it more secure and reliable. The objective of our solution is to provide substantial solutions to the supply chain stakeholders in record maintenance, drug transit monitoring and vendor side verification.

Blockchain is well known for its storage consistency, decentralization and tamper-proof, but the privacy disclosure and difficulty in auditing discourage the innovative application of blockchain technology. As compared to public blockchain and private blockchain, consortium blockchain is widely used across different industries and use cases due to its privacy-preserving ability, auditability and high transaction rate. However, the present co-audit of privacy-preserving data on consortium blockchain is inefficient. Private data is usually encrypted by a session key before being published on a consortium blockchain for privacy preservation. The session key is shared with transaction parties and auditors for their access. For decentralizing auditorial power, multiple auditors on the consortium blockchain jointly undertake the responsibility of auditing. The distribution of the session key to an auditor requires individually encrypting the session key with the public key of the auditor. The transaction initiator needs to be online when each auditor asks for the session key, and one encryption of the session key for each auditor consumes resources. This work proposes GAChain and applies group key agreement technology to efficiently co-audit privacy-preserving data on consortium blockchain. Multiple auditors on the consortium blockchain form a group and utilize the blockchain to generate a shared group encryption key and their respective group decryption keys. The session key is encrypted only once by the group encryption key and stored on the consortium blockchain together with the encrypted private data. Auditors then obtain the encrypted session key from the chain and decrypt it with their respective group decryption key for co-auditing. The group key generation is involved only when the group forms or group membership changes, which happens very infrequently on the consortium blockchain. We implement the prototype of GAChain based on Hyperledger Fabric framework. Our experimental studies demonstrate that GAChain improves the co-audit efficiency of transactions containing private data on Fabric, and its incurred overhead is moderate.

Internet of Things (IoT) is one relatively new technology, which aims to make our lives easier by automating our daily processes. This article would aim to deliver an idea how to prevent the IoT technology, delivering maliciously and bad things and how to scale. The intention of this research is to explain how a specific implementation of a Blockchain network, enterprise-grade permissioned distributed ledger framework called Hyperledger Fabric, can be used to resolve the security and scalability issues in an IoT network.

The ecosystem of the Internet of Things (IoT) continues growing now and covers more and more fields. One of these areas is the Industrial Internet of Things (IIoT) which integrates sensors and actuators, business applications, open web applications, multimedia security systems, positioning, and tracking systems. Each of these components creates its own data stream and has its own parameters of the probability distribution when transmitting information packets. One such distribution, specific to the TrumpfTruPrint 1000 IIoT system, is the beta distribution. We described issues of the processing of such a data flow by an agent model of the \$5\textbackslashtextbackslashtimes5\$ NoC switch fabric. The concepts of modern telecommunication networks 5G/6G imply the processing of “small” data in the place of their origin, not excluding the centralized processing of big data. This process, which involves the transmission, distribution, and processing of data, involves a large number of devices: routers, multiprocessor systems, multi-core systems, etc. We assumed that the data stream is processed by a device with the network structure, such as NoC, and goes to its built-in router. We carried out a study how the average queues of the \$5\textbackslashtextbackslashtimes5\$ router change with changes in the parameters of a data stream that has a beta distribution.

Waveguided air-coupled ultrasonic phased arrays offer grating-lobe-free beam forming for many applications such as obstacle detection, non-destructive testing, flow metering or tactile feedback. However, for industrial applications, the open output ports of the waveguide can be clogged due to dust, liquids or dirt leading to additional acoustic attenuation. In previous work, we presented the effectiveness of hydrophobic fabrics as a protection layer for acoustic waveguides. In this work, we created a numerical model of the waveguide including the hydrophobic fabric allowing the prediction of the insertion loss (IL). The numerical model uses the boundary element method (BEM) and the finite element method (FEM) in the frequency domain including the waveguide, the hydrophobic fabric and the finite-sized rigid baffle used in the measurements. All walls are assumed as ideal sound hard and the transducers are ideal piston transducers. The specific flow resistivity of the hydrophobic fabric, which is required for the simulation, is analyzed using a 3D-printed flow pipe. The simulations are validated with a calibrated microphone in an anechoic chamber. The IL of the simulations are within the uncertainties of the measurements. In addition, both the measurements and the simulations have no significant influence on the beamforming capabilities.

Modern System-on-Chip (SoC) designs integrate a number of third party IPs (3PIPs) that coordinate and communicate through a Network-on-Chip (NoC) fabric to realize system functionality. An important class of SoC security attack involves a rogue IP tampering with the inter-IP communication. These attacks include message snoop, message mutation, message misdirection, IP masquerade, and message flooding. Static IP-level trust verification cannot protect against these SoC-level attacks. In this paper, we analyze the vulnerabilities of system level communication among IPs and develop a novel SoC security architecture that provides system resilience against exploitation by untrusted 3PIPs integrated over an NoC fabric. We show how to address the problem through a collection of fine-grained SoC security policies that enable on-the-fly monitoring and control of appropriate security-relevant events. Our approach, for the first time to our knowledge, provides an architecture-level solution for trusted SoC communication through run-time resilience in the presence of untrusted IPs. We demonstrate viability of our approach on a realistic SoC design through a series of attack models and show that our architecture incurs minimal to modest overhead in area, power, and system latency.

