Search Results - binary code extraction~

Feature Extraction Methods for Binary Code Similarity Detection Using Neural Machine Translation Models by Ito, Norimitsu, Hashimoto, Masaki, Otsuka, Akira

“…Binary code similarity detection is an effective analysis technique for vulnerability, bug, and plagiarism detection in software for which the source code cannot be obtained…”
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Verified Propagation Redundancy and Compositional UNSAT Checking in CakeML by Tan, Yong Kiam, Heule, Marijn J. H., Myreen, Magnus O.

“…Modern SAT solvers can emit independently-checkable proof certificates to validate their results. The state-of-the-art proof system that allows for compact…”
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cake_lpr: Verified Propagation Redundancy Checking in CakeML by Tan, Yong Kiam, Heule, Marijn J. H., Myreen, Magnus

“…Modern SAT solvers can emit independently checkable proof certificates to validate their results. The state-of-the-art proof system that allows for compact…”
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Mal-XT: Higher accuracy hidden-code extraction of packed binary executable by Lim, Charles, Suryadi, Ramli, Kalamullah, Suhandi

“…Malware authors often use binary packers to hinder the malicious code from reverse-engineered by malware analyst…”
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A Natural Language Processing Approach for Instruction Set Architecture Identification by Sahabandu, Dinuka, Mertoguno, J. Sukarno, Poovendran, Radha

“… In this paper we propose a binary code feature extraction model to improve the accuracy and scalability…”
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Simultaneous Local Binary Feature Learning and Encoding for Homogeneous and Heterogeneous Face Recognition by Lu, Jiwen, Liong, Venice Erin, Zhou, Jie

“… (CBFD) which use a two-stage feature extraction procedure, our SLBFLE jointly learns binary codes and the codebook for local face patches so that discriminative information from raw pixels from face images…”
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Learning Binary Code for Personalized Fashion Recommendation by Lu, Zhi, Hu, Yang, Jiang, Yunchao, Chen, Yan, Zeng, Bing

“… Our system consists of three components, a feature network for content extraction, a set of type-dependent hashing modules to learn binary codes, and a matching block…”
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Semantic aware-based instruction embedding for binary code similarity detection by Jia, Yuhao, Yu, Zhicheng, Hong, Zhen

“… Moreover, current approaches often neglect multi-level semantic feature extraction, thereby failing to acquire precise semantic information about the binary code…”
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Unsupervised Dual Deep Hashing With Semantic-Index and Content-Code for Cross-Modal Retrieval by Zhang, Bin, Zhang, Yue, Li, Junyu, Chen, Jiazhou, Akutsu, Tatsuya, Cheung, Yiu-Ming, Cai, Hongmin

“…Hashing technology has exhibited great cross-modal retrieval potential due to its appealing retrieval efficiency and storage effectiveness. Most current…”
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Binary code traceability of multigranularity information fusion from the perspective of software genes by Huang, Yizhao, Qiao, Meng, Liu, Fudong, Li, Xingwei, Gui, Hairen, Zhang, Chunyan

“… Hence, we propose a feature extraction method and deep learning model that exploit the sequence and structure information of binary codes to identify the authors of anonymous and malicious binary…”
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About Methods for Extracting Algorithms from Binary Code by Kulagin, I. I., Padaryan, V. A., Koshkin, V. A.

“…This paper proposes an iterative method for extracting algorithms from binary code and constructing their high-level representation…”
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CrossSimEmb: transformer-based embedding model for cross-compilation binary code similarity detection by Yu, Gaoqing, Huang, Wei, Lyu, Jiuyang, Wang, Dongxia, Cheng, Yixuan, Sui, Aina

“… to successfully transfer natural language processing methodologies to binary code analysis. However, existing approaches remain limited by their lack of multi-granularity semantic feature extraction capability and multi-task generalization capability…”
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Adaptive Bit Selection for Scalable Deep Hashing by Wang, Min, Zhou, Wengang, Yao, Xin, Li, Houqiang

“… In the first step, a deep feature extraction model is trained to output binary codes by optimizing retrieval performance and bit properties…”
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A Performance-Sensitive Malware Detection System Using Deep Learning on Mobile Devices by Feng, Ruitao, Chen, Sen, Xie, Xiaofei, Meng, Guozhu, Lin, Shang-Wei, Liu, Yang

“…Currently, Android malware detection is mostly performed on server side against the increasing number of malware. Powerful computing resource provides more…”
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DAHP: Deep Attention-Guided Hashing With Pairwise Labels by Li, Xue, Yu, Jiong, Wang, Yongqiang, Chen, Jia-Ying, Chang, Peng-Xiao, Li, Ziyang

“…To address the problem of inadequate feature extraction and binary code discrete optimization faced by deep hashing methods using a relaxation-quantization strategy, a novel deep attention-guided…”
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Proactive defense against multi-stage attacks based on binary code similarity for IoT in-the-wild vulnerabilities by Ma, Li

“… code to be detected and the known in-wild vulnerability binary code and sends it to the feature extraction module…”
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US Patent Issued to STMicroelectronics on July 12 for "Extraction of a Binary Code Based on Physical Parameters of an Integrated Circuit Via Programming Resistors" (French Inventors)

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Deep Learning and Regularization Algorithms for Malicious Code Classification by Wang, Haojun, Long, Haixia, Wang, Ailan, Liu, Tianyue, Fu, Haiyan

“… While traditional machine learning methods for malicious code detection largely depend on hand-designed features with experts' knowledge of the domain or focus on the images which come from malicious code binary files…”
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Supervised deep semantics-preserving hashing for real-time pulmonary nodule image retrieval by Qi, Yongjun, Gu, Junhua, Zhang, Yajuan, Wu, Gengshen, Wang, Feng

“… In the paper, a novel deep hashing framework is proposed in the medical image retrieval, where the processes of deep feature extraction, binary code learning, and deep hash function learning…”
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Machine Learning-Based Analysis of Program Binaries: A Comprehensive Study by Xue, Hongfa, Sun, Shaowen, Venkataramani, Guru, Lan, Tian

“… To meet these challenges, machine learning-based binary code analysis frameworks attract substantial attention due to their automated feature extraction and drastically reduced efforts needed on large-scale programs…”
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