Metamorphic Code Generation from LLVM IR Bytecode

Metamorphic software changes its internal structure across generations with its functionality remaining unchanged. Metamorphism has been employed by malware writers as a means of evading signature detection and other advanced detection strate- gies. However, code morphing also has potential security benefits, since it increases the “genetic diversity” of software. In this research, we have created a metamorphic code generator within the LLVM compiler framework. LLVM is a three-phase compiler that supports multiple source languages and target architectures. It uses a common intermediate representation (IR) bytecode in its optimizer. Consequently, any supported high-level programming language can be transformed to this IR bytecode as part of the LLVM compila- tion process. Our metamorphic generator functions at the IR bytecode level, which provides many advantages over previously developed metamorphic generators. The morphing techniques that we employ include dead code insertion—where the dead code is actually executed within the morphed code—and subroutine permutation. We have tested the effectiveness of our code morphing using hidden Markov model analysis

Adolescent Refugees’ Judgments of Harm in War and Resettlement Contexts

Protracted wars in the Middle East have forced millions of people to flee and resettle in Western countries. Adolescents might be most affected by their war and resettlement experiences, yet have received limited attention in developmental research. The purpose of the current study was to determine how younger (12-14-year-olds) and older (17-19-year-olds) adolescent refugees from Syria make judgments about harm in unprovoked and provoked situational contexts. Fifty-nine newcomer Syrian adolescent refugees (30 boys and 29 girls) living in Canada were interviewed about straightforward and complex situations involving harm (i.e., hitting). All participants provided negative evaluations of harm in response to general questions and almost all stated that there should be a law against hitting. The majority of evaluations were stable, meaning not contingent on parental authority, school rules, or common societal practice. All participants in the baseline (unprovoked) condition, and almost all participants in the survival condition provided negative evaluations of harm in Syrian war and Canadian resettlement contexts. The majority of participants provided negative evaluations of harm in retribution conditions, and a small but significant proportion evaluated harm as less acceptable in the resettlement context than in the war context. Negative evaluations elicited moral justifications (i.e., welfare, equality), whereas positive evaluations elicited nonmoral justifications (i.e., personal, authority/rules, and retaliation). The Canadian resettlement context elicited more authority/rules considerations than did the Syrian war context. Younger adolescents were significantly more likely than older adolescents to justify negative evaluations based on authority/rules. Older adolescents were more likely than younger adolescents to provide mixed evaluations for retribution conditions. Significant gender differences were not found. Cultural considerations, social and educational implications, and future directions are discussed

Image Segmentation and Classification of Marine Organisms

To automate the arduous task of identifying and classifying images through their domain expertise, pioneers in the field of machine learning and computer vision invented many algorithms and pre-processing techniques. The process of classification is flexible with many user and domain specific alterations. These techniques are now being used to classify marine organisms to study and monitor their populations. Despite advancements in the field of programming languages and machine learning, image segmentation and classification for unlabeled data still needs improvement. The purpose of this project is to explore the various pre-processing techniques and classification algorithms that help cluster and classify images and hence choose the best parameters for identifying the various marine species present in an image