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  <doc>
    <id>29700</id>
    <completedYear/>
    <publishedYear>2022</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>596</pageFirst>
    <pageLast>621</pageLast>
    <pageNumber/>
    <edition/>
    <issue>4</issue>
    <volume>3</volume>
    <type>articler</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2022-11-11</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">A Flashback on Control Logic Injection Attacks against Programmable Logic Controllers</title>
    <abstract language="eng">Programmable logic controllers (PLCs) make up a substantial part of critical infrastructures (CIs) and industrial control systems (ICSs). They are programmed with a control logic that defines how to drive and operate critical processes such as nuclear power plants, petrochemical factories, water treatment systems, and other facilities. Unfortunately, these devices are not fully secure and are prone to malicious threats, especially those exploiting vulnerabilities in the control logic of PLCs. Such threats are known as control logic injection attacks. They mainly aim at sabotaging physical processes controlled by exposed PLCs, causing catastrophic damage to target systems as shown by Stuxnet. Looking back over the last decade, many research endeavors exploring and discussing these threats have been published. In this article, we present a flashback on the recent works related to control logic injection attacks against PLCs. To this end, we provide the security research community with a new systematization based on the attacker techniques under three main attack scenarios. For each study presented in this work, we overview the attack strategies, tools, security goals, infected devices, and underlying vulnerabilities. Based on our analysis, we highlight the current security challenges in protecting PLCs from such severe attacks and suggest security recommendations for future research directions.</abstract>
    <parentTitle language="eng">Automation</parentTitle>
    <identifier type="issn">2673-4052</identifier>
    <identifier type="doi">10.3390/automation3040030</identifier>
    <enrichment key="opus.import.date">2022-12-07T10:11:03+00:00</enrichment>
    <enrichment key="opus.source">sword</enrichment>
    <enrichment key="opus.import.user">deepgreen</enrichment>
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    <enrichment key="opus.import.checksum">9125af4f144e2c02a3d6f43a16f08bb4</enrichment>
    <enrichment key="BTU">an der BTU erstellt / created at BTU</enrichment>
    <enrichment key="Publikationsweg">Open Access</enrichment>
    <enrichment key="Fprofil">4 Künstliche Intelligenz und Sensorik / Artificial Intelligence and Sensor Technology</enrichment>
    <author>
      <firstName>Wael</firstName>
      <lastName>Alsabbagh</lastName>
    </author>
    <author>
      <firstName>Peter</firstName>
      <lastName>Langendörfer</lastName>
    </author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>industrial control system</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>programmable logic controller</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>control logic injection attack</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>program injection</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>program modification</value>
    </subject>
    <collection role="institutes" number="1222">FG Systeme</collection>
    <collection role="Import" number="import">Import</collection>
  </doc>
  <doc>
    <id>32629</id>
    <completedYear/>
    <publishedYear>2023</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber>7</pageNumber>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject_ref</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2024-01-26</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Coarse-Grained Control Flow Integrity Check for Processors with Sliding Register Windows</title>
    <parentTitle language="eng">12th Mediterranean Conference on Embedded Computing (MECO)</parentTitle>
    <identifier type="doi">10.1109/MECO58584.2023.10154928</identifier>
    <identifier type="isbn">979-8-3503-2291-0</identifier>
    <identifier type="isbn">979-8-3503-2290-3</identifier>
    <identifier type="issn">2637-9511</identifier>
    <enrichment key="BTU">an der BTU erstellt / created at BTU</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="Publikationsweg">Open Access</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">false</enrichment>
    <enrichment key="Fprofil">4 Künstliche Intelligenz und Sensorik / Artificial Intelligence and Sensor Technology</enrichment>
    <author>
      <firstName>Kai</firstName>
      <lastName>Lehniger</lastName>
    </author>
    <submitter>
      <firstName>Elisabeth</firstName>
      <lastName>Vogel</lastName>
    </submitter>
    <author>
      <firstName>Marcin</firstName>
      <lastName>Aftowicz</lastName>
    </author>
    <author>
      <firstName>Mario</firstName>
      <lastName>Schölzel</lastName>
    </author>
    <author>
      <firstName>Peter</firstName>
      <lastName>Langendörfer</lastName>
    </author>
    <collection role="institutes" number="1222">FG Systeme</collection>
  </doc>
  <doc>
    <id>32631</id>
    <completedYear/>
    <publishedYear>2023</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber>6</pageNumber>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject_ref</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2024-01-26</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Novel Approach to a Plant Inspired Distributed Security Scheme for Wireless Sensor Networks</title>
