相关论文: Retrofitting XoM for Stripped Binaries without Emb…
Binary code similarity detection is a core task in reverse engineering. It supports malware analysis and vulnerability discovery by identifying semantically similar code in different contexts. Modern methods have progressed from manually…
The widespread integration of embedded systems across various industries has facilitated seamless connectivity among devices and bolstered computational capabilities. Despite their extensive applications, embedded systems encounter…
Debugging and monitoring programs are integral to engineering and deploying software. Dynamic analyses monitor applications through source code or IR injection, machine code or bytecode rewriting, and virtual machine or direct hardware…
Embedding image features into a binary Hamming space can improve both the speed and accuracy of large-scale query-by-example image retrieval systems. Supervised hashing aims to map the original features to compact binary codes in a manner…
Trusted executions environments (TEEs) such as Intel(R) SGX provide hardware-isolated execution areas in memory, called enclaves. By running only the most trusted application components in the enclave, TEEs enable developers to minimize the…
Recently, more and more images are compressed and sent to the back-end devices for the machine analysis tasks~(\textit{e.g.,} object detection) instead of being purely watched by humans. However, most traditional or learned image codecs are…
Software obfuscation techniques can prevent binary diffing techniques from locating vulnerable code by obfuscating the third-party code, to achieve the purpose of protecting embedded device software. With the rapid development of binary…
As state of the art neural networks (NNs) continue to grow in size, their resource-efficient implementation becomes ever more important. In this paper, we introduce a compression scheme that reduces the number of computations required for…
Processing-using-DRAM (PUD) architectures impose a restrictive data layout and alignment for their operands, where source and destination operands (i) must reside in the same DRAM subarray (i.e., a group of DRAM rows sharing the same row…
Data compression algorithms change frequently, and obsolete decoders do not always run on new hardware and operating systems, threatening the long-term usability of content archived using those algorithms. Re-encoding content into new…
Modern computing systems suffer from the dichotomy between computation on one side, which is performed only in the processor (and accelerators), and data storage/movement on the other, which all other parts of the system are dedicated to.…
Inefficient data transfer between computation and memory inspired emerging processing-in-memory (PIM) technologies. Many PIM solutions enable storage and processing using memristors in a crossbar-array structure, with techniques such as…
CXL shared memory and persistent memory allow the contents of memory to persist beyond crashes. Stores to persistent or CXL memory are typically not immediately made persistent; developers must manually flush the corresponding cache lines…
The Compute Express Link (CXL) technology facilitates the extension of CPU memory through byte-addressable SerDes links and cascaded switches, creating complex heterogeneous memory systems where CPU access to various endpoints differs in…
Memory corruption vulnerabilities often enable attackers to take control of a target system by overwriting control-flow relevant data (such as return addresses and function pointers), which are potentially stored in close proximity of…
Recommendation algorithms that incorporate techniques from deep learning are becoming increasingly popular. Due to the structure of the data coming from recommendation domains (i.e., one-hot-encoded vectors of item preferences), these…
Traditional permutation schemes mostly focus on random scrambling of pixels, often neglecting the intrinsic image information that could enhance diffusion in image encryption algorithms. This paper introduces PermutEx, a…
Binary embedding is a nonlinear dimension reduction methodology where high dimensional data are embedded into the Hamming cube while preserving the structure of the original space. Specifically, for an arbitrary $N$ distinct points in…
Memory persistency models provide a foundation for persistent programming by specifying which (and when) writes to non-volatile memory (NVM) become persistent. Memory persistency models for the Intel-x86 and Arm architectures have been…
Processing-in-Memory (PIM) architectures enable computation directly within DRAM and help combat the memory wall problem. Bit-shifting is a fundamental operation that enables PIM applications such as shift-and-add multiplication, adders…