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1. Denial of service attacks in edge computing layers: Taxonomy, vulnerabilities, threats and solutions

   https://doi.org/10.1016/j.adhoc.2023.103322  

   Uddin, Ryhan; Kumar; Sathish; Chamola, Vinay (October 2023, Ad hoc networks)

   Edge computing has emerged as the dominant communication technology connecting IoT and cloud, offering reduced latency and harnessing the potential of edge devices. However, its widespread adoption has also introduced various security vulnerabilities, similar to any nascent technology. One notable threat is the denial of service (DoS) attack, including its distributed form, the distributed denial of service (DDoS) attack, which is the primary focus of this research. This paper aims to explore the impact of different types of DoS and DDoS attacks on edge computing layers by examining the vulnerabilities associated with various edge peripherals. Addition ally, existing detection and prevention mechanisms are investigated to address these weaknesses. Furthermore, a theoretical architecture is proposed to mitigate distributed denial of service attacks targeting edge systems. By comprehensively analyzing and addressing the security concerns related to DoS and DDoS attacks in edge computing, this research aims to contribute to the development of robust and secure edge computing systems. 

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2. A Survey on Security Applications with SmartNICs: Taxonomy, Implementations, Challenges, and Future Trends

   Elizalde, Sergio; AlSabeh, Ali; Mazloum, Ali; Choueiri, Samia; Kfoury, Elie; Gomez, Jose; Crichigno, Jorge (October 2025, Journal of Network and Computer Applications)

   Over the last decade, network applications have grown exponentially, demanding high-speed interconnects. Unfortunately, chip manufacturers are approaching the upper limits of silicon-based computing with slow improvements in computational performance and energy efficiency. This trend has forced the industry to shift paradigms, moving from monolithic architectures to heterogeneous, domain-specific designs. Moreover, the ever-evolving threats compromise digital services and demand more scalable and flexible solutions to ensure service continuity in production networks. Smart Network Interface Cards (SmartNICs) are a product of this new paradigm, integrating domain-specific engines and general-purpose cores to offload various network infrastructure tasks, including those related to security. This paper provides a comprehensive overview of SmartNICs, with a particular focus on their role in strengthening network defenses. It introduces SmartNIC technology and presents a taxonomy of security applications offloaded to SmartNICs, categorized into Intrusion Detection and Prevention Systems (IDS/IPS), defenses against volumetric attacks, and data confidentiality mechanisms. Additionally, the paper explores vulnerabilities associated with adopting SmartNICs in the cloud, examining the threat model and reviewing proposed remediations in the literature. Finally, it discusses challenges and future trends in SmartNIC security applications, highlighting current initiatives and open research areas. 

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3. Gotcha! I Know What You Are Doing on the FPGA Cloud: Fingerprinting Co-Located Cloud FPGA Accelerators via Measuring Communication Links

   https://doi.org/10.1145/3576915.3616606  

   Fang, Chongzhou; Miao, Ning; Wang, Han; Zhou, Jiacheng; Sheaves, Tyler; Emmert, John M; Sasan, Avesta; Homayoun, Houman (November 2023, ACM)

   In recent decades, due to the emerging requirements of computation acceleration, cloud FPGAs have become popular in public clouds. Major cloud service providers, e.g. AWS and Microsoft Azure have provided FPGA computing resources in their infrastructure and have enabled users to design and deploy their own accelerators on these FPGAs. Multi-tenancy FPGAs, where multiple users can share the same FPGA fabric with certain types of isolation to improve resource efficiency, have already been proved feasible. However, this also raises security concerns. Various types of side-channel attacks targeting multi-tenancy FPGAs have been proposed and validated. The awareness of security vulnerabilities in the cloud has motivated cloud providers to take action to enhance the security of their cloud environments. In FPGA security research papers, researchers always perform attacks under the assumption that attackers successfully co-locate with victims and are aware of the existence of victims on the same FPGA board. However, the way to reach this point, i.e., how attack- ers secretly obtain information regarding accelerators on the same fabric, is constantly ignored despite the fact that it is non-trivial and important for attackers. In this paper, we present a novel finger- printing attack to gain the types of co-located FPGA accelerators. We utilize a seemingly non-malicious benchmark accelerator to sniff the communication link and collect performance traces of the FPGA-host communication link. By analyzing these traces, we are able to achieve high classification accuracy for fingerprinting co-located accelerators, which proves that attackers can use our method to perform cloud FPGA accelerator fingerprinting with a high success rate. As far as we know, this is the first paper targeting multi-tenant FPGA accelerator fingerprinting with the communica- tion side-channel. 

