相关论文: Metamorphic Virus Detection in Portable Executable…

We study distributed algorithms for string matching problem in presence of wildcard characters. Given a string T (a text), we look for all occurrences of another string P (a pattern) as a substring of string T . Each wildcard character in…

There is a large collection of Handwritten English paper documents of Historical and Scientific importance. But paper documents are not recognized directly by computer. Hence the closest way of indexing these documents is by storing their…

A morphed face image is a synthetically created image that looks so similar to the faces of two subjects that both can use it for verification against a biometric verification system. It can be easily created by aligning and blending face…

Adversarially perturbed images of text can cause sophisticated OCR systems to produce misleading or incorrect transcriptions from seemingly invisible changes to humans. Some of these perturbations even survive physical capture, posing…

We propose an approach to distinguish between correct and incorrect image classifications. Our approach can detect misclassifications which either occur $\it{unintentionally}$ ("natural errors"), or due to…

A homoglyph (name spoofing) attack is a common technique used by adversaries to obfuscate file and domain names. This technique creates process or domain names that are visually similar to legitimate and recognized names. For instance, an…

In recent years, deep learning has shown performance breakthroughs in many applications, such as image detection, image segmentation, pose estimation, and speech recognition. However, this comes with a major concern: deep networks have been…

Open-source software (OSS) has experienced a surge in popularity, attributed to its collaborative development model and cost-effective nature. However, the adoption of specific software versions in development projects may introduce…

Modern malware poses a severe threat to cybersecurity, continually evolving in sophistication. To combat this threat, researchers and security professionals continuously explore advanced techniques for malware detection and analysis.…

Detecting reliably copy-move forgeries is difficult because images do contain similar objects. The question is: how to discard natural image self-similarities while still detecting copy-moved parts as being "unnaturally similar"? Copy-move…

Although the problem of spam classification seems to be solved, there are still vulnerabilities in the current spam filters that could be easily exploited. We present one such vulnerability, in which one could replace some characters with…

The task of obfuscating writing style using sequence models has previously been investigated under the framework of obfuscation-by-transfer, where the input text is explicitly rewritten in another style. These approaches also often lead to…

We have identified a methodological problem in the empirical evaluation of the string encryption detection capabilities of the AndrODet system described by Mirzaei et al. in the recent paper "AndrODet: An adaptive Android obfuscation…

In this work, we analyze efficient window shift schemes for windowed decoding of spatially coupled low-density parity-check (SC-LDPC) codes, which is known to yield close-tooptimal decoding results when compared to full belief propagation…

Advanced metamorphic malware and ransomware, by using obfuscation, could alter their internal structure with every attack. If such malware could intrude even into any of the IoT networks, then even if the original malware instance gets…

Homomorphic encryption is a method used in cryptopgraphy to create programs that can interact with encrypted data without ever leaving the data in the clear. This has many potential applications in cybersecurity. This paper uses…

Machine learning (ML) used for static portable executable (PE) malware detection typically employs per-file numerical feature vector representations as input with one or more target labels during training. However, there is much orthogonal…

Machine learning models provide statistically impressive results which might be individually unreliable. To provide reliability, we propose an Epistemic Classifier (EC) that can provide justification of its belief using support from the…

This research proposed an architecture and a system which able to monitor the virus behavior and classify them as a traditional or polymorphic virus. Preliminary research was conducted to get the current virus behavior and to find the…

Industry practitioners care about small improvements in malware detection accuracy because their models are deployed to hundreds of millions of machines, meaning a 0.1\% change can cause an overwhelming number of false positives. However,…