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Testing cybersecurity techniques for critical infrastructure on real-world setups is economically infeasible and lacks flexibility. A study presents a testbed for water infrastructures capable of accurately assessing the effectiveness of cybersecurity solutions to address this challenge. The study has exploited the testbed to investigate monitoring systems’ reactions in the presence of physical and cyber issues. A comparison between a model-based fault diagnosis (FD) system with a network anomaly detector (NAD) has been provided. The experimental stage has stressed the consideration that wanted to be emphasized where the control theory world has to merge with the network security one in order to provide overall cyber–physical security for critical infrastructure (CI) scenarios.

This paper concerns the mathematical evaluation of sperm quality as examined by electron microscopy. Proceeding with a Bayesian technique, we have developed a formula considering all statistical possibilities for defects of the examined sperm to be present in a sperm cell, the total number of affected spermatozoa, and, as consequence, that of sperm devoid of defects, also considering the probability of association characteristics of some of them. The formula has been studied in three applications. The first concerns the number of healthy spermatozoa present in ejaculates of fertile men. We have found an enormous variability, but we have observed that the minimal number of spermatozoa free of defects assuring a normal fertility seems to be a little higher than 2 x 10(6). The second and third examples concern varicocele and assisted fertilization. In both cases the formula allows a precise simultaneous evaluation of the totality of studied characters and a determination of the number of spermatozoa free from defects. This comparative analysis shows that the formula is sufficiently sensitive to distinguish the different degrees of the varicocele condition and the various possibilities of fertility power in cases of natural or artificial insemination. In this way we will easily control the level of improvement of sperm quality in cases of varicocele treated pharmacologically or surgically, or we will better predict the success of artificial insemination.

In this paper, a highly-configurable network anomaly detection system for Critical Infrastructure scenarios is presented. The Mininet virtual machine environment has been used in this framework to simulate an Industrial Control System network and to replicate both physical and cyber components. Finally, a cyber-attack has been implemented for showing both the effectiveness and capability of the proposed network security system.

The interaction among networking, sensing, and control in the modern industry results in a variety of new devices used in many sectors such as health, energy distribution, and transportation. The on-going tendency of exploiting automation and data exchange in manufacturing technologies leads to the Industry 4.0. The fourth industrial revolution deals with Cyber-Physical Systems, the Internet of Things, cloud computing, and cognitive computing converging towards the Industrial Internet of Things. To be successful, this new era requires innovative paradigms to ensure the security of provided services and connected systems. In the industrial field, the problem gets more complex due to the need of protecting a large attack surface while guaranteeing the availability of the systems and the real-time response to the presence of threats. In this chapter, we perform an analysis of the existing industrial threats and we present a distributed intrusion detection methodology to deal with attacks affecting the Industrial Internet of Things scenarios.

Industry 4.0 advent opens several cyber-threats scenarios originally designedfor classic information technology, drawing the attention to serious risks for themodern industrial control networks. To cope with this problem, in this paper weaddress the security issues related to covert channels applied to industrial networks,identifying the new vulnerability points when information technologies convergewith operational technologies such as edge computing infrastructures. Specifically,we define two signaling strategies where we exploit the Modbus/TCP protocol astarget to set up a covert channel. Once the threat channel is established, passiveand active offensive methodologies are further exploited by implementing and testingthem on a real Industrial Internet of Things testbed. The experimental resultshighlight the potential damage of such specific threats and the easy extrapolationof the attacks to other types of channels in order to show the new risks for the Industry4.0. Related to this, we discuss some countermeasures offering an overviewof possible mitigation and defensive measures.

Complex and heterogeneous systems characterize the Industry 4.0. Due to the Information Technology (IT) convergence towards the Operational Technology (OT), the development of innovative cyber-physical security tools represents a milestone for the Industrial Control Systems (ICSs) protection. In this context, honeypots are systems used as decoys to detect and analyze malicious actions. However, industrial networks require specific honeypot development capabilities. In this work, we present MimePot, a cyber-physical honeypot conceived for industrial control networks. Compared to classic honeypots, MimePot offers a model-based approach: it is able to simulate physical processes to lure skilled attackers targeting industrial plants. Moreover, MimePot uses the Software Defined Networking (SDN) technology to provide a consistent future proof security approach. We demonstrate the usefulness of MimePot performing data integrity attacks against a water distribution system in a simulated environment.