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1. Spatial Blockchain: Smart Contract Using Multiple Camera Censuses

   Vasanth Iyer, Asif Mehmood (July 2022, Lecture Notes in Networks and Systems book series (LNNS,volume 507))

   With many data breaches and spoofing attacks on our networks, it becomes imperative to provide a reliable method for verifying the integrity of the source. Blockchain location-based proof-of-origin is explored for tracking trucks and vehicles. Blockchain applications that support quick authentication with these non-mutable ledger properties: consensus and implemented as smart contracts at the edge. This Blockchain application will now be known as the POWTracker platform, gathering data from multiple cameras. POWTracker is based on an existing GPS-based blockchain ledger and runs on an edge device that uses AI consensus and multiple cameras. By using GPS algorithms, we present a novel mining algorithm that rewards POW miners, providing a trustworthy, verifiable proof-of-location system. 

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2. Towards a Threat Model for Fog Computing

   https://doi.org/10.1109/UEMCON47517.2019.8993005  

   Karim, Yasser; Hasan, Ragib (October 2019, 2019 IEEE 10th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON))

   null (Ed.)

   In recent years, the addition of billions of Internet of Thing (IoT) device spawned a massive demand for computing service near the edge of the network. Due to latency, limited mobility, and location awareness, cloud computing is not capable enough to serve these devices. As a result, the focus is shifting more towards distributed platform service to put ample computing power near the edge of the networks. Thus, paradigms such as Fog and Edge computing are gaining attention from researchers as well as business stakeholders. Fog computing is a new computing paradigm, which places computing nodes in between the Cloud and the end user to reduce latency and increase availability. As an emerging technology, Fog computing also brings newer security challenges for the stakeholders to solve. Before designing the security models for Fog computing, it is better to understand the existing threats to Fog computing. In this regard, a thorough threat model can significantly help to identify these threats. Threat modeling is a sophisticated engineering process by which a computer-based system is analyzed to discover security flaws. In this paper, we applied two popular security threat modeling processes - CIAA and STRIDE - to identify and analyze attackers, their capabilities and motivations, and a list of potential threats in the context of Fog computing. We posit that such a systematic and thorough discussion of a threat model for Fog computing will help security researchers and professionals to design secure and reliable Fog computing systems. 

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3. Towards a Threat Model for Fog Computing

   Karim, Md. Yasser; Hasan, Ragib (October 2019, IEEE UEMCON 2019)

   In recent years, the addition of billions of Internet of Thing (IoT) device spawned a massive demand for computing service near the edge of the network. Due to latency, limited mobility, and location awareness, cloud computing is not capable enough to serve these devices. As a result, the focus is shifting more towards distributed platform service to put ample com- puting power near the edge of the networks. Thus, paradigms such as Fog and Edge computing are gaining attention from researchers as well as business stakeholders. Fog computing is a new computing paradigm, which places computing nodes in between the Cloud and the end user to reduce latency and increase availability. As an emerging technology, Fog computing also brings newer security challenges for the stakeholders to solve. Before designing the security models for Fog computing, it is better to understand the existing threats to Fog computing. In this regard, a thorough threat model can significantly help to identify these threats. Threat modeling is a sophisticated engineering process by which a computer-based system is analyzed to discover security flaws. In this paper, we applied two popular security threat modeling processes – CIAA and STRIDE – to identify and analyze attackers, their capabilities and motivations, and a list of potential threats in the context of Fog computing. We posit that such a systematic and thorough discussion of a threat model for Fog computing will help security researchers and professionals to design secure and reliable Fog computing systems. 

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4. Proof-of-Useful-Randomness: Mitigating the Energy Waste in Blockchain Proof-of-Work

   https://doi.org/10.5220/0010519204120419  

   Seyitoglu, Efe; Yavuz, Attila; Hoang, Thang (January 2021, In Proceedings of the 18th International Conference on Security and Cryptography (SECRYPT 2021))

   Proof-of-Work (PoW) is one of the fundamental and widely-used consensus algorithms in blockchains. In PoW, nodes compete to receive the mining reward by trying to be the first to solve a puzzle. Despite its fairness and wide availability, traditional PoW incurs extreme computational and energy waste over the blockchain. This waste is considered to be one of the biggest problems in PoW-based blockchains and cryptocurrencies. In this work, we propose a new useful PoW called Proof-of-Useful-Randomness (PoUR) that mitigates the energy waste by incorporating pre-computed (disclosable) randomness into the PoW. The key idea is to inject special randomness into puzzles via algebraic commitments that can be stored and later disclosed. Unlike the traditional wasteful PoWs, our approach enables pre-computed commitments to be utilized by a vast array of public-key cryptography methods that require offline-online processing (e.g., digital signature, key exchange, zero-knowledge protocol). Moreover, our PoW preserves the desirable properties of the traditional PoW and therefore does not require a substantial alteration in the underlying protocol. We showed the security of our PoW, and then fully implemented it to validate its significant energy-saving capabilities. 

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5. PEPPER: Privacy-prEserving, auditable, and fair Payment based resource discovery at the PERvasive edge

   Sariboz, Emrah; Tourani, Reza; Vishwanathan, Roopa; Misra, Satyajayant (July 2024, ACM Asia Conference on Computer and Communications Security (ACM AsiaCCS))

   Pervasive Edge Computing (PEC), a recent addition to the edge computing paradigm, leverages the computing resources of end-user devices to execute computation tasks in close proximity to users. One of the primary challenges in the PEC environment is determining the appropriate servers for offloading computation tasks based on factors, such as computation latency, response quality, device reliability, and cost of service. Computation outsourcing in the PEC ecosystem requires additional security and privacy considerations. Finally, mechanisms need to be in place to guarantee fair payment for the executed service(s). We present 𝑃𝐸𝑃𝑃𝐸𝑅, a novel, privacy-preserving, and decentralized framework that addresses aforementioned challenges by utilizing blockchain technology and trusted execution environments (TEE). 𝑃𝐸𝑃𝑃𝐸𝑅 improves the performance of PEC by allocating resources among end-users efficiently and securely. It also provides the underpinnings for building a financial ecosystem at the pervasive edge. To evaluate the effectiveness of 𝑃𝐸𝑃𝑃𝐸𝑅, we developed and deployed a proof of concept implementation on the Ethereum blockchain, utilizing Intel SGX as the TEE technology. We propose a simple but highly effective remote attestation method that is particularly beneficial to PEC compared to the standard remote attestation method used today. Our extensive comparison experiment shows that 𝑃𝐸𝑃𝑃𝐸𝑅 is 1.23× to 2.15× faster than the current standard remote attestation procedure. In addition, we formally prove the security of our system using the universal composability (UC) framework. 

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