The issue of a low minority class identification rate caused by data imbalance in anomaly detection tasks is addressed by the proposal of a GAN-SR-based intrusion detection model for industrial control systems. First, to correct the imbalance of minority classes in the dataset, a generative adversarial network (GAN) processes the dataset to reconstruct new minority class training samples accordingly. Second, high-dimensional feature extraction is completed using stacked asymmetric depth self-encoder to address the issues of low reconstruction error and lengthy training times. After that, a random forest (RF) decision tree is built, and intrusion detection is carried out using the features that SNDAE retrieved. According to experimental validation on the UNSW-NB15, SWaT and Gas Pipeline datasets, the GAN-SR model outperforms SNDAE-SVM and SNDAE-KNN in terms of detection performance and stability.

Industrial networks need to provide reliable communication services, usually in a redundant transmission (RT) manner. In the past few years, several device-redundancy-based, layer 2 solutions have been proposed. However, with the evolution of industrial networks to the Industrial Internet, these methods can no longer work properly in the non-redundancy, layer 3 environments. In this paper, an SDN-based reliable communication framework is proposed for the Industrial Internet. It can provide reliable communication guarantees for mission-critical applications while servicing non-critical applications in a best-effort transmission manner. Specifically, it first implements an RT-based reliable communication method using the Industrial Internet's link-redundancy feature. Next, it presents a redundant synchronization mechanism to prevent end systems from receiving duplicate data. Finally, to maximize the number of critical flows in it (an NP-hard problem), two ILP-based routing & scheduling algorithms are also put forward. These two algorithms are optimal (Scheduling with Unconstrained Routing, SUR) and suboptimal (Scheduling with Minimum length Routing, SMR). Numerous simulations are conducted to evaluate its effectiveness. The results show that it can provide reliable, duplicate-free services to end systems. Its reliable communication method performs better than the conventional best-effort transmission method in terms of packet delivery success ratio in layer 3 networks. In addition, its scheduling algorithm, SMR, performs well on the experimental topologies (with average quality of 93% when compared to SUR), and the time overhead is acceptable.

Manufacturers are coping with increasing pressures in quality, cost and efficiency as more and more industries are moving from traditional setup to industry 4.0 based digitally transformed setup due to its numerous playbacks. Within the manufacturing domain organizational structures and processes are complex, therefore adopting industry 4.0 and finding an optimized re-engineered business process is difficult without using a systematic methodology. Authors have developed Business Process Re-engineering (BPR) and Business Process Optimization (BPO) methods but no consolidated methodology have been seen in the literature that is based on industry 4.0 and incorporates both the BPR and BPO. We have presented a consolidated and systematic re-engineering and optimization framework for a manufacturing industry setup. The proposed framework performs Evolutionary Multi-Objective Combinatorial Optimization using Multi-Objective Genetic Algorithm (MOGA). An example process from an aircraft manufacturing factory has been optimized and re-engineered with available set of technologies from industry 4.0 based on the criteria of lower cost, reduced processing time and reduced error rate. At the end to validate the proposed framework Business Process Model and Notation (BPMN) is used for simulations and perform comparison between AS-IS and TO-BE processes as it is widely used standard for business process specification. The proposed framework will be used in converting an industry from traditional setup to industry 4.0 resulting in cost reduction, increased performance and quality.

Real-time and scalable multicast services are of paramount importance to Industrial Internet of Things (IIoT) applications. To realize these services, the multicast algorithm should, on the one hand, ensure the maximum delay of a multicast session not exceeding its upper delay bound. On the other hand, the algorithm should minimize session costs. As an emerging networking paradigm, Software-defined Networking (SDN) can provide a global view of the network to multicast algorithms, thereby bringing new opportunities for realizing the desired multicast services in IIoT environments. Unfortunately, existing SDN-based multicast (SDM) algorithms cannot meet the real-time and scalable requirements simultaneously. Therefore, in this paper, we focus on SDM algorithm design for IIoT environments. To be specific, the paper first converts the multicast tree construction problem for SDM in IIoT environments into a delay-bounded least-cost shared tree problem and proves that it is an NP-complete problem. Then, the paper puts forward a shared tree (ST) algorithm called SDM4IIoT to compute suboptimal solutions to the problem. The algorithm consists of five steps: 1) construct a delay-optimal shared tree; 2) divide the tree into a set of subpaths and a subtree; 3) optimize the cost of each subpath by relaxing the delay constraint; 4) optimize the subtree cost in the same manner; 5) recombine them into a shared tree. Simulation results show that the algorithm can provide real-time support that other ST algorithms cannot. In addition, it can achieve good scalability. Its cost is only 20.56% higher than the cost-optimal ST algorithm. Furthermore, its computation time is also acceptable. The algorithm can help to realize real-time and scalable multicast services for IIoT applications.

