Software vulnerabilities are a challenge in cybersecurity. Manual security patches are often difficult and slow to be deployed, while new vulnerabilities are created. Binary code vulnerability detection is less studied and more complex compared to source ...

Present manuscript designs and analyzes numerically all-optical binary-to-gray code (BTGC) converter utilizing silicon microring resonator. A waveguide-based silicon microring resonator has been employed to achieve optical switching under low-...

This article proposes a method for preprocessing fragments of binary program codes for subsequent detection of their similarity using machine learning methods. The method is based on the analysis of pseudocode obtained as a result of decompiling ...

Image retrieval with relevant feedback on large and high-dimensional image databases is a challenging task. In this paper, we propose an image retrieval method, called BCFIR (Binary Codes for Fast Image Retrieval). BCFIR utilizes sparse discriminant ...

Binary code similarity detection is to detect the similarity of code at binary (assembly) level without source code. Existing work still has their limitation when dealing with mutated binary code with different compiling options. We proposed a novel ...

Binary code similarity detection, which answers whether two pieces of binary code are similar, has been used in a number of applications,such as vulnerability detection and automatic patching. Existing approaches face two hurdles in their efforts to ...

Facial expression is the non-verbal communication used to send and receive their inner emotions state. It plays a key role in person's behaviour and communication. Facial expression recognition can be applied in various areas like human-computer ...

The goal of hashing is to learn a low-dimensional binary representation of high-dimensional information, leading to a tremendous reduction of computational cost. Previous studies usually achieved this goal by applying projection or quantization methods. ...

We present a novel approach for predicting debug information in stripped binaries. Using machine learning, we first train probabilistic models on thousands of non-stripped binaries and then use these models to predict properties of meaningful elements ...

A representation of algorithms extracted from binary code by reverse engineering is discussed. Both intermediate representations designed for automatic analysis and final representations passed to the end user are considered. The two main tasks of ...

Program trace alignment is the process of establishing a correspondence between dynamic instruction instances in executions of two semantically similar but syntactically different programs. In this paper we present what is, to the best of our knowledge,...

The Second Workshop on Forming an Ecosystem Around Software Transformation (FEAST 2017) is held in conjunction with the 24th ACM Conference on Computer and Communications Security (CCS 2017) on November 3, 2017 in Dallas, Texas. The workshop is geared ...

The problem of cross-platform binary code similarity detection aims at detecting whether two binary functions coming from different platforms are similar or not. It has many security applications, including plagiarism detection, malware detection, ...

Recently, deep neural networks based hashing methods have greatly improved the multimedia retrieval performance by simultaneously learning feature representations and binary hash functions. Inspired by the latest advance in the asymmetric hashing scheme,...

Traditionally, computer programs have been developed using the sequential programming paradigm. With the advent of parallel computing systems, such as multicore processors and distributed environments, the sequential paradigm became a barrier to the ...

The analysis of binary code is a common step of Man-At-The-End attacks to identify code sections crucial to implement attacks, such as identifying private key hidden in the code, identifying sensitive algorithms or tamper with the code to disable ...

Binary code learning techniques have been actively studied for hashing based nearest neighbor search in recent years. However, most existing techniques directly map the data into a Hamming space, which ignores the inherent property that original ...

In many existing image retrieval algorithms, Bag-of-Words (BoW) model has been widely adopted for image representation. To achieve accurate indexing and efficient retrieval, local features such as the SIFT descriptor are extracted and quantized to ...

Vulnerability analysis is an important component of software assurance practices. One of its most challenging issues is to find software flaws that could be exploited by malicious users. A necessary condition is the existence of some tainted information ...

Many binary code embedding techniques have been proposed for large-scale approximate nearest neighbor search in computer vision. Recently, product quantization that encodes the cluster index in each subspace has been shown to provide impressive accuracy ...