    <abstract language="eng">Energy efficiency is a key factor for the longevity of wireless sensor networks (WSNs). Most representatives of the plants have evolved to be highly energy-efficient in their survival strategies, despite their limited resources. Plants have to deal with a variety of threats originating from different herbivores and microbial pathogens while handling a number of abiotic stress factors. For plants and WSNs, different defence mechanisms impose different fitness costs and therefore the costs and benefits have to be well-balanced. This way, plants are able to not only conquer a large variety of different attacks but also handle several different simultaneous attacks adequately. To react early and adapt to upcoming threats, plants within a network are capable of signalling each other within a certain distance about ongoing attacks. The biological strategies of plants in terms of signalling and defence, as well as their energy and resource limitations, share significant similarities with WSNs. This study aims to explore these similarities and demonstrates the correspondence between the biological concepts and WSNs. Additionally, we present a novel approach to enhancing security in WSNs through a cooperative distributed security scheme inspired by key factors of plant defence mechanisms, with the goal of reducing the energy constraints and maximising the longevity of the network.</abstract>
    <parentTitle language="eng">12th Mediterranean Conference on Embedded Computing (MECO), Budva, Montenegro, 2023</parentTitle>
    <identifier type="doi">10.1109/MECO58584.2023.10154949</identifier>
    <identifier type="isbn">979-8-3503-2291-0</identifier>
    <identifier type="isbn">979-8-3503-2290-3</identifier>
    <identifier type="issn">2637-9511</identifier>
    <enrichment key="BTU">an der BTU erstellt / created at BTU</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="Publikationsweg">Open Access</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">false</enrichment>
    <enrichment key="Fprofil">4 Künstliche Intelligenz und Sensorik / Artificial Intelligence and Sensor Technology</enrichment>
    <author>
      <firstName>Benjamin</firstName>
      <lastName>Förster</lastName>
    </author>
    <submitter>
      <firstName>Elisabeth</firstName>
      <lastName>Vogel</lastName>
    </submitter>
    <author>
      <firstName>Peter</firstName>
      <lastName>Langendörfer</lastName>
    </author>
    <author>
      <firstName>Thomas</firstName>
      <lastName>Hinze</lastName>
    </author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Wireless sensor networks</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Pathogens</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Embedded computing</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Cyber-physical systems</value>
    </subject>
    <collection role="institutes" number="1222">FG Systeme</collection>
  </doc>
  <doc>
    <id>32632</id>
    <completedYear/>
    <publishedYear>2023</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber>8</pageNumber>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject_ref</type>
    <publisherName>IEEE</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2024-01-26</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">You Are What You Attack: Breaking the Cryptographically-Protected S7 Protocol</title>
    <abstract language="eng">S7 protocol defines an appropriate format for exchanging messages between SIMATIC S7 PLCs and their corresponding engineering software i.e., TIA Portal. Recently, Siemens has provided its newer PLC models and their proprietary S7 protocols with a very developed and sophisticated integrity check mechanism to protect them from various exploits e.g., replay attacks. This paper addresses exactly this point, and investigates the security of the most developed integrity check mechanism that the newest S7CommPlus protocol version implements. Our results showed that the latest S7 PLC models as well as their related protocols are still vulnerable. We found that adversaries can manipulate two hashes that play a significant role in generating keys and bytes for the encryption processes implemented in the S7CommPlus protocol. This allows to reproduce S7 packets and conduct several attacks that eventually impact the operation of the target PLC and the entire physical process it controls. To validate our findings, we test all the attack scenarios presented in this work on a cryptographically protected S7 PLC from the 1500 family which uses the S7CommPlusV3 protocol.</abstract>
    <parentTitle language="eng">19th International Conference on Factory Communication Systems (WFCS), (2023)</parentTitle>
    <identifier type="doi">10.1109/WFCS57264.2023.10144251</identifier>
    <identifier type="isbn">978-1-6654-6432-1</identifier>
    <identifier type="isbn">978-1-6654-6433-8</identifier>
    <identifier type="issn">2835-8414</identifier>
    <enrichment key="BTU">an der BTU erstellt / created at BTU</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="Publikationsweg">Open Access</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">false</enrichment>
    <enrichment key="Fprofil">4 Künstliche Intelligenz und Sensorik / Artificial Intelligence and Sensor Technology</enrichment>
    <author>
      <firstName>Wael</firstName>
      <lastName>Alsabbagh</lastName>
    </author>
    <submitter>
      <firstName>Elisabeth</firstName>
      <lastName>Vogel</lastName>
    </submitter>
    <author>
      <firstName>Peter</firstName>
      <lastName>Langendörfer</lastName>
    </author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Protocols</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Process control</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>S7 Protocol</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Industrial Control Systems</value>
    </subject>
    <collection role="institutes" number="1222">FG Systeme</collection>
