Add to ORKGThesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2018.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Cataloged from student-submitted PDF version of thesis.Includes bibliographical references (pages 45-48).A central challenge of malware detection using machine learning methods is the presence of adversarial variants, small changes to detectable malware that allow it to evade a model (i.e. be classified as benign). We take inspiration from adversarial variant generation methods in the continuous-valued image domain to introduce methods for malware in the binary domain. We incorpo...
Over the last decade, machine learning systems have achieved state-of-the-art performance in many fi...
While machine learning is vulnerable to adversarial examples, it still lacks systematic procedures a...
Nowadays, Machine Learning (ML) solutions are widely adopted in modern malware and network intrusion...
Cyber security is used to protect and safeguard computers and various networks from ill-intended dig...
With the rise of the popularity of machine learning (ML), it has been shown that ML-based classifier...
We present a new algorithm to train a robust malware detector. Malware is a prolific problem and mal...
The global volume of malware attacks has risen significantly over the last decade. A large majority ...
In the realm of modern technology, malware has become a paramount concern. Defined as any software d...
Machine learning is a subset of Artificial Intelligence which is utilised in a variety of different ...
The use of machine learning (ML) has become an established practice in the realm of malware classific...
Modern commercial antivirus systems increasingly rely on machine learning to keep up with the rampan...
Training classifiers that are robust against adversarially modified examples is becoming increasingl...
Modern commercial antivirus systems increasingly rely on machine learning to keep up with the rampan...
A deployed machine learning-based malware detection model is effectively a black-box for an adversar...
Malware is a serious threat in a world where IoT devices are becoming more and more pervasive; indee...
Over the last decade, machine learning systems have achieved state-of-the-art performance in many fi...
While machine learning is vulnerable to adversarial examples, it still lacks systematic procedures a...
Nowadays, Machine Learning (ML) solutions are widely adopted in modern malware and network intrusion...
Cyber security is used to protect and safeguard computers and various networks from ill-intended dig...
With the rise of the popularity of machine learning (ML), it has been shown that ML-based classifier...
We present a new algorithm to train a robust malware detector. Malware is a prolific problem and mal...
The global volume of malware attacks has risen significantly over the last decade. A large majority ...
In the realm of modern technology, malware has become a paramount concern. Defined as any software d...
Machine learning is a subset of Artificial Intelligence which is utilised in a variety of different ...
The use of machine learning (ML) has become an established practice in the realm of malware classific...
Modern commercial antivirus systems increasingly rely on machine learning to keep up with the rampan...
Training classifiers that are robust against adversarially modified examples is becoming increasingl...
Modern commercial antivirus systems increasingly rely on machine learning to keep up with the rampan...
A deployed machine learning-based malware detection model is effectively a black-box for an adversar...
Malware is a serious threat in a world where IoT devices are becoming more and more pervasive; indee...
Over the last decade, machine learning systems have achieved state-of-the-art performance in many fi...
While machine learning is vulnerable to adversarial examples, it still lacks systematic procedures a...
Nowadays, Machine Learning (ML) solutions are widely adopted in modern malware and network intrusion...