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1. Secrecy Coding in the Integrated Network Enhanced Telemetry (iNET)

   Shoushtari, Morteza; Harrison, Willie (October 2021, Proceedings International Telemetering Conference US)

   Data security plays a crucial role in all areas of data transmission, processing, and storage. This paper considers security in eavesdropping attacks over wireless communication links in aeronautical telemetry systems. Data streams in these systems are often encrypted by traditional encryption algorithms such as the Advanced Encryption Standard (AES). Here, we propose a secure coding technique for the integrated Network Enhanced Telemetry (iNET) communications system that can be coupled with modern encryption schemes. We consider a wiretap scenario where there are two telemetry links between a test article (TA) and a legitimate receiver, or ground station (GS). We show how these two links can be used to transmit both encrypted and unencrypted data streams while keeping both streams secure. A single eavesdropper is assumed who can tap into both links through its noisy channel. Since our scheme does not require encryption of the unencrypted data stream, the proposed scheme offers the ability to reduce the size of the required secret key while keeping the transmitted data secure. 

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2. Lightweight Digital Signatures for Internet of Things: Current and Post-Quantum Trends and Visions

   https://doi.org/10.1109/DSC61021.2023.10354177  

   Nouma, Saif E.; Yavuz, Attila A. (November 2023, IEEE)

   The Internet of Things (IoT) harbors a large number of resource-limited devices (e.g., sensors) that continuously generate and offload sensitive information (e.g., financial, health, personal). It is imperative the ensure the trustworthiness of this data with efficient cryptographic mechanisms. Digital signatures can offer scalable authentication with public verifiability and nonrepudiation. However, the state-of-the-art digital signatures do not offer the desired efficiency and are not scalable for the connected resource-limited IoT devices. This is without considering long term security features such as post-quantum security and forward security. In this paper, we summarize the main challenges to an energy-aware and efficient signature scheme. Then, we propose new scheme design improvements that uniquely embed different emerging technologies such as Mutli-Party Computation (MPC) and secure enclaves (e.g., Intel SGX) in order to secret-share confidential keys of low-end IoT devices across multiple cloud servers. We also envision building signature schemes with Fully Homomorphic Encryption (FHE) to enable verifiers to compute expensive commitments under encryption. We provide evaluation metrics that showcase the feasibility and efficiency of our designs for potential deployment on embedded devices in IoT. 

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3. Optimizing Huffman Decoding for Error-Bounded Lossy Compression on GPUs

   https://doi.org/10.1109/IPDPS53621.2022.00075  

   Rivera, Cody; Di, Sheng; Tian, Jiannan; Yu, Xiaodong; Tao, Dingwen; Cappello, Franck (May 2022, The 36th IEEE International Parallel and Distributed Processing Symposium (IPDPS 2022))

   More and more HPC applications require fast and effective compression techniques to handle large volumes of data in storage and transmission. Not only do these applications need to compress the data effectively during simulation, but they also need to perform decompression efficiently for post hoc analysis. SZ is an error-bounded lossy compressor for scientific data, and cuSZ is a version of SZ designed to take advantage of the GPU's power. At present, cuSZ's compression performance has been optimized significantly while its decompression still suffers considerably lower performance because of its sophisticated lossless compression step---a customized Huffman decoding. In this work, we aim to significantly improve the Huffman decoding performance for cuSZ, thus improving the overall decompression performance in turn. To this end, we first investigate two state-of-the-art GPU Huffman decoders in depth. Then, we propose a deep architectural optimization for both algorithms. Specifically, we take full advantage of CUDA GPU architectures by using shared memory on decoding/writing phases, online tuning the amount of shared memory to use, improving memory access patterns, and reducing warp divergence. Finally, we evaluate our optimized decoders on an Nvidia V100 GPU using eight representative scientific datasets. Our new decoding solution obtains an average speedup of 3.64X over cuSZ's Huffman decoder and improves its overall decompression performance by 2.43X on average. 

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4. Lightweight Encryption Using Chaffing and Winnowing with All-or-Nothing Transform for Network-on-Chip Architectures

   https://doi.org/10.1109/HOST49136.2021.9702282  

   Weerasena, Hansika; Charles, Subodha; Mishra, Prabhat (December 2021, IEEE International Symposium on Hardware Oriented Security and Trust (HOST))

   Network-on-Chip (NoC) fulfills the communication requirements of modern System-on-Chip (SoC) architectures. Due to the resource-constrained nature of NoC-based SoCs, it is a major challenge to secure on-chip communication against eavesdropping attacks using traditional encryption methods. In this paper, we propose a lightweight encryption technique using chaffing and winnowing (C&W) with all-or-nothing transform (AONT) that benefits from the unique NoC traffic characteristics. Our experimental results demonstrate that our proposed encryption technique provides the required security with significantly less area and energy overhead compared to the state-of-the-art approaches. 

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5. New Approaches to Traitor Tracing with Embedded Identities

   https://doi.org/10.1007/978-3-030-36033-7_6  

   Goyal, Rishab; Koppula, Venkata; Waters, Brent (November 2019, New Approaches to Traitor Tracing with Embedded Identities)

   In a traitor tracing (TT) system for n users, every user has his/her own secret key. Content providers can encrypt messages using a public key, and each user can decrypt the ciphertext using his/her secret key. Suppose some of the n users collude to construct a pirate decoding box. Then the tracing scheme has a special algorithm, called 𝖳𝗋𝖺𝖼𝖾 , which can identify at least one of the secret keys used to construct the pirate decoding box. Traditionally, the trace algorithm output only the ‘index’ associated with the traitors. As a result, to use such systems, either a central master authority must map the indices to actual identities, or there should be a public mapping of indices to identities. Both these options are problematic, especially if we need public tracing with anonymity of users. Nishimaki, Wichs, and Zhandry (NWZ) [Eurocrypt 2016] addressed this problem by constructing a traitor tracing scheme where the identities of users are embedded in the secret keys, and the trace algorithm, given a decoding box D, can recover the entire identities of the traitors. We call such schemes ‘Embedded Identity Traitor Tracing’ schemes. NWZ constructed such schemes based on adaptively secure functional encryption (FE). Currently, the only known constructions of FE schemes are based on nonstandard assumptions such as multilinear maps and iO. In this work, we study the problem of embedded identities TT based on standard assumptions. We provide a range of constructions based on different assumptions such as public key encryption (PKE), bilinear maps and the Learning with Errors (LWE) assumption. The different constructions have different efficiency trade offs. In our PKE based construction, the ciphertext size grows linearly with the number of users; the bilinear maps based construction has sub-linear (𝑛√ ) sized ciphertexts. Both these schemes have public tracing. The LWE based scheme is a private tracing scheme with optimal ciphertexts (i.e., log(𝑛)). Finally, we also present other notions of traitor tracing, and discuss how they can be build in a generic manner from our base embedded identity TT scheme. 

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