AI-DRIVEN TECHNIQUES FOR MALWARE AND MALICIOUS CODE DETECTION
- Project Research
- 1-5 Chapters
- Abstract : Available
- Table of Content: Available
- Reference Style: APA
- Recommended for : Student Researchers
- NGN 3000
ABSTRACT
Driven by considerable economic profits, there has been explosive growth of malware which has posed significant damages and finical losses to public users. The increasingly sophisticated malware call for new defensive techniques that are capable of protecting legitimate users against novel threats in cyberspace. To solve this problem, in this dissertation, we aim to design and develop innovative links between artificial intelligence (AI) and cybersecurity for new defensive techniques against evolving malware attacks and thus help improve security in cyberspace. More specifically, we first study how deep learning models integrating cybersecurity domain knowledge can be designed for intelligent malware detection. In order to comprehensively characterize the complex semantics and social relations among various applications (apps) for malware detection, we propose to utilize both content- and relation-based features and construct structured heterogeneous information networks (i.e., heterogeneous graphs) for data abstraction. Based on the constructed graphs, we propose novel node representation learning techniques and further address the out-of-sample node representation learning problem in malware detection. As the representations of malware could be highly entangled with benign apps in the complex ecosystem of development, to solve this problem, we propose an innovative adversarial disentangler to separate the distinct, informative factors of variations in the observed environment of given apps for evolving malware detection. In addition, we bring an important new insight to exploit social coding properties for the study of code security problem on social coding platforms such as Stack Overflow and GitHub. Last but not least, as AI-driven systems have been widely used in various applications including automatic malware detection, their success may also incentivize attackers to defeat the learning-based models to bypass the detection. To address this challenge, we x 1 further investigate adversarial learning over heterogeneous graph based models to improve their robustness in malware detection. To comprehensively evaluate the proposed techniques for malware and malicious code detection, we conduct extensive experimental studies based on the real-world data collections. The promising results demonstrate the outstanding performance of our proposed models compared with state-of-the-art approaches. Our proposed techniques and developed models can be readily applied to realworld malware and malicious code detection tasks.
Related Project Materials
THE IMPACT OF MONEY SUPPLY ON ECONOMIC GROWTH IN NIGERIA (1981-2010)
ABSTRACT
The study examined the impact of money supply on economic growth in Nigeria. In the model specified, real gross domestic product...
SOCIO-PSYCHOLOGICAL FACTORS OF HOME CONFLICT AS PREDICATORS OF ACADEMIC PERFORMANCE OF SOME SELECTED SECONDARY SCHOOL STUDENTS
ABSTRACT
This study attempted to identify some socio psychological effects of conflict in the home on a...
Driving Manoeuvre Recognition using Mobile Sensors
Abstract
Automobiles are integral in today’s society as they are used for transportation, commerce, and public services. The ubiqui...
THE INFLUENCE OF SMS POLITICAL ADVERTISING (MESSAGES) ON VOTING PATTERN OF ELECTORATES IN THE 2015 GOVERNORSHIP ELECTION
ABSTRACT
The research is carried out on the thrust to examine the influence o...
ENTREPRENEURSHIP DEVELOPMENT AS A TOOL FOR WEALTH CREATION
Abstract
This study is on entrepreneurship development as a tool for wealth creation. The total population for the...
EARLY CHILDHOOD EDUCATION AND THE DEVELOPMENT OF FARM-TO-TABLE INITIATIVES
ABSTRACT: This study examines the role of early childhood education in developing farm-to-table initiatives among young children. Early exposu...
FACTORS RESPONSIBLE FOR LOW ENROLEMENT OF STUDENTS IN CHEMISTRY EDUCATION
Abstract
An imbalance in the enrolment of students into the science subjects and science courses has been observed. Where there is...
THE ROLE OF ADVERTISEMENT IN NEWSPAPER PATRONAGE
ABSTRACT
The project is titled “The Role of Advertisement in Newspaper Patronage: A case study of Nigerian Tri...
A COMPARATIVE ASSESSMENT OF THE USE OF "ICT" IN TEACHING BIOLOGY IN SOME SELECTED SECONDARY SCHOOLS
Abstract
This study examines A Comparative Assessment of the Use of "ICT" in Teaching Biology in Some Selected...
DESIGN AND IMPLEMENTATION OF A COMPUTER BASED INFORMATION SYSTEM FOR THE PROJECTION OF STUDENT’S ENROLMENT IN UNIVERSITIES
INTRODUCTION
The project work deals on computer based planning information system for the projection of...
