Biblio

[Purpose/meaning] In this paper, a unified scheme based on blockchain technology to realize the three modules of intellectual property confirmation, utilization, and protection of rights at the application layer is constructed, to solve the problem of unbalanced and inadequate resource distribution and development level in the field of industrial intellectual property. [Method/process] Based on the application of the core technology of blockchain in the field of intellectual property, this paper analyzes the pain points in the current field of intellectual property, and selects matching blockchain types according to the protection of intellectual property and the different decisions involved in the transaction process, to build a heterogeneous multi-chain model based on blockchain technology. [Conclusion] The heterogeneous multi-chain model based on Polkadot[1] network is proposed to realize the intellectual property protection scheme of a heterogeneous multi-chain model, to promote collaborative design and product development between regions, and to make up for the shortcomings of technical exchange, and weaken the phenomenon of "information island" in a certain extent. [Limitation/deficiency] The design of smart contracts in the field of intellectual property, the development of cross-chain protocols, and the formulation of national standards for blockchain technology still need to be developed and improved. At the same time, the intellectual property protection model designed in this paper needs to be verified in the application of practical cases.

In Production System Engineering (PSE), domain experts from different disciplines reuse assets such as products, production processes, and resources. Therefore, PSE organizations aim at establishing reuse across engineering disciplines. However, the coordination of multi-disciplinary reuse tasks, e.g., the re-validation of related assets after changes, is hampered by the coarse-grained representation of tasks and by scattered, heterogeneous domain knowledge. This paper introduces the Multi-disciplinary Reuse Coordination (MRC) artifact to improve task management for multi-disciplinary reuse. For assets and their properties, the MRC artifact describes sub-tasks with progress and result states to provide references for detailed reuse task management across engineering disciplines. In a feasibility study on a typical robot cell in automotive manufacturing, we investigate the effectiveness of task management with the MRC artifact compared to traditional approaches. Results indicate that the MRC artifact is feasible and provides effective capabilities for coordinating multi-disciplinary re-validation after changes.

In Production System Engineering (PSE), domain experts aim at effectively and efficiently analyzing and mitigating information security risks to product and process qualities for manufacturing. However, traditional security standards do not connect security analysis to the value stream of the production system nor to production quality requirements. This paper aims at facilitating security analysis for production quality already in the design phase of PSE. In this paper, we (i) identify the connection between security and production quality, and (ii) introduce the Production Security Network (PSN) to efficiently derive reusable security requirements and design patterns for PSE. We evaluate the PSN with threat scenarios in a feasibility study. The study results indicate that the PSN satisfies the requirements for systematic security analysis. The design patterns provide a good foundation for improving the communication of domain experts by connecting security and quality concerns.

Artificial intelligence (AI) has been successfully employed in industries for decades, beginning with the invention of expert systems in the 1960s and continuing through the present ubiquity of deep learning. Data-driven AI solutions have grown increasingly common as a means of supporting ever-more complicated industrial processes owing to the accessibility of affordable computer and storage infrastructure. Despite recent optimism, implementing AI to smart industrial applications still offers major difficulties. The present paper gives an executive summary of AI methodologies with an emphasis on deep learning before detailing unresolved issues in AI safety, data privacy, and data quality — all of which are necessary for completely automated commercial AI systems.

This paper reports on the advanced assembly technology for small chip size of Fan-out WLP(FO-WLP) using high expansion tape. In a preceding paper, we reported that we have developed new tape expansion machine which can expand tape in four directions individually. Using this expansion machine device, we have developed high expansion tape which can get enough chip distance after expansion. Our expansion technology provides both high throughput and high placement accuracy. These previous studies have been evaluated using 3 mm x 3 mm chips assuming an actual FO-WLP device. Since our process can be handled by wafer size, smaller chip size improves throughput than larger chip size. In this study, we evaluate with 0.6 mm x 0.3 mm chip size and investigate tape characteristics required for small chip size expansion. By optimizing adhesive thickness and composition of adhesive, we succeed in developing high expansion tape for small chip size with good expandability and no adhesive residue on the expanded chip. We indicate that our proposal process is also effective for small chip size of FO-WLP.