  </doc>
  <doc>
    <id>32637</id>
    <completedYear/>
    <publishedYear>2023</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber>9</pageNumber>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject_ref</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2024-01-26</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">A Stealthy False Command Injection Attack on Modbus based SCADA Systems</title>
    <abstract language="eng">Modbus is a widely-used industrial protocol in Supervisory Control and Data Acquisition (SCADA) systems for different purposes such as controlling remote devices, monitoring physical processes, data acquisition, etc. Unfortunately, such a protocol lacks security means i.e., authentication, integrity, and confidentiality. This has exposed industrial plants using the Modbus protocol and made them attractive to malicious adversaries who could perform various kinds of cyber-attacks causing significant consequences as Stuxnet showed. In this paper, we exploit the insecurity of the Modbus protocol and perform a stealthy false command injection scenario concealing our injection from the SCADA operator. Our attack approach is comprised of two main phases: 1) Pre-attack phase (offline) where an attacker sniffs, collects and stores sufficient valid request-response pairs in a database, 2) Attack phase (online) where the attacker performs false command injection and conceals his injection by replaying a valid response from his database upon each request sent from the HMI user. Such a scenario is quite severe and might cause disastrous damages in SCADA systems and critical infrastructures if it is successfully implemented by malicious adversaries. Finally, we suggest some appropriate mitigation solutions to prevent such a serious threat.</abstract>
    <parentTitle language="eng">20th Consumer Communications &amp; Networking Conference (CCNC), (2023)</parentTitle>
    <identifier type="doi">10.1109/CCNC51644.2023.10059804</identifier>
    <identifier type="isbn">978-1-6654-9734-3</identifier>
    <identifier type="isbn">978-1-6654-9735-0</identifier>
    <identifier type="issn">2331-9860</identifier>
    <enrichment key="BTU">an der BTU erstellt / created at BTU</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="Publikationsweg">Open Access</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">false</enrichment>
    <enrichment key="Fprofil">4 Künstliche Intelligenz und Sensorik / Artificial Intelligence and Sensor Technology</enrichment>
    <author>
      <firstName>Wael</firstName>
      <lastName>Alsabbagh</lastName>
    </author>
    <submitter>
      <firstName>Elisabeth</firstName>
      <lastName>Vogel</lastName>
    </submitter>
    <author>
      <firstName>Samuel</firstName>
      <lastName>Amogbonjaye</lastName>
    </author>
    <author>
      <firstName>Diego</firstName>
      <lastName>Urrego</lastName>
    </author>
    <author>
      <firstName>Peter</firstName>
      <lastName>Langendörfer</lastName>
    </author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Performance evaluation</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>SCADA systems</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Command Injection Attacks</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Industrial plants</value>
    </subject>
    <collection role="institutes" number="1222">FG Systeme</collection>
  </doc>
  <doc>
    <id>32603</id>
    <completedYear/>
    <publishedYear>2023</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber>4</pageNumber>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject_ref</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2024-01-24</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Vulnerability of Atomic Patterns to Simple SCA</title>
    <abstract language="eng">In this work we discuss the vulnerability of atomic pattern algorithms for elliptic curve point multiplication against simple side-channel analysis attacks using our own implementation as an example. One of the assumptions, on which the atomicity principle is based, is the indistinguishability of operations with different registers, i.e. storing of the data into two different registers cannot be distinguished if their old and new data values are the same. But before the data can be stored in a register/block, this register/block has to be addressed for storing the data. Different registers/blocks have different addresses. The key-dependent addressing of registers/blocks is an inherent feature of the binary kP algorithms and allows to reveal the key k. In our work we demonstrated it. This means that the main assumption, that addressing of different registers/blocks is an indistinguishable operation, may no longer be applied when realizing kP implementations, at least not for hardware implementations.</abstract>
    <parentTitle language="eng">19th IEEE East-West Design &amp; Test Symposium (EWDTS 2023), (2023)</parentTitle>
    <identifier type="isbn">979-8-3503-1484-7</identifier>
    <identifier type="issn">2472-761X</identifier>
    <identifier type="doi">10.1109/EWDTS59469.2023.10297074</identifier>
    <enrichment key="BTU">an der BTU erstellt / created at BTU</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="Publikationsweg">Open Access</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">false</enrichment>
    <enrichment key="Fprofil">4 Künstliche Intelligenz und Sensorik / Artificial Intelligence and Sensor Technology</enrichment>
    <author>
      <firstName>Ievgen</firstName>
      <lastName>Kabin</lastName>
    </author>
    <submitter>
      <firstName>Elisabeth</firstName>
      <lastName>Vogel</lastName>
    </submitter>
    <author>
      <firstName>Peter</firstName>
      <lastName>Langendörfer</lastName>
    </author>
    <author>