Blockchain is one of the prominent rapidly used technology in the last decade in various applications. In recent years, many researchers explored the capabilities of blockchain in smart IoT to address various security challenges. Integration of IoT and blockchain solves the security problems but scalability still remains a huge challenge. To address this, various AI techniques can be applied in the blockchain IoT framework, thus providing an efficient information system. In this survey, various works pertaining to the domains which integrate AI, IoT and Blockchain has been explored. Also, this article discusses potential industrial use cases on fusion of blockchain, AI and IoT applications and its challenges.

Vision systems are widely adopted in industrial fields for monitoring and automation. As a typical example, industrial vision systems are extensively implemented in vibrator parts feeder to ensure orientations of parts for assembling are aligned and disqualified parts are eliminated. An efficient parts orientation recognition and counting method is thus critical to adopt. In this paper, an integrated method for fast parts counting and orientation recognition using industrial vision systems is proposed. Original 2D spatial image signal of parts is decomposed to 1D signal with its temporal variance, thus efficient recognition and counting is achievable, feeding speed of each parts is further leveraged to elaborate counting in an adaptive way. Experiments on parts of different types are conducted, the experimental results revealed that our proposed method is both more efficient and accurate compared to other relevant methods.

The flexibility of wireless communication makes it more and more widely used in industrial scenarios. To satisfy the strict real-time requirements of industry, various wireless methods especially based on the time division multiple access protocol have been introduced. In this work, we first conduct a mathematical analysis of the network model and the problem of minimum packet loss. Then, an optimal Real-time Scheduling algorithm based on Backtracking method (RSBT) for industrial wireless sensor networks is proposed; this yields a scheduling scheme that can achieve the lowest network packet loss rate. We also propose a suboptimal Real-time Scheduling algorithm based on Urgency and Concurrency (RSUC). Simulation results show that the proposed algorithms effectively reduce the rate of the network packet loss and the average response time of data flows. The real-time performance of the RSUC algorithm is close to optimal, which confirms the computation efficiency of the algorithm.

Since cyber attacks such as cyberterrorism against Industrial Control Systems (ICSs) and cyber espionage against companies managing them have increased, the techniques to detect anomalies in early stages are required. To achieve the purpose, several studies have developed anomaly detection methods for ICSs. In particular, some techniques using packet flow regularity in industrial control networks have achieved high-accuracy detection of attacks disrupting the regularity, i.e. normal behaviour, of ICSs. However, these methods cannot identify scanning attacks employed in cyber espionage because the probing packets assimilate into a number of normal ones. For example, the malware called Havex is customised to clandestinely acquire information from targeting ICSs using general request packets. The techniques to detect such scanning attacks using widespread packets await further investigation. Therefore, the goal of this study was to examine high performance methods to identify anomalies even if elaborate packets to avoid alert systems were employed for attacks against industrial control networks. In this paper, a novel detection model for anomalous packets concealing behind normal traffic in industrial control networks was proposed. For the proposal of the sophisticated detection method, we took particular note of packet flow regularity and employed the Markov-chain model to detect anomalies. Moreover, we regarded not only original packets but similar ones to them as normal packets to reduce false alerts because it was indicated that an anomaly detection model using the Markov-chain suffers from the ample false positives affected by a number of normal, irregular packets, namely noise. To calculate the similarity between packets based on the packet flow regularity, a vector representation tool called word2vec was employed. Whilst word2vec is utilised for the culculation of word similarity in natural language processing tasks, we applied the technique to packets in ICSs to calculate packet similarity. As a result, the Markov-chain with word2vec model identified scanning packets assimulating into normal packets in higher performance than the conventional Markov-chain model. In conclusion, employing both packet flow regularity and packet similarity in industrial control networks contributes to improving the performance of anomaly detection in ICSs.