The Internet of Things is an emerging technology for recent marketplace. In IoT, the heterogeneous devices are connected through the medium of the Internet for seamless communication. The devices used in IoT are resource-constrained in terms of memory, power and processing. Due to that, IoT system is unable to implement hi-end security for malicious cyber-attacks. The recent era is all about connecting IoT devices in various domains like medical, agriculture, transport, power, manufacturing, supply chain, education, etc. and thus need to be prevented from attacks and analyzed after attacks for legal action. The legal analysis of IoT data, devices and communication is called IoT forensics which is highly indispensable for various types of attacks on IoT system. This paper will review types of IoT attacks and its preventive measures in cyber security. It will also help in ascertaining IoT forensics and its challenges in detail. This paper will conclude with the high requirement of cyber security in IoT domains with implementation of standard rules for IoT forensics.

Domestic robots and agents are widely sold to the grand public, leading us to ethical issues related to the data harvested by such machines. While users show a general acceptance of these robots, concerns remain when it comes to information security and privacy. Current research indicates that there’s a privacy-security trade-off for better use, but the anthropomorphic and social abilities of a robot are also known to modulate its acceptance and use. To explore and deepen what literature already brought on the subject we examined how users perceived their robot (Replika, Roomba©, Amazon Echo©, Google Home©, or Cozmo©/Vector©) through an online questionnaire exploring acceptance, perceived privacy and security, anthropomorphism, disclosure, perceived intimacy, and loneliness. The results supported the literature regarding the potential manipulative effects of robot’s anthropomorphism for acceptance but also information disclosure, perceived intimacy, security, and privacy.

Swarm robotics is a network based multi-device system designed to achieve shared objectives in a synchronized way. This system is widely used in industries like farming, manufacturing, and defense applications. In recent implementations, swarm robotics is integrated with Blockchain based networks to enhance communication, security, and decentralized decision-making capabilities. As most of the current blockchain applications are based on complex consensus algorithms, every individual robot in the swarm network requires high computing power to run these complex algorithms. Thus, it is a challenging task to achieve consensus between the robots in the network. This paper will discuss the details of designing an effective consensus algorithm that meets the requirements of swarm robotics network.

The Sixth Generation (6G) is currently under development and it is a planned successor of the Fifth Generation (5G). It is a new wireless communication technology expected to have a greater coverage area, significant fast and a higher data rate. The aim of this paper is to examine the literature on challenges and possible solutions of 6G's security, privacy and trust. It uses the systematic literature review technique by searching five research databases for search engines which are precise keywords like “6G,” “6G Wireless communication,” and “sixth generation”. The latter produced a total of 1856 papers, then the security, privacy and trust issues of the 6G wireless communication were extracted. Two security issues, the artificial intelligence and visible light communication, were apparent. In conclusion, there is a need for new paradigms that will provide a clear 6G security solutions.

Cloud Computing (CC) has emerged as an on-demand accessible tool in different practical applications such as digital industry, academics, manufacturing, health sector and others. In this paper different security threats faced by CC are discussed with suitable examples. Moreover, an artificial intelligence based security enabled CC is also discussed based on suitable empirical data. It is found that an artificial neural network (ANN) is an effective system to detect the level of risk factors associated with CC along with mitigating those risk issues with appropriate algorithms. Hence, it provides a desired level of protection against cyber attacks, internal confidential threats and external threat of data theft from a cloud computing system. Levenberg–Marquardt (LMBP) algorithms are also found as a significant tool to estimate the level of security performance around a cloud computing system. ANN is used to improve the performance level of data security across a cloud computing network and make it security enabled to ensure a protected data transmission to clients associated with the system.

The importance of the security of industrial control network has become increasingly prominent. Aiming at the defects of main security protection system in the intelligent manufacturing industrial control network, we propose a security attack risk detection and defense, and emergency processing capability synchronization technology system suitable for the intelligent manufacturing industrial control system. Integrating system control and network security theories, a flexible and reconfigurable system-wide security architecture method is proposed. On the basis of considering the high availability and strong real-time of the system, our research centers on key technologies supporting system-wide security analysis, defense strategy deployment and synchronization, including weak supervision system reinforcement and pattern matching, etc.. Our research is helpful to solve the problem of industrial control network of “old but full of loopholes” caused by the long-term closed development of the production network of important parts, and alleviate the contradiction between the high availability of the production system and the relatively backward security defense measures.