      <firstName>Zoya</firstName>
      <lastName>Dyka</lastName>
    </author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Elliptic curves</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>NIST</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Elliptic curve cryptography</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Atomicity principle</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Side-channel Analysis (SCA)</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Simple Power Analysis (SPA)</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Horizontal attacks</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Address-bit attacks</value>
    </subject>
    <collection role="institutes" number="1222">FG Systeme</collection>
  </doc>
  <doc>
    <id>32606</id>
    <completedYear/>
    <publishedYear>2023</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>181</pageFirst>
    <pageLast>182</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>image</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2024-01-24</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Machine Learning based Real Time Detection of Freezing of Gait of Parkinson Patients Running on a Body Worn Device</title>
    <abstract language="eng">For those who have Parkinson's disease, one of the most incapacitating symptoms is Freezing of Gait (FOG). Gait impairment and disruptions limit everyday activities and reduce quality of daily life along with the increase in the risk of falling [1]. Thanks to recent advancement in embedded electronics and sensors as well as their adaptation in the wearable device market, low power devices are becoming more and more capable running neural networks. This enables researchers to implement complex models on wearable devices that capture and analyze sensor data to detect FOGin real-time.</abstract>
    <parentTitle language="eng">IEEE/ACM international conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE 2023), 181 (2023)</parentTitle>
    <identifier type="isbn">979-8-4007-0102-3</identifier>
    <identifier type="issn">2832-2975</identifier>
    <identifier type="doi">10.1145/3580252.3589423</identifier>
    <enrichment key="BTU">an der BTU erstellt / created at BTU</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="Publikationsweg">Open Access</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">false</enrichment>
    <enrichment key="Fprofil">4 Künstliche Intelligenz und Sensorik / Artificial Intelligence and Sensor Technology</enrichment>
    <author>
      <firstName>Ali</firstName>
      <lastName>Haddadi Esfahani</lastName>
    </author>
    <submitter>
      <firstName>Elisabeth</firstName>
      <lastName>Vogel</lastName>
    </submitter>
    <author>
      <firstName>Oliver</firstName>
      <lastName>Maye</lastName>
    </author>
    <author>
      <firstName>Max</firstName>
      <lastName>Frohberg</lastName>
    </author>
    <author>
      <firstName>Maria</firstName>
      <lastName>Speh</lastName>
    </author>
    <author>
      <firstName>Michael</firstName>
      <lastName>Jöbges</lastName>
    </author>
    <author>
      <firstName>Peter</firstName>
      <lastName>Langendörfer</lastName>
    </author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Parkinson's disease</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Wearable computers</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Neural networks</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Machine learning</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Real-time systems</value>
    </subject>
    <collection role="institutes" number="1222">FG Systeme</collection>
  </doc>
  <doc>
    <id>32609</id>
    <completedYear/>
    <publishedYear>2023</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber>12</pageNumber>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject_ref</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2024-01-24</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">No Attacks Are Available: Securing the OpenPLC and Related Systems</title>
    <abstract language="eng">The use of Programmable Logic Controllers (PLCs) expands in industrial domains, which makes ensuring the security of Industrial Control Systems (ICSs) become paramount. The OpenPLC project, the first open-source initiative, provides flexible and cost-effective PLC solutions to build up affordable test-beds, as well as conduct experiments and academic researches. This project has wildly grown in the last few years, thus it is essential to address the most emerging security challenges it encounters. This paper introduces a new OpenPLC architecture, called OpenPLC Aqua, provided with a set of security solutions designed specifically to overcome the vulnerabilities that the current OpenPLC versions are prone to. The new OpenPLC architecture includes four security features: 1) user credentials encryption, securing the Webserver, Whitelisting and secure SSL/TLS communication channel. The OpenPLC Aqua software was tested against several attack scenarios, that were feasible against the old OpenPLC versions. Our experimental results showed our enhanced OpenPLC software is secure and resistant against several attack scenarios e.g., authentication, injection, Man-in-the-Middle and replay attacks. The OpenPLC Aqua is publicly available and a proof of concept demo is also published with this paper.</abstract>
    <parentTitle language="eng">8th GI/ACM Workshop on Industrial Automation and Control Systems (IACS WS 2023), 2085 (2023)</parentTitle>
    <identifier type="doi">10.13140/RG.2.2.24570.47043</identifier>
    <enrichment key="BTU">an der BTU erstellt / created at BTU</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="Publikationsweg">Open Access</enrichment>
