35 research outputs found

    HMT: A Hardware-Centric Hybrid Bonsai Merkle Tree Algorithm for High-Performance Authentication

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    Bonsai Merkle tree (BMT) is a widely used data structure for authenticating data/metadata in a secure computing system. However, the predominantly recursive andsequential nature of traditional BMT algorithms make them challenging to implement with Field-Programmable Gate Array (FPGA) in modern heterogeneous computing platforms. In this work, we introduce HMT, a hardware-friendly implementation methodology for BMT that enables the verification and update processes to function independently, as well as saves additional write-backs by making the update conditions more flexible compared to previous algorithms. The methodology of HMT contributes both novel algorithm revisions and innovative hardware techniques to implementing BMT. Our empirical performance measurements have demonstrated that HMT can achieve up to 7x improvement in bandwidth and 4.5x reduction in latency over the baseline

    Enabling Recovery of Secure Non-Volatile Memories

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    Emerging non-volatile memories (NVMs), such as phase change memory (PCM), spin-transfer torque RAM (STT-RAM) and resistive RAM (ReRAM), have dual memory-storage characteristics and, therefore, are strong candidates to replace or augment current DRAM and secondary storage devices. The newly released Intel 3D XPoint persistent memory and Optane SSD series have shown promising features. However, when these new devices are exposed to events such as power loss, many issues arise when data recovery is expected. In this dissertation, I devised multiple schemes to enable secure data recovery for emerging NVM technologies when memory encryption is used. With the data-remanence feature of NVMs, physical attacks become easier; hence, emerging NVMs are typically paired with encryption. In particular, counter-mode encryption is commonly used due to its performance and security advantages over other schemes (e.g., electronic codebook encryption). However, enabling data recovery in power failure events requires the recovery of security metadata associated with data blocks. Naively writing security metadata updates along with data for each operation can further exacerbate the write endurance problem of NVMs as they have limited write endurance and very slow write operations. Therefore, it is necessary to enable the recovery of data and security metadata (encryption counters) but without incurring a significant number of writes. The first work of this dissertation presents an explanation of Osiris, a novel mechanism that repurposes error correcting code (ECC) co-located with data to enable recovery of encryption counters by additionally serving as a sanity-check for encryption counters used. Thus, by using a stop-loss mechanism with a limited number of trials, ECC can be used to identify which encryption counter that was used most recently to encrypt the data and, hence, allow correct decryption and recovery. The first work of this dissertation explores how different stop-loss parameters along with optimizations of Osiris can potentially reduce the number of writes. Overall, Osiris enables the recovery of encryption counters while achieving better performance and fewer writes than a conventional write-back caching scheme of encryption counters, which lacks the ability to recover encryption counters. Later, in the second work, Osiris implementation is expanded to work with different counter-mode memory encryption schemes, where we use an epoch-based approach to periodically persist updated counters. Later, when a crash occurs, we can recover counters through test-and-verification to identify the correct counter within the size of an epoch for counter recovery. Our proposed scheme, Osiris-Global, incurs minimal performance overheads and write overheads in enabling the recovery of encryption counters. In summary, the findings of the present PhD work enable the recovery of secure NVM systems and, hence, allows persistent applications to leverage the persistency features of NVMs. Meanwhile, it also minimizes the number of writes required in meeting this crash consistency requirement of secure NVM systems

    Anchor: Architecture for Secure Non-Volatile Memories

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    The rapid growth of memory-intensive applications like cloud computing, deep learning, bioinformatics, etc., have propelled memory industry to develop scalable, high density, low power non-volatile memory (NVM) technologies; however, computing systems that integrate these advanced NVMs are vulnerable to several security attacks that threaten (i) data confidentiality, (ii) data availability, and (iii) data integrity. This dissertation presents ANCHOR, which integrates 4 low overhead, high performance security solutions SECRET, COVERT, ACME, and STASH to thwart these attacks on NVM systems. SECRET is a low cost security solution for data confidentiality in multi-/triple-level cell (i.e., MLC/TLC) NVMs. SECRET synergistically combines (i) smart encryption, which prevents re-encryption of unmodified or zero-words during a write-back with (ii) XOR-based energy masking, which further optimizes NVM writes by transforming a high-energy ciphertext into a low-energy ciphertext. SECRET outperforms state-of-the-art encryption solutions, with the lowest write energy and latency, as well as the highest lifetime. COVERT and ACME complement SECRET to improve system availability of counter mode encryption (CME). COVERT repurposes unused error correction resources to dynamically extend time to counter overflow of fast growing counters, thereby delaying frequent full memory re-encryption (system freeze). ACME performs counter write leveling (CWL) to further increase time to counter overflow, and thereby delays the time to full memory re-encryption. COVERT+ACME achieves system availability of 99.999% during normal operation and 99.9% under a denial of memory service (DoMS) attack. In contrast, conventional CME achieves system availability of only 85.71% during normal operation and is rendered non-operational under a DoMS attack. Finally, STASH is a comprehensive end-to-end security architecture for state-of-the-art smart hybrid memories (SHMs) that employ a smart DRAM cache with smart NVM-based main memory. STASH integrates (i) CME for data confidentiality, (ii) page-level Merkle Tree authentication for data integrity, (iii) recovery-compatible MT updates to withstand power/system failures, and (iv) page-migration friendly security meta-data management. For security guarantees equivalent to state-of-the-art, STASH reduces memory overhead by 12.7x, improves system performance by 65%, and increases NVM lifetime by 5x. This dissertation thus addresses the core security challenges of next-generation NVM-based memory systems. Directions for future research include (i) exploration of holistic architectures that ensure both security and reliability of smart memory systems, (ii) investigating applications of ANCHOR to reduce security overhead of Internet-of-Things, and (iii) extending ANCHOR to safeguard emerging non-volatile processors, especially in the light of advanced attacks like Spectre and Meltdown