Supply chain plays a significant job in an organization making systems between an organization and its supplier to deliver and disperse items and administrations to the last purchasers. Digitization alludes to the way toward moving physical reports into physical documents. Digitization will make incredible open doors for associations and supply chain rehearses. Numerous associations need to turn out to be progressively “advanced” since they have watched the criticality and value of computerized advances for their development and their own organizations. This research study topic presents a review of the supply chain management digitization practices and dreams with a merged image of digitization and stream of data between the Supplier and Manufacturer chain. Value management, in value analysis, assumes a huge job in a viable Digital Supply Chain Management, it is progressively centered around mechanization, digitizing the procedure, and the coordination and reconciliation of the considerable number of components associated with the supply chain. In view of how value-chain management has developed, it assumes an urgent job in managing the ever-expanding unpredictability in supply chains all inclusive. This study presents an overview of the supply chain management digitization practices and visions with a consolidated picture of digitization and flow of information between the Supplier and Manufacturer chain. This study can be further improved by integrating the latest technology and tools AI and IoT-as a future study.

The ever-increasing cost and complexity of cutting-edge manufacturing and test processes have migrated the semiconductor industry towards a globalized business model. With many untrusted entities involved in the supply chain located across the globe, original intellectual property (IP) owners face threats such as IP theft/piracy, tampering, counterfeiting, reverse engineering, and overproduction. Logic locking has emerged as a promising solution to protect integrated circuits (ICs) against supply chain vulnerabilities. It inserts key gates to corrupt circuit functionality for incorrect key inputs. A logic-locked chip test can be performed either before or after chip activation (becoming unlocked) by loading the unlocking key into the on-chip tamperproof memory. However, both pre-activation and post-activation tests suffer from lower test coverage, higher test cost, and critical security vulnerabilities. To address the shortcomings, we propose LL-ATPG, a logic-locking aware test method that applies a set of valet (dummy) keys based on a target test coverage to perform manufacturing test in an untrusted environment. LL-ATPG achieves high test coverage and minimizes test time overhead when testing the logic-locked chip before activation without sharing the unlocking key. We perform security analysis of LL-ATPG and experimentally demonstrate that sharing the valet keys with the untrusted foundry does not create additional vulnerability for the underlying locking method.

In the theoretical part of the paper, the scope of application of pseudorandom numbers and methods of their generation, as well as methods of statistical testing of pseudorandom sequences (PS) are considered. In the practical part of the work, the quality of PS obtained by Mersenne Twister [1] generator and the cryptographic generator of the RNGCryptoServiceProvider class of the. NET platform is evaluated. Based on the conducted research, the results of testing are obtained, which show that the quality of pseudorandom sequences generated by the cryptographic random number generator is higher than PS generated by Mersenne Twister. Additionally, based on statistical analysis by NIST and TestU01, a study is conducted in an attempt to establish the statistical indistinguishability of sets of empty- and stegocontainers created using a two-dimensional associative masking mechanism [2-4] based on a gamma of at least 500 KB in length. Research work was carried out under the guidance of R.F. Gibadullin, Associate Professor of the Department of Computer Systems of Kazan National Research Technical University named after A.N.Tupolev-KAI.

Recently, with the spread of Internet of Things (IoT) devices, embedded hardware devices have been used in a variety of everyday electrical items. Due to the increased demand for embedded hardware devices, some of the IC design and manufacturing steps have been outsourced to third-party vendors. Since malicious third-party vendors may insert malicious circuits, called hardware Trojans, into their products, developing an effective hardware Trojan detection method is strongly required. In this paper, we propose 25 hardware-Trojan features based on the structure of trigger circuits for machine-learning-based hardware Trojan detection. Combining the proposed features into 11 existing hardware-Trojan features, we totally utilize 36 hardware-Trojan features for classification. Then we classify the nets in an unknown netlist into a set of normal nets and Trojan nets based on the random-forest classifier. The experimental results demonstrate that the average true positive rate (TPR) becomes 63.6% and the average true negative rate (TNR) becomes 100.0%. They improve the average TPR by 14.7 points while keeping the average TNR compared to existing state-of-the-art methods. In particular, the proposed method successfully finds out Trojan nets in several benchmark circuits, which are not found by the existing method.