The complexity of building, deploying, and managing cross-organizational enterprise computing services with self-service, security, and quality assurances has been increasing exponentially in the era of hybrid multiclouds. AI-accelerated material discovery capabilities, for example, are desirable for enterprise application users to consume through business API services with assurance of satisfactory nonfunctional properties, e.g., enterprise-compliant self-service management of sharable sensitive data and machine learning capabilities at Internet scale. This paper presents a composable microservices based approach to creating and continuously improving enterprise computing services. Moreover, it elaborates on several key architecture design decisions for Navarch, a composable enterprise microservices fabric that facilitates consuming, managing, and composing enterprise API services. Under service management model of individual administration, every Navarch microservice is a managed composable API service that can be provided by an internal organization, an enterprise partner, or a public service provider. This paper also illustrates a Navarch-enabled systematic and efficient approach to transforming an AI-accelerated material discovery tool into secure, scalable, and composable enterprise microservices. Performance of the microservices can be continuously improved by exploiting advanced heterogeneous microservice hosting infrastructures. Factual comparative performance analyses are provided before the paper concludes with future work.

We propose a novel attestation architecture for the Internet of Things (IoT). Our distributed attestation network (DAN) utilizes blockchain technology to store and share device information. We present the design of this new attestation architecture as well as a prototype system chosen to emulate an IoT deployment with a network of Raspberry Pi, Infineon TPMs, and a Hyperledger Fabric blockchain.

In many organizations, permissioned blockchain networks are currently transitioning from a proof-of-concept stage to production use. A crucial part of this transition is ensuring awareness of potential threats to network operations. Due to the plethora of software components involved in distributed ledgers, threats may be difficult or impossible to detect without a structured monitoring approach. To this end, we conduct a survey of attacks on permissioned blockchains and develop a set of threat indicators. To gather these indicators, a data processing pipeline is proposed to aggregate log information from relevant blockchain components, enriched with data from external sources. To evaluate the feasibility of monitoring current blockchain frameworks, we determine relevant data sources in Hyperledger Fabric. Our results show that the required data is mostly available, but also highlight significant improvement potential with regard to threat intelligence, chaincode scanners and built-in metrics.

In agriculture, farmers are the most important entity. For supporting farmers in increasing productivity and efficiency, the government offers subsidies, loans, insurances, and so on. This paper explores the usage of Blockchain technology for securing farmer's data in the Indian scenario. The farmer needs to register through the multiple official registration systems for availing different schemes and information provided by the country. The personnel and crop-based details of each farmer are collected at the time of registration. The filing also helps in providing better services to farmers like connecting farmers and traders to ensure a fair price for quality crops, advice to farmers of agricultural practices and location. In this paper, a blockchain-based farmer's data securing system is proposed to provide data provenance and transparency of the information entered in the system. While registering, the data is collected, and it is verified. A single verified record of farmers accessed by various government agriculture departments were designed using the Hyperledger fabric framework.

Authenticating a person's identity has always been a challenge. While attempts are being made by government agencies to address this challenge, the citizens are being exposed to a new age problem of Identity management. The sharing of photocopies of identity cards in order to prove our identity is a common sight. From score-card to Aadhar-card, the details of our identity has reached many unauthorized hands during the years. In India the identity thefts accounts for 77% [1] of the fraud cases, and the threats are trending. Programs like e-Residency by Estonia[2], Bitnation using Ethereum[3] are being devised for an efficient Identity Management. Even the US Home Land Security is funding a research with an objective of “Design information security and privacy concepts on the Blockchain to support identity management capabilities that increase security and productivity while decreasing costs and security risks for the Homeland Security Enterprise (HSE).” [4] This paper will discuss the challenges specific to India around Identity Management, and the possible solution that the Distributed ledger, hashing algorithms and smart contracts can offer. The logic of hashing the personal data, and controlling the distribution of identity using public-private keys with Blockchain technology will be discussed in this paper.

Due to the decentralization, irreversibility, and traceability, blockchain has attracted significant attention and has been deployed in many critical industries such as banking and logistics. However, the micro-architecture characteristics of blockchain programs still remain unclear. What's worse, the large number of micro-architecture events make understanding the characteristics extremely difficult. We even lack a systematic approach to identify the important events to focus on. In this paper, we propose a novel benchmarking methodology dubbed BBS to characterize blockchain programs at micro-architecture level. The key is to leverage fuzzy set theory to identify important micro-architecture events after the significance of them is quantified by a machine learning based approach. The important events for single programs are employed to characterize the programs while the common important events for multiple programs form an importance vector which is used to measure the similarity between benchmarks. We leverage BBS to characterize seven and six benchmarks from Blockbench and Caliper, respectively. The results show that BBS can reveal interesting findings. Moreover, by leveraging the importance characterization results, we improve that the transaction throughput of Smallbank from Fabric by 70% while reduce the transaction latency by 55%. In addition, we find that three of seven and two of six benchmarks from Blockbench and Caliper are redundant, respectively.

