Potential Single Point Of Failure Research Articles

Distributed Identity Authentication with Lenstra-Lenstra-Lovász Algorithm-Ciphertext Policy Attribute-Based Encryption from Lattices: An Efficient Approach Based on Ring Learning with Errors Problem.

In recent years, research on attribute-based encryption (ABE) has expanded into the quantum domain. Because a traditional single authority can cause the potential single point of failure, an improved lattice-based quantum-resistant identity authentication and policy attribute encryption scheme is proposed, in which the generation of random values is optimized by adjusting parameters in the Gaussian sampling algorithm to improve overall performance. Additionally, in the key generation phase, attributes are processed according to their shared nature, which reduces the computational overhead of the authorization authority. In the decryption phase, the basis transformation of the Lenstra-Lenstra-Lovász (LLL) lattice reduction algorithm is utilized to rapidly convert shared matrices into the shortest vector form, which can reduce the computational cost of linear space checks. The experimental results demonstrate that the proposed method not only improves efficiency but also enhances security compared with related schemes.

A Novel Blockchain-based Responsible Recommendation System for Service Process Creation and Recommendation

Service composition platforms play a crucial role in creating personalized service processes. Challenges, including the risk of tampering with service data during service invocation and the potential single point of failure in centralized service registration centers, hinder the efficient and responsible creation of service processes. This paper presents a novel framework called Context-Aware Responsible Service Process Creation and Recommendation (SPCR-CA), which incorporates blockchain, Recurrent Neural Networks (RNNs), and a Skip-Gram model holistically to enhance the security, efficiency, and quality of service process creation and recommendation. Specifically, the blockchain establishes a trusted service provision environment, ensuring transparent and secure transactions between services and mitigating the risk of tampering. The RNN trains responsible service processes, contextualizing service components and producing coherent recommendations of linkage components. The Skip-Gram model trains responsible user-service process records, generating semantic vectors that facilitate the recommendation of similar service processes to users. Experiments using the Programmable-Web dataset demonstrate the superiority of the SPCR-CA framework to existing benchmarks in precision and recall. The proposed framework enhances the reliability, efficiency, and quality of service process creation and recommendation, enabling users to create responsible and tailored service processes. The SPCR-CA framework offers promising potential to provide users with secure and user-centric service creation and recommendation capabilities.

Decentralized Identity Authentication Mechanism: Integrating FIDO and Blockchain for Enhanced Security

FIDO (Fast Identity Online) is a set of network identity standards established by the FIDO Alliance. It employs a framework based on public key cryptography to facilitate multi-factor authentication (MFA) and biometric login, ensuring the robust protection of personal data associated with cloud accounts and ensuring the security of server-to-terminal device protocols during the login process. The FIDO Alliance has established three standards: FIDO Universal Second Factor (FIDO U2F), FIDO Universal Authentication Framework (FIDO UAF), and the Client to Authenticator Protocols (CTAP). The newer CTAP, also known as FIDO2, integrates passwordless login and two-factor authentication. Importantly, FIDO2’s support for major browsers enables users to authenticate their identities via FIDO2 across a broader range of platforms and devices, ushering in the era of passwordless authentication. In the FIDO2 framework, if a user’s device is stolen or compromised, then the private key may be compromised, and the public key stored on the FIDO2 server may be tampered with by attackers attempting to impersonate the user for identity authentication, posing a high risk to information security. Recognizing this, this study aims to propose a solution based on the FIDO2 framework, combined with blockchain technology and access control, called the FIDO2 blockchain architecture, to address existing security vulnerabilities in FIDO2. By leveraging the decentralized nature of the blockchain, the study addresses potential single points of failure in FIDO2 server centralized identity management systems, thereby enhancing system security and availability. Furthermore, the immutability of the blockchain ensures the integrity of public keys once securely stored on the chain, effectively reducing the risk of attackers impersonating user identities. Additionally, the study implements an access control mechanism to manage user permissions effectively, ensuring that only authorized users can access corresponding permissions and preventing unauthorized modifications and abuse. In addition to proposing practical solutions and steps, the study explains and addresses security concerns and conducts performance evaluations. Overall, this study brings higher levels of security and trustworthiness to FIDO2, providing a robust identity authentication solution.

Fixation of the Proximal Hamstring Tendon Using an All-Suture Tensionable Knotless Technique

Proximal hamstring injuries are a common sports and recreational injury among the active patient population. Surgical fixation of the tendons of the hamstring muscle complex, as opposed to conservative treatment alone, has shown improved patient outcomes, prompting the evolution of the suture anchors utilized in these repairs. Previous studies investigating the biomechanical properties of hamstring repair anchors have focused on double-row knotless techniques, in which the fixation of the overall construct relies on each individual anchor to maintain fixation. While these constructs have demonstrated biomechanical strength and clinical durability, each suture anchor represents a potential point of failure for the entire construct due to the crossed stitch anchor configuration. To address this limitation, recent tensionable knotless all-suture anchor designs have been implemented with success due to their smaller size and biomechanical strength. The aim of this technical note is, thus, to describe a technique for proximal hamstring repair using a tensionable knotless all-suture anchor construct that has 5 independent mattress sutures and, in doing so, employs the biomechanical strength of knotless fixation but eliminates the potential single point of failure seen with current knotless suture anchor designs.