With the rapid development of Internet of Things technology and sensor networks, large amount of data is facing security challenges in the transmission process. In the process of data transmission, the standardization and authentication of data sources are very important. A digital signature scheme based on bilinear pairing problem is designed. In this scheme, by signing the authorization mechanism, the management node can control the signature process and distribute data. The use of private key segmentation mechanism can reduce the performance requirements of sensor nodes. The reasonable combination of timestamp mechanism can ensure the time limit of signature and be verified after the data is sent. It is hoped that the implementation of this scheme can improve the security of data transmission on the Internet of things environment.

In today’s world, Supervisory Control and Data Acquisition (SCADA) networks have many critical tasks, including managing infrastructure such as power, water, and sewage systems, and controlling automated manufacturing and transportation systems. Securing these systems is crucial. Here we describe a project to design security into an example system using formal specifications. Our example system is a component in a cybersecurity testbed at the University of Cincinnati, which was described in previous work. We also show how a design flaw can be discovered and corrected early in the system development process.

This paper focuses on the typical business scenario of intelligent factory, it includes the manufacturing process, carries out hierarchical security protection, forms a full coverage industrial control security protection network, completes multi-means industrial control security direct protection, at the same time, it utilizes big data analysis, dynamically analyzes the network security situation, completes security early warning, realizes indirect protection, and finally builds a self sensing and self-adjusting industrial network security protection system It provides a reliable reference for the development of intelligent manufacturing industry.

Existing systems allow manufacturers to acquire factory floor data and perform analysis with cloud applications for machine health monitoring, product quality prediction, fault diagnosis and prognosis etc. However, they do not provide capabilities to perform testing of machine tools and associated components remotely, which is often crucial to identify causes of failure. This paper presents a fault diagnosis system in a cyber-physical manufacturing cloud (CPMC) that allows manufacturers to perform diagnosis and maintenance of manufacturing machine tools through remote monitoring and online testing using Machine Tool Communication (MTComm). MTComm is an Internet scale communication method that enables both monitoring and operation of heterogeneous machine tools through RESTful web services over the Internet. It allows manufacturers to perform testing operations from cloud applications at both machine and component level for regular maintenance and fault diagnosis. This paper describes different components of the system and their functionalities in CPMC and techniques used for anomaly detection and remote online testing using MTComm. It also presents the development of a prototype of the proposed system in a CPMC testbed. Experiments were conducted to evaluate its performance to diagnose faults and test machine tools remotely during various manufacturing scenarios. The results demonstrated excellent feasibility to detect anomaly during manufacturing operations and perform testing operations remotely from cloud applications using MTComm.

Digital-Twins simulate physical world objects by creating 'as-is' virtual images in a cyberspace. In order to create a well synchronized digital-twin simulator in manufacturing, information and activities of a physical machine need to be virtualized. Many existing digital-twins stream read-only data of machine sensors and do not incorporate operations of manufacturing machines through Internet. In this paper, a new method of virtualization is proposed to integrate machining data and operations into the digital-twins using Internet scale machine tool communication method. A fully functional digital-twin is implemented in CPMC testbed using MTComm and several manufacturing application scenarios are developed to evaluate the proposed method and system. Performance analysis shows that it is capable of providing data-driven visual monitoring of a manufacturing process and performing manufacturing operations through digital twins over the Internet. Results of the experiments also shows that the MTComm based digital twins have an excellent efficiency.

