4,661 research outputs found

    Creation and detection of hardware trojans using non-invasive off-the-shelf technologies

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    As a result of the globalisation of the semiconductor design and fabrication processes, integrated circuits are becoming increasingly vulnerable to malicious attacks. The most concerning threats are hardware trojans. A hardware trojan is a malicious inclusion or alteration to the existing design of an integrated circuit, with the possible effects ranging from leakage of sensitive information to the complete destruction of the integrated circuit itself. While the majority of existing detection schemes focus on test-time, they all require expensive methodologies to detect hardware trojans. Off-the-shelf approaches have often been overlooked due to limited hardware resources and detection accuracy. With the advances in technologies and the democratisation of open-source hardware, however, these tools enable the detection of hardware trojans at reduced costs during or after production. In this manuscript, a hardware trojan is created and emulated on a consumer FPGA board. The experiments to detect the trojan in a dormant and active state are made using off-the-shelf technologies taking advantage of different techniques such as Power Analysis Reports, Side Channel Analysis and Thermal Measurements. Furthermore, multiple attempts to detect the trojan are demonstrated and benchmarked. Our simulations result in a state-of-the-art methodology to accurately detect the trojan in both dormant and active states using off-the-shelf hardware

    Industrial networks and IIoT: Now and future trends

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    Connectivity is the one word summary for Industry 4.0 revolution. The importance of Internet of Things (IoT) and Industrial IoT (IIoT) have been increased dramatically with the rise of industrialization and industry 4.0. As new opportunities bring their own challenges, with the massive interconnected devices of the IIoT, cyber security of those networks and privacy of their users have become an important aspect. Specifically, intrusion detection for industrial networks (IIoT) has great importance. For instance, it is a key factor in improving the safe operation of the smart grid systems yet protecting the privacy of the consumers at the same time. In the same manner, data streaming is a valid option when the analysis is to be pushed from the cloud to the fog for industrial networks to provide agile response, since it brings the advantage of fast action on intrusion detection and also can buy time for intrusion mitigation. In order to dive deep in industrial networks, basic ground needs to be settled. Hence, this chapter serves in this manner, by presenting basic and emerging technologies along with ideas and discussions: First, an introduction of semiconductor evolution is provided along with the up-to-date hi-tech wired/wireless communication solutions for industrial networks. This is followed by a thorough representation of future trends in industrial environments. More importantly, enabling technologies for industrial networks is also presented. Finally, the chapter is concluded with a summary of the presentations along with future projections of IIoT networks

    Creation and detection of hardware trojans using non-invasive off-the-shelf technologies

    Get PDF
    As a result of the globalisation of the semiconductor design and fabrication processes, integrated circuits are becoming increasingly vulnerable to malicious attacks. The most concerning threats are hardware trojans. A hardware trojan is a malicious inclusion or alteration to the existing design of an integrated circuit, with the possible effects ranging from leakage of sensitive information to the complete destruction of the integrated circuit itself. While the majority of existing detection schemes focus on test-time, they all require expensive methodologies to detect hardware trojans. Off-the-shelf approaches have often been overlooked due to limited hardware resources and detection accuracy. With the advances in technologies and the democratisation of open-source hardware, however, these tools enable the detection of hardware trojans at reduced costs during or after production. In this manuscript, a hardware trojan is created and emulated on a consumer FPGA board. The experiments to detect the trojan in a dormant and active state are made using off-the-shelf technologies taking advantage of different techniques such as Power Analysis Reports, Side Channel Analysis and Thermal Measurements. Furthermore, multiple attempts to detect the trojan are demonstrated and benchmarked. Our simulations result in a state-of-the-art methodology to accurately detect the trojan in both dormant and active states using off-the-shelf hardwar

    ENHANCING THE OPERATIONAL RESILIENCE OF CYBER- MANUFACTURING SYSTEMS (CMS) AGAINST CYBER-ATTACKS

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    Cyber-manufacturing systems (CMS) are interconnected production environments comprised of complex and networked cyber-physical systems (CPS) that can be instantiated across one or many locations. However, this vision of manufacturing environments ushers in the challenge of addressing new security threats to production systems that still contain traditional closed legacy elements. The widespread adoption of CMS has come with a dramatic increase in successful cyber-attacks. With a myriad of new targets and vulnerabilities, hackers have been able to cause significant economic losses by disrupting manufacturing operations, reducing outgoing product quality, and altering product designs. This research aims to contribute to the design of more resilient cyber-manufacturing systems. Traditional cybersecurity mechanisms focus on preventing the occurrence of cyber-attacks, improving the accuracy of detection, and increasing the speed of recovery. More often neglected is addressing how to respond to a successful attack during the time from the attack onset until the system recovery. We propose a novel approach that correlates the state of production and the timing of the attack to predict the effect on the manufacturing key performance indicators. Then a real-time decision strategy is deployed to select the appropriate response to maintain availability, utilization efficiency, and a quality ratio above degradation thresholds until recovery. Our goal is to demonstrate that the operational resilience of CMS can be enhanced such that the system will be able to withstand the advent of cyber-attacks while remaining operationally resilient. This research presents a novel framework to enhance the operational resilience of cyber-manufacturing systems against cyber-attacks. In contrast to other CPS where the general goal of operational resilience is to maintain a certain target level of availability, we propose a manufacturing-centric approach in which we utilize production key performance indicators as targets. This way we adopt a decision-making process for security in a way that is aligned with the operational strategy and bound to the socio-economic constraints inherent to manufacturing. Our proposed framework consists of four steps: 1) Identify: map CMS production goals, vulnerabilities, and resilience-enhancing mechanisms; 2) Establish: set targets of performance in production output, scrap rate, and downtime at different states; 3) Select: determine which mechanisms are needed and their triggering strategy, and 4) Deploy: integrate into the operation of the CMS the selected mechanisms, threat severity evaluation, and activation strategy. Lastly, we demonstrate via experimentation on a CMS testbed that this framework can effectively enhance the operational resilience of a CMS against a known cyber-attack
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