Crystalor: Persistent Memory Encryption Mechanism with Optimized Metadata Structure and Fast Crash Recovery

This study presents an efficient persistent memory encryption mechanism, named Crystalor, which efficiently realizes a secure persistent/non-volatile memory based on an authentication tree with structural optimization, such as the split counter (SC). Crystalor can completely exploit the advantage of metadata compression techniques, whereas existing mechanisms are incompatible with such optimization. Meanwhile, Crystalor incurs almost no latency overhead under the nominal operation conditions for realizing the crash consistency/recoverability. We implement Crystalor with a state-of-the-art parallelizable authentication tree instance, namely ELM (IEEE TIFS 2022), and evaluate the effectiveness by both algorithmic analyses and system-level simulation in comparison with the existing state-of-the-art ones (e.g., SCUE in HPCA 2023). For protecting a 4 TB memory, Crystalor requires 29–62% fewer clock cycles per memory read/write operation than SCUE owing to the compatibility with the SC. In addition, Crystalor and SCUE require 312GB and 554GB memory overheads for metadata, respectively, which indicates that Crystalor achieves a reduction of memory overhead by 44%. The result of the system-level simulation using the gem5 simulator indicates that Crystalor achieves a reduction of the workload execution time by up to 11.5% from SCUE. Moreover, Crystalor can offer a lazy recovery, which makes recovery several thousand times faster than SCUE

Improving Phase Change Memory Performance with Data Content Aware Access

A prominent characteristic of write operation in Phase-Change Memory (PCM) is that its latency and energy are sensitive to the data to be written as well as the content that is overwritten. We observe that overwriting unknown memory content can incur significantly higher latency and energy compared to overwriting known all-zeros or all-ones content. This is because all-zeros or all-ones content is overwritten by programming the PCM cells only in one direction, i.e., using either SET or RESET operations, not both. In this paper, we propose data content aware PCM writes (DATACON), a new mechanism that reduces the latency and energy of PCM writes by redirecting these requests to overwrite memory locations containing all-zeros or all-ones. DATACON operates in three steps. First, it estimates how much a PCM write access would benefit from overwriting known content (e.g., all-zeros, or all-ones) by comprehensively considering the number of set bits in the data to be written, and the energy-latency trade-offs for SET and RESET operations in PCM. Second, it translates the write address to a physical address within memory that contains the best type of content to overwrite, and records this translation in a table for future accesses. We exploit data access locality in workloads to minimize the address translation overhead. Third, it re-initializes unused memory locations with known all-zeros or all-ones content in a manner that does not interfere with regular read and write accesses. DATACON overwrites unknown content only when it is absolutely necessary to do so. We evaluate DATACON with workloads from state-of-the-art machine learning applications, SPEC CPU2017, and NAS Parallel Benchmarks. Results demonstrate that DATACON significantly improves system performance and memory system energy consumption compared to the best of performance-oriented state-of-the-art techniques.Comment: 18 pages, 21 figures, accepted at ACM SIGPLAN International Symposium on Memory Management (ISMM

Forensic Analysis of the ChatSecure Instant Messaging Application on Android Smartphones

We present the forensic analysis of the artifacts generated on Android smartphones by ChatSecure, a secure Instant Messaging application that provides strong encryption for transmitted and locally-stored data to ensure the privacy of its users. We show that ChatSecure stores local copies of both exchanged messages and files into two distinct, AES-256 encrypted databases, and we devise a technique able to decrypt them when the secret passphrase, chosen by the user as the initial step of the encryption process, is known. Furthermore, we show how this passphrase can be identified and extracted from the volatile memory of the device, where it persists for the entire execution of ChatSecure after having been entered by the user, thus allowing one to carry out decryption even if the passphrase is not revealed by the user. Finally, we discuss how to analyze and correlate the data stored in the databases used by ChatSecure to identify the IM accounts used by the user and his/her buddies to communicate, as well as to reconstruct the chronology and contents of the messages and files that have been exchanged among them. For our study we devise and use an experimental methodology, based on the use of emulated devices, that provides a very high degree of reproducibility of the results, and we validate the results it yields against those obtained from real smartphones