Coupling regular topologies with optimized routing algorithms is key in pushing the performance of interconnection networks of HPC systems. In this paper we present Dmodc, a fast deterministic routing algorithm for Parallel Generalized Fat-Trees (PGFTs) which minimizes congestion risk even under massive topology degradation caused by equipment failure. It applies a modulo-based computation of forwarding tables among switches closer to the destination, using only knowledge of subtrees for pre-modulo division. Dmodc allows complete re-routing of topologies with tens of thousands of nodes in less than a second, which greatly helps centralized fabric management react to faults with high-quality routing tables and no impact to running applications in current and future very large-scale HPC clusters. We compare Dmodc against routing algorithms available in the InfiniBand control software (OpenSM) first for routing execution time to show feasibility at scale, and then for congestion risk under degradation to demonstrate robustness. The latter comparison is done using static analysis of routing tables under random permutation (RP), shift permutation (SP) and all-to-all (A2A) traffic patterns. Results for Dmodc show A2A and RP congestion risks similar under heavy degradation as the most stable algorithms compared, and near-optimal SP congestion risk up to 1% of random degradation.

The global Electronic Health Record (EHR) market is growing dramatically and expected to reach \$39.7 billions by 2022. To safe-guard security and privacy of EHR, access control is an essential mechanism for managing EHR data. This paper proposes a hybrid architecture to facilitate access control of EHR data by using both blockchain and edge node. Within the architecture, a blockchain-based controller manages identity and access control policies and serves as a tamper-proof log of access events. In addition, off-chain edge nodes store the EHR data and apply policies specified in Abbreviated Language For Authorization (ALFA) to enforce attribute-based access control on EHR data in collaboration with the blockchain-based access control logs. We evaluate the proposed hybrid architecture by utilizing Hyperledger Composer Fabric blockchain to measure the performance of executing smart contracts and ACL policies in terms of transaction processing time and response time against unauthorized data retrieval.

Numerous IoT applications, like building automation or process control of industrial sites, exist today. These applications inherently have a strong connection to the physical world. Hence, IT security threats cannot only cause problems like data leaks but also safety issues which might harm people. Attacks on IT systems are not only performed by outside attackers but also insiders like administrators. For this reason, we present ongoing work on a Byzantine fault tolerant configuration management system (CMS) that provides control over administrators, restrains their rights, and enforces separation of concerns. We reach this goal by conducting a configuration management process that requires multi-party authorization for critical configurations to prevent individual malicious administrators from performing undesired actions. Only after a configuration has been authorized by multiple experts, it is applied to the targeted devices. For the whole configuration management process, our CMS guarantees accountability and traceability. Lastly, our system is tamper-resistant as we leverage Hyperledger Fabric, which provides a distributed execution environment for our CMS and a blockchain-based distributed ledger that we use to store the configurations. A beneficial side effect of this approach is that our CMS is also suitable to manage configurations for infrastructure shared across different organizations that do not need to trust each other.

In this paper, we propose a video surveillance system based on blockchain system. The proposed system consists of a blockchain network with trusted internal managers. The metadata of the video is recorded on the distributed ledger of the blockchain, thereby blocking the possibility of forgery of the data. The proposed architecture encrypts and stores the video, creates a license within the blockchain, and exports the video. Since the decryption key for the video is managed by the private DB of the blockchain, it is not leaked by the internal manager unauthorizedly. In addition, the internal administrator can manage and export videos safely by exporting the license generated in the blockchain to the DRM-applied video player.

Recently, the Internet of Things (IoT) is growing rapidly. IoT sensors are attached to various devices, and information is detected, collected and utilized through various wired and wireless communication environments. As the IoT is used in various places, IoT devices face a variety of malicious attacks such as MITM and reverse engineering. To prevent these, encryption is required for device-to-device communication, and keys required for encryption must be properly managed. We propose a scheme to generate seed needed for key generation and a scheme to manage the public key using blockchain.

Emergency medical services universally get regarded as the essential part of the health care delivery system [1]. A relationship exists between the emergency patient death rate and factors such as the failure to access a patient's critical data and the time it takes to arrive at hospitals. Nearly thirty million Americans do not live within an hour of trauma care, so this poor access to trauma centers links to higher pre-hospital death rates in more than half of the United States [2]. So, we need to address the problem. In a patient care-cycle, loads of medical data items are born in different healthcare settings using a disparate system of records during patient visits. The ability for medical care providers to access a patient's complete picture of emergency-relevant medical data is critical and can significantly reduce the annual mortality rate. Today, the problem exists with a continuous recording system of the patient data between healthcare providers. In this paper, we've introduced a combination of secure file transfer methods/tools and blockchain technology as a solution to record patient Emergency relevant medical data as patient walk through from one clinic/medical facility to another, creating a continuous footprint of patient as a secure and scalable data source. So, ambulance crews can access and use it to provide high quality pre-hospital care. All concerns of medical record sharing and accessing like authentication, privacy, security, scalability and audibility, confidentiality has been considered in this approach.