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    <enrichment key="opus.urn.autoCreate">false</enrichment>
    <enrichment key="Fprofil">4 Künstliche Intelligenz und Sensorik / Artificial Intelligence and Sensor Technology</enrichment>
    <author>
      <firstName>Wael</firstName>
      <lastName>Alsabbagh</lastName>
    </author>
    <submitter>
      <firstName>Elisabeth</firstName>
      <lastName>Vogel</lastName>
    </submitter>
    <author>
      <firstName>Chaerin</firstName>
      <lastName>Kim</lastName>
    </author>
    <author>
      <firstName>Peter</firstName>
      <lastName>Langendörfer</lastName>
    </author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>OpenPLC</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Seucrity Solutions</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Industrial Control Systems</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Mitigation Solutions</value>
    </subject>
    <collection role="institutes" number="1222">FG Systeme</collection>
  </doc>
  <doc>
    <id>32614</id>
    <completedYear/>
    <publishedYear>2023</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber>6</pageNumber>
    <edition/>
    <issue/>
    <volume/>
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    <publisherName/>
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    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2024-01-24</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Successful Simple Side Channel Analysis: Vulnerability of an Atomic Pattern kP Algorithm Implemented with a Constant Time Crypto Library to Simple Electromagnetic Analysis Attacks</title>
    <parentTitle language="eng">12th Mediterranean Conference on Embedded Computing (MECO 2023), 167 (2023)</parentTitle>
    <identifier type="doi">10.1109/MECO58584.2023.10154940</identifier>
    <identifier type="isbn">979-8-3503-2291-0</identifier>
    <identifier type="isbn">979-8-3503-2290-3</identifier>
    <identifier type="issn">2637-9511</identifier>
    <enrichment key="BTU">an der BTU erstellt / created at BTU</enrichment>
    <enrichment key="opus.source">publish</enrichment>
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    <enrichment key="Fprofil">4 Künstliche Intelligenz und Sensorik / Artificial Intelligence and Sensor Technology</enrichment>
    <author>
      <firstName>Alkistis</firstName>
      <lastName>Sigourou</lastName>
    </author>
    <submitter>
      <firstName>Elisabeth</firstName>
      <lastName>Vogel</lastName>
    </submitter>
    <author>
      <firstName>Ievgen</firstName>
      <lastName>Kabin</lastName>
    </author>
    <author>
      <firstName>Peter</firstName>
      <lastName>Langendörfer</lastName>
    </author>
    <author>
      <firstName>Nicolas</firstName>
      <lastName>Sklavos</lastName>
    </author>
    <author>
      <firstName>Zoya</firstName>
      <lastName>Dyka</lastName>
    </author>
    <collection role="institutes" number="1222">FG Systeme</collection>
  </doc>
  <doc>
    <id>32615</id>
    <completedYear/>
    <publishedYear>2023</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber>6</pageNumber>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject_ref</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2024-01-24</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Randomized Addressing Countermeasures are Inefficient against Address-Bit SCA</title>
    <parentTitle language="eng">IEEE International Conference on Cyber Security and Resilience (CSR 2023), 580 (2023)</parentTitle>
    <identifier type="doi">10.1109/CSR57506.2023.10224968</identifier>
    <identifier type="isbn">979-8-3503-1170-9</identifier>
    <identifier type="isbn">979-8-3503-1171-6</identifier>
    <enrichment key="BTU">an der BTU erstellt / created at BTU</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="Publikationsweg">Open Access</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">false</enrichment>
    <enrichment key="Fprofil">4 Künstliche Intelligenz und Sensorik / Artificial Intelligence and Sensor Technology</enrichment>
    <author>
      <firstName>Ievgen</firstName>
      <lastName>Kabin</lastName>
    </author>
    <submitter>
      <firstName>Elisabeth</firstName>
      <lastName>Vogel</lastName>
    </submitter>
    <author>
      <firstName>Zoya</firstName>
      <lastName>Dyka</lastName>
    </author>
    <author>
      <firstName>Peter</firstName>
      <lastName>Langendörfer</lastName>
    </author>
    <collection role="institutes" number="1222">FG Systeme</collection>
  </doc>
  <doc>
    <id>32623</id>
    <completedYear/>
    <publishedYear>2023</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber>8</pageNumber>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject_ref</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2024-01-25</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Good Night, and Good Luck: A Control Logic Injection Attack on OpenPLC</title>
    <parentTitle language="eng">Proc. 49th Annual Conference of the IEEE Industrial Electronics Society (IECON 2023), (2023)</parentTitle>
    <identifier type="doi">10.13140/RG.2.2.32913.20321</identifier>
    <enrichment key="BTU">an der BTU erstellt / created at BTU</enrichment>
    <enrichment key="opus.source">publish</enrichment>
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    <enrichment key="Fprofil">4 Künstliche Intelligenz und Sensorik / Artificial Intelligence and Sensor Technology</enrichment>
    <author>
      <firstName>Wael</firstName>
      <lastName>Alsabbagh</lastName>
    </author>
    <submitter>
      <firstName>Elisabeth</firstName>
      <lastName>Vogel</lastName>
    </submitter>
    <author>
      <firstName>Chaerin</firstName>
      <lastName>Kim</lastName>
    </author>
    <author>
      <firstName>Peter</firstName>