    Hardware Mechanisms for Efficient Memory System Security

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    The security of a computer system hinges on the trustworthiness of the operating system and the hardware, as applications rely on them to protect code and data. As a result, multiple protections for safeguarding the hardware and OS from attacks are being continuously proposed and deployed. These defenses, however, are far from ideal as they only provide partial protection, require complex hardware and software stacks, or incur high overheads. This dissertation presents hardware mechanisms for efficiently providing strong protections against an array of attacks on the memory hardware and the operating system’s code and data. In the first part of this dissertation, we analyze and optimize protections targeted at defending memory hardware from physical attacks. We begin by showing that, contrary to popular belief, current DDR3 and DDR4 memory systems that employ memory scrambling are still susceptible to cold boot attacks (where the DRAM is frozen to give it sufficient retention time and is then re-read by an attacker after reboot to extract sensitive data). We then describe how memory scramblers in modern memory controllers can be transparently replaced by strong stream ciphers without impacting performance. We also demonstrate how the large storage overheads associated with authenticated memory encryption schemes (which enable tamper-proof storage in off-chip memories) can be reduced by leveraging compact integer encodings and error-correcting code (ECC) DRAMs – without forgoing the error detection and correction capabilities of ECC DRAMs. The second part of this dissertation presents Neverland: a low-overhead, hardware-assisted, memory protection scheme that safeguards the operating system from rootkits and kernel-mode malware. Once the system is done booting, Neverland’s hardware takes away the operating system’s ability to overwrite certain configuration registers, as well as portions of its own physical address space that contain kernel code and security-critical data. Furthermore, it prohibits the CPU from fetching privileged code from any memory region lying outside the physical addresses assigned to the OS kernel and drivers. This combination of protections makes it extremely hard for an attacker to tamper with the kernel or introduce new privileged code into the system – even in the presence of software vulnerabilities. Neverland enables operating systems to reduce their attack surface without having to rely on complex integrity monitoring software or hardware. The hardware mechanisms we present in this dissertation provide building blocks for constructing a secure computing base while incurring lower overheads than existing protections.PHDComputer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/147604/1/salessaf_1.pd

    Anchor: Architecture for Secure Non-Volatile Memories

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    The rapid growth of memory-intensive applications like cloud computing, deep learning, bioinformatics, etc., have propelled memory industry to develop scalable, high density, low power non-volatile memory (NVM) technologies; however, computing systems that integrate these advanced NVMs are vulnerable to several security attacks that threaten (i) data confidentiality, (ii) data availability, and (iii) data integrity. This dissertation presents ANCHOR, which integrates 4 low overhead, high performance security solutions SECRET, COVERT, ACME, and STASH to thwart these attacks on NVM systems. SECRET is a low cost security solution for data confidentiality in multi-/triple-level cell (i.e., MLC/TLC) NVMs. SECRET synergistically combines (i) smart encryption, which prevents re-encryption of unmodified or zero-words during a write-back with (ii) XOR-based energy masking, which further optimizes NVM writes by transforming a high-energy ciphertext into a low-energy ciphertext. SECRET outperforms state-of-the-art encryption solutions, with the lowest write energy and latency, as well as the highest lifetime. COVERT and ACME complement SECRET to improve system availability of counter mode encryption (CME). COVERT repurposes unused error correction resources to dynamically extend time to counter overflow of fast growing counters, thereby delaying frequent full memory re-encryption (system freeze). ACME performs counter write leveling (CWL) to further increase time to counter overflow, and thereby delays the time to full memory re-encryption. COVERT+ACME achieves system availability of 99.999% during normal operation and 99.9% under a denial of memory service (DoMS) attack. In contrast, conventional CME achieves system availability of only 85.71% during normal operation and is rendered non-operational under a DoMS attack. Finally, STASH is a comprehensive end-to-end security architecture for state-of-the-art smart hybrid memories (SHMs) that employ a smart DRAM cache with smart NVM-based main memory. STASH integrates (i) CME for data confidentiality, (ii) page-level Merkle Tree authentication for data integrity, (iii) recovery-compatible MT updates to withstand power/system failures, and (iv) page-migration friendly security meta-data management. For security guarantees equivalent to state-of-the-art, STASH reduces memory overhead by 12.7x, improves system performance by 65%, and increases NVM lifetime by 5x. This dissertation thus addresses the core security challenges of next-generation NVM-based memory systems. Directions for future research include (i) exploration of holistic architectures that ensure both security and reliability of smart memory systems, (ii) investigating applications of ANCHOR to reduce security overhead of Internet-of-Things, and (iii) extending ANCHOR to safeguard emerging non-volatile processors, especially in the light of advanced attacks like Spectre and Meltdown
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