Blockchain technology has brought a huge paradigm shift in multiple industries, by integrating distributed ledger, smart contracts and consensus protocol under the same roof. Notable applications of blockchain include cryptocurrencies and large-scale multi-party transaction management systems. The latter fits very well into the domain of manufacturing and supply chain management for Integrated Circuits (IC), which, despite several advanced technologies, is vulnerable to malicious practices, such as overproduction, IP piracy and deleterious design modification to gain unfair advantages. To combat these threats, researchers have proposed several ideas like hardware metering, design obfuscation, split manufacturing and watermarking. In this paper, we show, how these issues can be complementarily dealt with using blockchain technology coupled with identity-based encryption and physical unclonable functions, for improved resilience against certain adversarial motives. As part of our proposed blockchain protocol, titled `BLIC', we propose an authentication mechanism to secure both active and passive IC transactions, and a composite consensus protocol designed for IC supply chains. We also present studies on the security, scalability, privacy and anonymity of the BLIC protocol.

With the globalization of manufacturing and supply chains, ensuring the security and trustworthiness of ICs has become an urgent challenge. Split manufacturing (SM) and layout camouflaging (LC) are promising techniques to protect the intellectual property (IP) of ICs from malicious entities during and after manufacturing (i.e., from untrusted foundries and reverse-engineering by end-users). In this paper, we strive for “the best of both worlds,” that is of SM and LC. To do so, we extend both techniques towards 3D integration, an up-and-coming design and manufacturing paradigm based on stacking and interconnecting of multiple chips/dies/tiers. Initially, we review prior art and their limitations. We also put forward a novel, practical threat model of IP piracy which is in line with the business models of present-day design houses. Next, we discuss how 3D integration is a naturally strong match to combine SM and LC. We propose a security-driven CAD and manufacturing flow for face-to-face (F2F) 3D ICs, along with obfuscation of interconnects. Based on this CAD flow, we conduct comprehensive experiments on DRC-clean layouts. Strengthened by an extensive security analysis (also based on a novel attack to recover obfuscated F2F interconnects), we argue that entering the next, third dimension is eminent for effective and efficient IP protection.

Modern large scale technical systems often face iterative changes on their behaviours with the requirement of validated quality which is not easy to achieve completely with traditional testing. Regression verification is a powerful tool for the formal correctness analysis of software-driven systems. By proving that a new revision of the software behaves similarly as the original version of the software, some of the trust that the old software and system had earned during the validation processes or operation histories can be inherited to the new revision. This trust inheritance by the formal analysis relies on a number of implicit assumptions which are not self-evident but easy to miss, and may lead to a false sense of safety induced by a misunderstood regression verification processes. This paper aims at pointing out hidden, implicit assumptions of regression verification in the context of cyber-physical systems by making them explicit using practical examples. The explicit trust inheritance analysis would clarify for the engineers to understand the extent of the trust that regression verification provides and consequently facilitate them to utilize this formal technique for the system validation.

A method to increase the resiliency of in-cone logic locking against the SAT attack is described in this paper. Current logic locking techniques provide protection through the addition of circuitry outside of the original logic cone. While the additional circuitry provides provable security against the SAT attack, other attacks, such as the removal attack, limit the efficacy of such techniques. Traditional in-cone logic locking is not prone to removal attacks, but is less secure against the SAT attack. The focus of this paper is, therefore, the analysis of in-cone logic locking to increase the security against the SAT attack, which provides a comparison between in-cone techniques and newly developed methodologies. A novel algorithm is developed that utilizes maximum fanout free cones (MFFC). The application of the algorithm limits the fanout of incorrect key information. The MFFC based algorithm resulted in an average increase of 61.8% in the minimum number of iterations required to complete the SAT attack across 1,000 different variable orderings of the circuit netlist while restricted to a 5% overhead in area.

This paper describes an approach to overcome the interoperability challenges related to identity management systems supporting cross-collaboration between heterogeneous manufacturing platforms. Traditional identity management systems have shown many weaknesses when it comes to cloud platforms and their federations, from not being able to support a simplified login process, to information disclosure and complexity of implementation in practice. This paper discusses workflows to practically implement federated identity management across the heterogeneous manufacturing platforms and design interoperability at different levels, e.g. at the platform level and at the platform integration level. Our motivation to find the best federated identity management solution for heterogeneous cloud-based platforms is related to practical requirements coming from the ongoing European project eFactory.