      <lastName>Langendörfer</lastName>
    </author>
    <collection role="institutes" number="1222">FG Systeme</collection>
  </doc>
  <doc>
    <id>32624</id>
    <completedYear/>
    <publishedYear>2023</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue>6</issue>
    <volume>15</volume>
    <type>articler</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2024-01-25</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Through the Window: Exploitation and Countermeasures of the ESP32 Register Window Overflow</title>
    <abstract language="eng">With the increasing popularity of IoT (Internet-of-Things) devices, their security becomes an increasingly important issue. Buffer overflow vulnerabilities have been known for decades, but are still relevant, especially for embedded devices where certain security measures cannot be implemented due to hardware restrictions or simply due to their impact on performance. Therefore, many buffer overflow detection mechanisms check for overflows only before critical data are used. All data that an attacker could use for his own purposes can be considered critical. It is, therefore, essential that all critical data are checked between writing a buffer and its usage. This paper presents a vulnerability of the ESP32 microcontroller, used in millions of IoT devices, that is based on a pointer that is not protected by classic buffer overflow detection mechanisms such as Stack Canaries or Shadow Stacks. This paper discusses the implications of vulnerability and presents mitigation techniques, including a patch, that fixes the vulnerability. The overhead of the patch is evaluated using simulation as well as an ESP32-WROVER-E development board. We showed that, in the simulation with 32 general-purpose registers, the overhead for the CoreMark benchmark ranges between 0.1% and 0.4%. On the ESP32, which uses an Xtensa LX6 core with 64 general-purpose registers, the overhead went down to below 0.01%. A worst-case scenario, modeled by a synthetic benchmark, showed overheads up to 9.68%.</abstract>
    <parentTitle language="eng">Future Internet</parentTitle>
    <identifier type="doi">10.3390/fi15060217</identifier>
    <identifier type="issn">1999-5903</identifier>
    <enrichment key="BTU">an der BTU erstellt / created at BTU</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="Artikelnummer">217</enrichment>
    <enrichment key="Publikationsweg">Open Access</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">false</enrichment>
    <enrichment key="Fprofil">4 Künstliche Intelligenz und Sensorik / Artificial Intelligence and Sensor Technology</enrichment>
    <author>
      <firstName>Kai</firstName>
      <lastName>Lehniger</lastName>
    </author>
    <submitter>
      <firstName>Elisabeth</firstName>
      <lastName>Vogel</lastName>
    </submitter>
    <author>
      <firstName>Peter</firstName>
      <lastName>Langendörfer</lastName>
    </author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Xtensa</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Buffer overflow</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>return-oriented prgramming</value>
    </subject>
    <collection role="institutes" number="1222">FG Systeme</collection>
  </doc>
  <doc>
    <id>33393</id>
    <completedYear/>
    <publishedYear>2024</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue>2</issue>
    <volume>16</volume>
    <type>articler</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2024-01-29</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Non-Profiled Unsupervised Horizontal Iterative Attack against Hardware Elliptic Curve Scalar Multiplication Using Machine Learning</title>
    <abstract language="eng">While IoT technology makes industries, cities, and homes smarter, it also opens the door to security risks. With the right equipment and physical access to the devices, the attacker can leverage side-channel information, like timing, power consumption, or electromagnetic emanation, to compromise cryptographic operations and extract the secret key. This work presents a side channel analysis of a cryptographic hardware accelerator for the Elliptic Curve Scalar Multiplication operation, implemented in a Field-Programmable Gate Array and as an Application-Specific Integrated Circuit. The presented framework consists of initial key extraction using a state-of-the-art statistical horizontal attack and is followed by regularized Artificial Neural Networks, which take, as input, the partially incorrect key guesses from the horizontal attack and correct them iteratively. The initial correctness of the horizontal attack, measured as the fraction of correctly extracted bits of the secret key, was improved from 75% to 98% by applying the iterative learning.</abstract>
    <parentTitle language="eng">Future Internet</parentTitle>
    <identifier type="issn">1999-5903</identifier>
    <identifier type="doi">10.3390/fi16020045</identifier>
    <enrichment key="opus.import.date">2024-04-16T12:41:48+00:00</enrichment>
    <enrichment key="opus.source">sword</enrichment>
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    <enrichment key="Artikelnummer">45</enrichment>
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    <enrichment key="Fprofil">4 Künstliche Intelligenz und Sensorik / Artificial Intelligence and Sensor Technology</enrichment>
    <author>
      <firstName>Marcin</firstName>
      <lastName>Aftowicz</lastName>
    </author>
    <author>
      <firstName>Ievgen</firstName>
      <lastName>Kabin</lastName>
    </author>
    <author>
      <firstName>Zoya</firstName>
      <lastName>Dyka</lastName>
    </author>
    <author>
      <firstName>Peter</firstName>
      <lastName>Langendörfer</lastName>
