On Benchmarking Embedded Linux Flash File Systems

Due to its attractive characteristics in terms of performance, weight and power consumption, NAND flash memory became the main non volatile memory (NVM) in embedded systems. Those NVMs also present some specific characteristics/constraints: good but asymmetric I/O performance, limited lifetime, write/erase granularity asymmetry, etc. Those peculiarities are either managed in hardware for flash disks (SSDs, SD cards, USB sticks, etc.) or in software for raw embedded flash chips. When managed in software, flash algorithms and structures are implemented in a specific flash file system (FFS). In this paper, we present a performance study of the most widely used FFSs in embedded Linux: JFFS2, UBIFS,and YAFFS. We show some very particular behaviors and large performance disparities for tested FFS operations such as mounting, copying, and searching file trees, compression, etc.Comment: Embed With Linux, Lorient : France (2012

SCMFS Performance Enhancement and Implementation on Mobile Platform

This thesis presents a method for enhancing performance of Storage Class Memory File System (SCMFS) and an implementation of SCMFS on Android platform. It focuses on analyzing performance influencing factors of memory file systems and the differences in implementation of SCMFS on Android and Linux kernels. SCMFS allocates memory pages as file blocks and employs virtual memory addresses as file block addresses. SCMFS utilizes processor's memory management unit and TLB (Translation Lookaside Buffer) during file accesses. TLB is an expensive resource and has a limited number of entries to cache virtual to physical address translations. TLB miss results in expensive page walks through memory page table. Thus TLB misses play an important role in determining SCMFS performance. In this thesis, SCMFS is designed to support both 4KB and 2MB page sizes in order to reduce TLB misses and to avoid significant internal fragmentation. By comparing SCMFS with YAFFS2 and EXT4 using popular benchmarks, both advantages and disadvantages of SCMFS huge-page version and small-page version are revealed. In the second part of this thesis, an implementation of SCMFS on Android platform is presented. At the time of working on this research project, Android kernel was not merged into Linux kernel yet. Two main changes of SCMFS kernel code: memory zoning and inode functions, are made to be compatible with Android kernel. AndroSH, a file system benchmark for SCMFS on Android, is developed based on shell script. Evaluations are made from three perspectives to compare SCMFS with YAFFS2 and EXT4: I/O throughput, user data access latency, and application execution latency. SCMFS shows a performance advantage because of its small instruction footprint and its pre-allocation mechanism. However, the singly linked list used by SCMFS to store subdirectories is less efficient than HTree index used by EXT4. The future work can improve lookup efficiency of SCMFS

Swarm testing

ManuscriptSwarm testing is a novel and inexpensive way to improve the diversity of test cases generated during random testing. Increased diversity leads to improved coverage and fault detection. In swarm testing, the usual practice of potentially including all features in every test case is abandoned. Rather, a large "swarm" of randomly generated configurations, each of which omits some features, is used, with configurations receiving equal resources. We have identified two mechanisms by which feature omission leads to better exploration of a system's state space. First, some features actively prevent the system from executing interesting behaviors; e.g., "pop" calls may prevent a stack data structure from executing a bug in its overflow detection logic. Second, even when there is no active suppression of behaviors, test features compete for space in each test, limiting the depth to which logic driven by features can be explored. Experimental results show that swarm testing increases coverage and can improve fault detection dramatically; for example, in a week of testing it found 42% more distinct ways to crash a collection of C compilers than did the heavily hand-tuned default configuration of a random tester

DEFY: A Deniable File System for Flash Memory

While solutions for file system encryption can prevent an adversary from determining the contents of files, in situations where a user wishes to hide even the existence of data, encryption alone is not enough. Indeed, encryption may draw attention to those files, as they most likely contain information the user wishes to keep secret, and coercion can be a very strong motivator for the owner of an encrypted file system to surrender their secret key. Herein we present DEFY, a deniable file system designed to work exclusively with solid-state drives, particularly those found in mobile devices. Solid-state drives have unique properties that render previous deniable file system designs impractical or insecure. Further, DEFY provides features not offered by any single prior work, including: support for multiple layers of deniability, authenticated encryption, and an ability to quickly and securely delete data from the device. We have implemented a prototype based on the YAFFS and WhisperYaffs file systems. An evaluation shows DEFY performs comparatively with WhisperYaffs

Leveraging Generated Tests

The main goal of automated test generation is to improve the reliability of a program by exposing faults to developers. To this end, testing should cover the largest possible portion of the program given a test budget (i.e., time and resources) as frequently as possible. Coverage of a program entity in testing increases our confidence in the correctness of that entity. Generating various tests to cover a program entity is a particularly hard problem to solve for large software systems because the test inputs are complex and they often exhibit sophisticated feature interactions. As a result, current test generation techniques, such as symbolic execution or search-based testing, do not scale well to complex, large-scale systems. This dissertation presents a test generation technique which aims to increase the frequency of coverage in large, complex software systems. It leverages the information of existing test cases to direct the automated testing. We show the results of the application of this technique to some large systems such as GCC compiler ( 850K Lines of code), and Mozillas JavaScript engine ( 120K lines of code). It increases the frequency of coverage upto the factor of 9x, compared to the state-of-the-art technique. It also proposes non-adequate test-case reduction for reducing the size of test cases by cov-erage and mutant detection criteria. C%-coverage test reduction technique reduces a test case while preseving at least C% of coverage in the original test case. N-mutant test reduction tech-nique reduces a test cases while preserving detection of N mutants of the original test case. We evaluate the effectiveness of these test reduction techniques on different attributes of test cases. This research suggest that the generated test cases should be treated as first-class artifacts in the software development and they can be leveraged for interesting testing tasks

On Implementing Deniable Storage Encryption for Mobile Devices

Data confidentiality can be effectively preserved through encryption. In certain situations, this is inadequate, as users may be coerced into disclosing their decryption keys. In this case, the data must be hidden so that its very existence can be denied. Steganographic techniques and deniable encryption algorithms have been devised to address this specific problem. Given the recent proliferation of smartphones and tablets, we examine the feasibility and efficacy of deniable storage encryption for mobile devices. We evaluate existing, and discover new, challenges that can compromise plausibly deniable encryption (PDE) in a mobile environment. To address these obstacles, we design a system called Mobiflage that enables PDE on mobile devices by hiding encrypted volumes within random data on a device’s external storage. We leverage lessons learned from known issues in deniable encryption in the desktop environment, and design new countermeasures for threats specific to mobile systems. Key features of Mobiflage include: deniable file systems with limited impact on throughput; efficient storage use with no data expansion; and restriction/prevention of known sources of leakage and disclosure. We provide a proof-of-concept implementation for the Android OS to assess the feasibility and performance of Mobiflage. We also compile a list of best practices users should follow to restrict other known forms of leakage and collusion that may compromise deniability

On implementing deniable storage encryption for mobile devices

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