A Novel Hierarchical Key Assignment Scheme for Data Access Control in IoT

Hierarchical key assignment scheme is an efficient cryptographic method for hierarchical access control, in which the encryption keys of lower classes can be derived by the higher classes. Such a property is an effective way to ensure the access control security of Internet of Things data markets. However, many researchers on this field cannot avoid potential single point of failure in key distribution, and some key assignment schemes are insecure against collusive attack or sibling attack or collaborative attack. In this paper, we propose a hierarchical key assignment scheme based on multilinear map to solve the multigroup access control in Internet of Things data markets. Compared with previous hierarchical key assignment schemes, our scheme can avoid potential single point of failure in key distribution. Also the central authority of our scheme (corresponding to the data owner in IoT data markets) does not need to assign the corresponding encryption keys to each user directly, and users in each class can obtain the encryption key via only a one-round key agreement protocol. We then show that our scheme satisfies the security of key indistinguishability under decisional multilinear Diffie-Hellman assumption. Finally, comparisons show the efficiency of our scheme and indicates that our proposed scheme can not only resist the potential attacks, but also guarantee the forward and backward security.

Monitoring Network Changes during the 2018 Kīlauea Volcano Eruption

Abstract In the summer of 2018, Kīlauea Volcano underwent one of its most significant eruptions in the past few hundred years. The volcano’s summit and East Rift Zone magma system partially drained, resulting in a series of occasionally explosive partial caldera collapses, and widespread lava flows in the lower East Rift Zone. The Hawaiian Volcano Observatory (HVO) operates a robust permanent monitoring network of about 250 stations, recording a variety of real-time data streams: seismic (short-period, broadband, strong-motion), infrasound, Global Navigation Satellite Systems (GNSS), tilt, camera, laser rangefinder, and gas geochemistry. During the eruption, HVO staff quickly established 35 new temporary monitoring stations, to better constrain evolving volcanic hazards. The partial collapses of the caldera threatened to disrupt important telemetry links in the HVO monitoring network, and a major effort was undertaken in the midst of the eruption crisis to reroute radio telemetry and maintain continuity of data flow. In the process, a new data center was established in Hilo, to mitigate a long-standing potential single point of failure at the HVO facility. Over the course of the eruption from May through August, lava, ashfall, wildfire, and cliff collapse destroyed or disabled 36 stations. Thousands of earthquakes damaged the main HVO facility at Uēkahuna Bluff, causing staff to evacuate the building and relocate observatory operations in the midst of the eruption response, adding more complexity to the response effort. Throughout these events, the HVO team maintained the monitoring network, provided timely information to the public and emergency managers, and collected valuable scientific data to better understand Kīlauea Volcano.

Hazard analysis for identifying common cause failures of digital safety systems using a redundancy-guided systems-theoretic approach

Replacing the existing aging analog instrumentation and control (I&C) systems with modern safety control and protection, digital technology offers one of the foremost means of performance improvements and cost reductions for the existing nuclear power plants (NPPs). However, the qualification of digital I&C systems remains a challenge, especially considering the issue of software common-cause failures (CCFs), which are difficult to address. With the application and upgrades of advanced digital I&C systems, software CCFs have become a potential threat to plant safety because most redundant designs use similar digital platforms or software in the operating and application systems. With complex designs of multilayer redundancy to meet the single-failure criterion, digital I&C safety systems (e.g., engineered safety-features actuation system [ESFAS]) are of a particular concern in the U.S. Nuclear Regulatory Commission (NRC) licensing procedures. This paper applies a modularized approach to conduct redundancy-guided systems-theoretic hazard analysis for an advanced digital ESFAS with multilevel redundancy designs. Systematic methods and risk-informed tools are incorporated to address both hardware and software CCFs, which provide guidance to eliminate the causal factors of potential single points of failure in the design of digital safety systems in advanced plant designs.