    </author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>side channel analysis</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>machine learning</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>horizontal attack</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>non-profiled attack</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>FPGA</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>ASIC</value>
    </subject>
    <collection role="institutes" number="1222">FG Systeme</collection>
    <collection role="Import" number="import">Import</collection>
  </doc>
  <doc>
    <id>35119</id>
    <completedYear/>
    <publishedYear>2024</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber>10</pageNumber>
    <edition/>
    <issue/>
    <volume>105</volume>
    <type>articler</type>
    <publisherName>Elsevier BV</publisherName>
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    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2025-01-13</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Advantages of unsupervised learning analysis methods in single-trace SCA attacks</title>
    <parentTitle language="eng">Microprocessors and Microsystems</parentTitle>
    <identifier type="doi">10.1016/j.micpro.2023.104994</identifier>
    <identifier type="issn">0141-9331</identifier>
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    <title language="eng">Unsupervised and semisupervised machine learning frameworks for multiclass tool wear recognition</title>
    <parentTitle language="eng">IEEE Open Journal of the Industrial Electronics Society</parentTitle>
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    <author>
      <firstName>Maryam</firstName>
      <lastName>Assafo</lastName>
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      <firstName>Elisabeth</firstName>
      <lastName>Vogel</lastName>
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      <firstName>Peter</firstName>
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    <title language="eng">Resistance of the Montgomery Ladder against Simple SCA: Theory and Practice</title>
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      <firstName>Ievgen</firstName>
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      <firstName>Elisabeth</firstName>
      <lastName>Vogel</lastName>
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    <author>
      <firstName>Zoya</firstName>
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      <firstName>Dan</firstName>
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    <author>
      <firstName>Marcin</firstName>
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      <firstName>Peter</firstName>
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    <title language="eng">Resilience in the Cyber World: Definitions, Features and Models</title>
    <parentTitle language="eng">Future Internet</parentTitle>
    <identifier type="doi">10.3390/fi13110293</identifier>
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    <author>
      <firstName>Elisabeth</firstName>
      <lastName>Vogel</lastName>
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    <submitter>
      <firstName>Elisabeth</firstName>
      <lastName>Vogel</lastName>
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    <author>
      <firstName>Zoya</firstName>
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    <author>
      <firstName>Dan</firstName>
      <lastName>Klann</lastName>
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      <firstName>Peter</firstName>
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    <id>31028</id>
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    <publishedYear>2023</publishedYear>
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    <language>eng</language>
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    <issue>9</issue>
    <volume>23</volume>
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    <title language="eng">On the Stability and Homogeneous Ensemble of Feature Selection for Predictive Maintenance: A Classification Application for Tool Condition Monitoring in Milling</title>
    <abstract language="eng">Feature selection (FS) represents an essential step for many machine learning-based predictive maintenance (PdM) applications, including various industrial processes, components, and monitoring tasks. The selected features not only serve as inputs to the learning models but also can influence further decisions and analysis, e.g., sensor selection and understandability of the PdM system. Hence, before deploying the PdM system, it is crucial to examine the reproducibility and robustness of the selected features under variations in the input data. This is particularly critical for real-world datasets with a low sample-to-dimension ratio (SDR). However, to the best of our knowledge, stability of the FS methods under data variations has not been considered yet in the field of PdM. This paper addresses this issue with an application to tool condition monitoring in milling, where classifiers based on support vector machines and random forest were employed. We used a five-fold cross-validation to evaluate three popular filter-based FS methods, namely Fisher score, minimum redundancy maximum relevance (mRMR), and ReliefF, in terms of both stability and macro-F1. Further, for each method, we investigated the impact of the homogeneous FS ensemble on both performance indicators. To gain broad insights, we used four (2:2) milling datasets obtained from our experiments and NASA’s repository, which differ in the operating conditions, sensors, SDR, number of classes, etc. For each dataset, the study was conducted for two individual sensors and their fusion. Among the conclusions: (1) Different FS methods can yield comparable macro-F1 yet considerably different FS stability values. (2) Fisher score (single and/or ensemble) is superior in most of the cases. (3) mRMR’s stability is overall the lowest, the most variable over different settings (e.g., sensor(s), subset cardinality), and the one that benefits the most from the ensemble.</abstract>