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4. A Capstone Project: Designing an IoT Threat Modeling to Prevent Cyber-attacks

   Toutsop, O. (November 2021, 2021 Fall ASEE Middle Atlantic Section Meeting)

   The NTT (Nippon Telegraph and Telephone) Data Corporation report found that 80% of U.S. consumers are concerned about their smart home data security. The Internet of Things (IoT) technology brings many benefits to people's homes, and more people across the world are heavily dependent on the technology and its devices. However, many IoT devices are deployed without considering security, increasing the number of attack vectors available to attackers. Numerous Internet of Things devices lacking security features have been compromised by attackers, resulting in many security incidents. Attackers can infiltrate these smart home devices and control the home via turning off the lights, controlling the alarm systems, and unlocking the smart locks, to name a few. Attackers have also been able to access the smart home network, leading to data exfiltration. There are many threats that smart homes face, such as the Man-in-the-Middle (MIM) attacks, data and identity theft, and Denial of Service (DoS) attacks. The hardware vulnerabilities often targeted by attackers are SPI, UART, JTAG, USB, etc. Therefore, to enhance the security of the smart devices used in our daily lives, threat modeling should be implemented early on in developing any given system. This past Spring semester, Morgan State University launched a (senior) capstone project targeting undergraduate (electrical) engineering students who were thus allowed to research with the Cybersecurity Assurance and Policy (CAP) center for four months. The primary purpose of the capstone was to help students further develop both hardware and software skills while researching. For this project, the students mainly focused on the Arduino Mega Board. Some of the expected outcomes for this capstone project include: 1) understanding the physical board components, 2) learning how to attack the board through the STRIDE technique, 3) generating a Data Flow Diagram (DFD) of the system using the Microsoft threat modeling tool, 4) understanding the attack patterns, and 5) generating the threat based on the user's input. To prevent future threats and attacks from taking advantage of systems vulnerabilities, the practice of "threat modeling" is implemented. This method allows the analysis of potential attackers, including their goals and techniques, while also providing solutions and mitigation strategies. Although Threat modeling can be performed throughout the development of a system, implementing it during developmental stages will prevent further problems in the future. Threat Modeling is crucial because it will help identify any potential threat before it propagates in the system. Identifying threats and providing countermeasures will save both time and money while also keeping the consumers safe. As a result, students must grow to understand how essential detecting and preventing attacks are to protect consumer information systems and networks. At the end of this capstone project, students should take away hands-on skills in cyber defense. 

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5. Towards a Layered and Secure Internet-of-Things Testbed via Hybrid Mesh

   https://doi.org/10.1109/ICIOT.2018.00010  

   Jones, Tyler; Dali, Aniket; Rao, Manoj Ramesh; Biradar, Neha; Madassery, Jean; Liu, Kaikai (July 2018, 2018 IEEE International Congress on Internet of Things (ICIOT))

   The Internet of Things (IoT) is an emerging technology that aims to connect our environment to the internet in the same way that personal computers connected people. As this technology progresses, the IoT paradigm becomes more prevalent in our everyday lives. The nature of IoT applications necessitates devices that are low-cost, power-sensitive, integrated, unobtrusive, and interoperable with existing cloud platforms and services, for example, Amazon AWS IoT, IBM Watson IoT. As a result, these devices are often small in size, with just enough computing power needed for their specific tasks. These resource-constrained devices are often unable to implement traditional network security measures and represent a vulnerability to network attackers as a result. Few frameworks are positioned to handle the influx of this new technology and the security concerns associated with it. Current solutions fail to provide a comprehensive and multi-layer solution to these inherent IoT security vulnerabilities. This paper presents a layered approach to IoT testbed that aims to bridge multiple connection standards and cloud platforms. To solve challenges surrounding this multi-layer IoT testbed, we propose a mesh inside a mesh IoT network architecture. Our designed "edge router" incorporates two mesh networks together and performs seamlessly transmission of multi-standard packets. The proposed IoT testbed interoperates with existing multi-standards (Wi-Fi, 6LoWPAN) and segments of networks, and provides both Internet and resilient sensor coverage to the cloud platform. To ensure confidentiality and authentication of IoT devices when interoperating with multiple service platforms, we propose optimized cryptographic techniques and software frameworks for IoT devices. We propose to extend and modify the existing open-source IDS platforms such as Snort to support IoT platforms and environments. We validate the efficacy of the proposed system by evaluating its performance and effect on key system resources. The work within this testbed design and implementation provides a solid foundation for further IoT system development. 

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