As advances in networking technology help to connect industrial control networks with the Internet, the threat from spammers, attackers and criminal enterprises has also grown accordingly. However, traditional Network Intrusion Detection System makes significant use of pattern matching to identify malicious behaviors and have bad performance on detecting zero-day exploits in which a new attack is employed. In this paper, a novel method of anomaly detection in industrial control network is proposed based on RNN-GBRBM feature decoder. The method employ network packets and extract high-quality features from raw features which is selected manually. A modified RNN-RBM is trained using the normal traffic in order to learn feature patterns of the normal network behaviors. Then the test traffic is analyzed against the learned normal feature pattern by using osPCA to measure the extent to which the test traffic resembles the learned feature pattern. Moreover, we design a semi-supervised incremental updating algorithm in order to improve the performance of the model continuously. Experiments show that our method is more efficient in anomaly detection than other traditional approaches for industrial control network.

In the past, the security of industrial control systems was guaranteed by their obscurity. However, as devices of industrial control systems became more varied and interaction between these devices became necessary, effective management systems for such networks emerged. This triggered the need for cyber-physical systems that connect industrial control system networks and external system networks. The standards for the protocols in industrial control systems explain security functions in detail, but many devices still use nonsecure communication because it is difficult to update existing equipment. Given this situation, a number of studies are being conducted to detect attacks against industrial control system protocols, but these studies consider only data payloads without considering the case that industrial control systems' availability is infringed owing to packet reassembly failures. Therefore, with regard to the DNP3 protocol, which is used widely in industrial control systems, this paper describes attacks that can result in packet reassembly failures, proposes a countermeasure, and tests the proposed countermeasure by conducting actual attacks and recoveries. The detection of a data payload should be conducted after ensuring the availability of an industrial control system by using this type of countermeasure.

Cyber-attacks and cybersecurity used to be the issues for those who use Internet and computers. The issues, however, are expanding to anyone who does not even use them directly. The society is gradually and heavily depending on networks and computers. They are not closed within a cyberspace anymore and having interaction with our real world with sensors and actuators. Such systems are known as CPS (Cyber Physical Systems), IoT/E (Internet of Things/Everything), Industry 4.0, Industrial Internet, M2M, etc. No matter what they are called, exploitation of any of these systems may cause a serious influence to our real life and appropriate countermeasures must be taken to mitigate the risks. In this paper, cybersecurity in ICS (Industrial Control Systems) is reviewed as a leading example of cyber physical security for critical infrastructures. Then as a future aspect of it, IoT security for consumers is explained.

A wideband on-body antenna for a wireless body area network for an Industrial, Scientific, and Medical band is proposed. A wideband characteristic is achieved by combining two zeroth-order resonance (ZOR) modes at adjacent frequencies by controlling the value of the shunt capacitance. The size of the proposed antenna is 0.072λ0 × 0.33λ0, and the measured 10-dB return loss bandwidth is 340MHz (14.3%). In addition, the resonance frequencies operating in the ZOR mode are insensitive to the effects of the human body by virtue of the ZOR characteristic.

In this paper, we consider a problem of simultaneously optimizing a sequence of graphs and a route which exhaustively visits the vertices from each pair of successive graphs in the sequence. This type of problem arises from repetitive routing of grasp-and-delivery robots used in the production of printed circuit boards. The problem is formulated as follows. We are given a metric graph G*=(V*,E*), a set of m+1 disjoint subsets Ci ⊆ V* of vertices with |Ci|=n, i=0,1,...,m, and a starting vertex s ∈ C0. We seek to find a sequence π=(Ci1, Ci2, ..., Cim) of the subsets of vertices and a shortest walk P which visits all (m+1)n vertices in G* in such a way that after starting from s, the walk alternately visits the vertices in Cik-1 and Cik, for k=1,2,...,m (i0=0). Thus, P is a walk with m(2n-1) edges obtained by concatenating m alternating Hamiltonian paths between Cik-1 and Cik, k=1,2,...,m. In this paper, we show that an approximate sequence of subsets of vertices and an approximate walk with at most three times the optimal route length can be found in polynomial time.