    <parentTitle language="eng">Sensors</parentTitle>
    <identifier type="issn">1424-8220</identifier>
    <identifier type="doi">10.3390/s23094461</identifier>
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    <author>
      <firstName>Maryam</firstName>
      <lastName>Assafo</lastName>
    </author>
    <author>
      <firstName>Jost Philipp</firstName>
      <lastName>Städter</lastName>
    </author>
    <author>
      <firstName>Tenia</firstName>
      <lastName>Meisel</lastName>
    </author>
    <author>
      <firstName>Peter</firstName>
      <lastName>Langendörfer</lastName>
    </author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>classification</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>feature selection</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>homogeneous feature selection ensemble</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>predictive maintenance</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>milling</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>sensor fusion</value>
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    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>stability of feature selection</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>tool condition monitoring</value>
    </subject>
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    <completedDate>2024-01-10</completedDate>
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    <title language="eng">Return-Oriented Programming Gadget Catalog for the Xtensa Architecture</title>
    <parentTitle language="eng">6th International Workshop on Security, Privacy and Trust in the Internet of Things (SPT-IoT 2022)</parentTitle>
    <identifier type="doi">10.1109/PerComWorkshops53856.2022.9767489</identifier>
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      <firstName>Batyi</firstName>
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      <firstName>Elisabeth</firstName>
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      <firstName>Kai</firstName>
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    <completedDate>2024-01-09</completedDate>
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    <title language="eng">A Remote Attack Tool on Siemens S7-300 Controllers: Practical Report</title>
    <parentTitle language="deu">Kommunikation und Bildverarbeitung in der Automation : Ausgewählte Beiträge der Jahreskolloquien KommA und BVAu 2020</parentTitle>
    <identifier type="doi">10.1007/978-3-662-64283-2_1</identifier>
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    <enrichment key="UBICOseries">Technologien für die intelligente Automation book series (TIA) ; volume 14</enrichment>
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    <author>
      <firstName>Wael</firstName>
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      <firstName>Elisabeth</firstName>
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    <editor>
      <firstName>Jürgen</firstName>
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      <firstName>Volker</firstName>
      <lastName>Lohweg</lastName>
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    <completedDate>2024-01-09</completedDate>
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    <title language="eng">Through the Window: On the Exploitability of Xtensa’s Register Window Overflow</title>
    <parentTitle language="eng">32nd International Telecommunication Networks and Applications Conference (ITNAC 2022), Wellington, New Zealand, 30 November 2022 - 02 December 2022</parentTitle>
    <identifier type="doi">10.1109/ITNAC55475.2022.9998407</identifier>
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    <title language="eng">Real time detection of Freezing of Gait of Parkinson patients based on machine learning running on a body worn device</title>
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    <abstract language="eng">The integration of MQTT (Message Queuing Telemetry Transport) in Industrial Internet of Things (IIoT) systems enhances operational efficiency but introduces significant security vulnerabilities, particularly through rogue MQTT clients. These clients exploit MQTT weaknesses to disrupt industrial processes and compromise data integrity. This paper examines the impact of rogue MQTT client attacks, demonstrated through a detailed case study using the Fischertechnik Lernfabrik 4.0. We highlight how attackers can exploit MQTT's inherent vulnerabilities, including anonymous connections and message retention, to inject false data and interfere with operations. To address these risks, we propose several mitigation strategies: implementing fine-grained authorization for topic access control, enhancing replay attack protection with Message Authentication Code (MAC), employing mutual TLS (mTLS) for secure client authentication, and incorporating real-time client activity monitoring and anomaly detection. These measures aim to bolster IIoT system security, mitigate potential disruptions, and maintain operational integrity. Our findings and recommendations contribute to advancing security practices in MQTT-based IIoT environments. All attack codes and a proof-of-concept are ublicly available.</abstract>
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      <value>Rogue Client</value>
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    <title language="eng">Comment on ‘‘RIO: Return Instruction Obfuscation for Bare-Metal IoT Devices’’</title>
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