The Good, the Bad, and the Ethical Implications of Bridging Blockchain and Multi-Agent Systems

The agent based approach is a well established methodology to model distributed intelligent systems. Multi-Agent Systems (MAS) are increasingly employed in applications dealing with safety and information critical tasks (e.g., in eHealth, financial, and energy domains). Therefore, transparency and the trustworthiness of the agents and their behaviors must be enforced. For example, employing reputation based mechanisms can promote the development of trust. Nevertheless, besides recent early stage studies, the existing methods and systems are still unable to guarantee the desired accountability and transparency adequately. In line with the recent trends, we advocate that combining blockchain technology (BCT) and MAS can achieve the distribution of the trust, removing the need for trusted third parties (TTP), potential single points of failure. This paper elaborates on the notions of trust, BCT, MAS, and their integration. Furthermore, to attain a trusted environment, this manuscript details the design and implementation of a system reconciling MAS (based on the Java Agent DEvelopment Framework (JADE)) and BTC (based on Hyperledger Fabric). In particular, the agents’ interactions, computation, tracking the reputation, and possible policies for disagreement-management are implemented via smart contracts and stored on an immutable distributed ledger. The results obtained by the presented system and similar solutions are also discussed. Finally, ethical implications (i.e., opportunities and challenges) are elaborated before concluding the paper.

THOR: A framework to build an advanced metering infrastructure resilient to DAP failures in smart grids

Abstract Smart Grids represent an evolution of the currently deployed power transmission and distribution systems. It implements a bidirectional data and energy flow infrastructure, which enables new important applications, such as distributed generation, remote metering and demand response. These applications require that a control center collects data from and sends commands to smart meters on the consumer premises. The communication between the control center and smart meters is performed through a gateway, called Data Aggregation Point (DAP). The interconnection of smart meters and DAPs results in an Advanced Metering Infrastructure (AMI), which is a key component of Smart Grids. Because a DAP is a potential single point of failure, the AMI must be implemented in such a way that each smart meter can reach the control center through multiple DAPs. In this work, we propose THOR, a framework that takes advantage of DAP redundancy to improve AMI reliability in case of DAP failures. In addition, we also propose the MultiDAP Selection Algorithm (MDSA) as an efficient implementation of THOR. Simulations results show that MDSA is able to guarantee the delivery of nearly 100% of all sent messages, without imposing significant message delay penalties.

A Route Optimized Distributed IP-Based Mobility Management Protocol for Seamless Handoff across Wireless Mesh Networks

A Wireless Mesh Network (WMN) can provide Internet connectivity to end users through heterogenous access network technologies. However, the mobility of mobile nodes across these access networks in WMNs results in service disruption. Existing mobility management protocols are designed for single hop networks and are centralized in nature. A Distributed IP-based Mobility Management Protocol (DIMMP) is proposed in this paper that provides seamless mobility with service continuation for mobile nodes when they roam across WMNs. Instead of relying on a centralized mobility anchor, the mobility functionality is distributed at multiple nodes in the WMN, in order to reduce the chances of potential single point of failure. The proposed protocol manages both types of mobilities i.e. intra-WMN and inter-WMN and uses a new enhanced route optimization procedure. Simulation results show that this work has contributed by improving the performance of handoff procedure with respect to handoff latency, packet loss and signalling overhead, as compared to the existing protocols.

Distributed Largest Eigenvalue-Based Spectrum Sensing Using Diffusion LMS

In this paper, we propose a distributed detection scheme for cognitive radio (CR) networks, based on the largest eigenvalues (LEs) of adaptively estimated correlation matrices (CMs), assuming that the primary user signal is temporally correlated. The proposed algorithm is fully distributed, thereby avoiding the potential single point of failure that a fusion center would imply. Different forms of diffusion least mean square algorithms are used for estimating and averaging the CMs over the CR network for the LE detection and the resulting estimation performance is analyzed using a common framework. In order to obtain analytic results on the detection performance, the exact distribution of the CM estimates are approximated by a Wishart distribution, by matching the moments. The theoretical findings are verified through simulations.

Rotated Logging Storage Architectures for Data Centers: Models and Optimizations

We propose Ro tated Lo gging (RoLo), a new logging architecture for parallel disk-based mirrored storage systems for enhanced energy efficiency, which is one of the key concerns in modern data centers. By spreading destaging I/O activities among short idle time slots and proactively reclaiming the stale logging space, RoLo rotates loggers among a logical logging space pool formed collectively from the free storage space available among mirrored disks. We develop three flavors of RoLo, that is, RoLo-P/R/E, to emphasize performance, reliability, and energy efficiency respectively. Without the extra dedicated log disks and the corresponding centralized destaging, RoLo eliminates the additional hardware and energy costs, potential single point of failure and performance bottleneck. Furthermore, RoLo-P/R/E, applied to specific scenes correctly, can prolong the lifecycle of the disks and improve the system's energy efficiency by reducing the disk spin up/down frequency. We propose RoLo-S to further alleviate the performance bottleneck and energy consumption caused by frequent disk head seeks in on-duty logger disks. We have implemented RoLo and RoLo-S on real disk systems. Extensive trace-driven evaluations demonstrate the advantages of the three RoLo schemes over both a RAID10 system with centralized logging architecture and a typical RAID10 system, and the advantages of RoLo-S over RoLo.