The research on body-centric wireless communications (BCWCs) is becoming very hot because of numerous applications, especially the application of E-health systems. Therefore, a small multi-band and low-profile planar inverted-F antenna (PIFA) with tuning function is presented for BCWCs in this paper. In order to achieve multi-band operation, there are two branches in the antenna: the longer branch low frequency band (950–956 MHz), and the shorter branch with a varactor diode embedded for high frequency bands. By supplying different DC voltages, the capacitance of the varactor diode varies, so the resonant frequency can be tuned without changing the dimension of the antenna. While the bias is set at 6 V and 14 V, WiMAX and ISM bands can be covered, respectively. From the radiation patterns, at 950 MHz, the proposed antenna is suitable for on-body communications, and in WiMAX and ISM bands, they are suitable for both on-body and off-body communications.

In this manuscript, a layered macro/micro diversity scheme is introduced at the receiver side of a MIMO STBC wireless control system under fading and shadowing environment. The combination of the outputs of micro diversity is based on soft-decision values, while the macro diversity branches are combined based on hard decision values. As a measure of the reliability of the system, the outage probability of frame-error rate is employed. The performance of the proposed system is analytically and numerically evaluated and the impact of the macro diversity in the outage probability is clarified.

Visual defects, called mura in the field, sometimes occur during the manufacturing of the flat panel liquid crystal displays. In this paper we propose an automatic inspection method that reliably detects and quantifies TFT-LCD region-mura defects. The method consists of two phases. In the first phase we segment candidate region-muras from TFT-LCD panel images using the modified regression diagnostics and Niblack's thresholding. In the second phase, based on the human eye's sensitivity to mura, we quantify mura level for each candidate, which is used to identify real muras by grading them as pass or fail. Performance of the proposed method is evaluated on real TFT-LCD panel samples.

In industrial assembly lines, seam sealing is a painting process used for making watertight seals or for preventing rusting. In the process, sealant is painted on seams located at the joints of pressed metal parts. We developed a sealing robot system that adjusts the sealing gun motion adaptively to the seam position sensed by a range sensor (a scanning laser rangefinder which senses profile range data). In this paper, we propose a high-speed and highly reliable algorithm for seam position computation from the sensed profile range data around the seam. It is proved experimentally that the sealing robot system used with the developed algorithm is very effective, especially for reducing wasted sealant.

This paper presents a new internal image representation, in which the scene is encoded into a three-intensity-level image. This representation is generated by Laplacian-Gaussian filtering followed by dual-thresholding. We refer to this imege as three-level broad-edge representation. It supresses the high frequency noise and shading in the image and encodes the sign of relative intensity of a pixel compared with surrounding region. Image model search based on cross correlation using this representation is as reliable as the one based on gray normalized correlation, while it reduces the computational cost by 50 times. We examined the reliability and realtime performance of this method when it is applied to an industrial object recognition task. Our prototype system achieves 3232 image model search from the 128128 pixel area in 2 milli-seconds with a 9 MHz pixel clock image processor. This speed is fast enough for searching and tracking a single object at video frame rate.

Industrial radio control systems require a high degree of safety and reliability even in operating environments where harsh interference conditions exist. In order to implement Spread Spectrum (SS) modulation techniques in industrial radio control systems, a hybrid Direct Sequence/Frequency Hopping (DS/FH) system with high speed synchronization capability was designed, implemented and evaluated. In this system, a digital matched filter was utilized for despreading the DS signal. By manipulating the despread signal and sensing the correlation peak, the frequency hopping circuit can operate without a special synchronizing circuit. The focus of this report is on an engineering sample created for the 900MHz band available as an ISM band in the U.S. In this sample, error correction code was integrated with the hybrid DS/FH which gives the system excellent narrow-band interference rejection properties and Code Division Multiple Access (CDMA) capabilities.