Malware Detection using Machine Learning and Deep Learning

Research shows that over the last decade, malware has been growing exponentially, causing substantial financial losses to various organizations. Different anti-malware companies have been proposing solutions to defend attacks from these malware. The velocity, volume, and the complexity of malware are posing new challenges to the anti-malware community. Current state-of-the-art research shows that recently, researchers and anti-virus organizations started applying machine learning and deep learning methods for malware analysis and detection. We have used opcode frequency as a feature vector and applied unsupervised learning in addition to supervised learning for malware classification. The focus of this tutorial is to present our work on detecting malware with 1) various machine learning algorithms and 2) deep learning models. Our results show that the Random Forest outperforms Deep Neural Network with opcode frequency as a feature. Also in feature reduction, Deep Auto-Encoders are overkill for the dataset, and elementary function like Variance Threshold perform better than others. In addition to the proposed methodologies, we will also discuss the additional issues and the unique challenges in the domain, open research problems, limitations, and future directions.Comment: 11 Pages and 3 Figure

Adaptive online deployment for resource constrained mobile smart clients

Nowadays mobile devices are more and more used as a platform for applications. Contrary to prior generation handheld devices configured with a predefined set of applications, today leading edge devices provide a platform for flexible and customized application deployment. However, these applications have to deal with the limitations (e.g. CPU speed, memory) of these mobile devices and thus cannot handle complex tasks. In order to cope with the handheld limitations and the ever changing device context (e.g. network connections, remaining battery time, etc.) we present a middleware solution that dynamically offloads parts of the software to the most appropriate server. Without a priori knowledge of the application, the optimal deployment is calculated, that lowers the cpu usage at the mobile client, whilst keeping the used bandwidth minimal. The information needed to calculate this optimum is gathered on the fly from runtime information. Experimental results show that the proposed solution enables effective execution of complex applications in a constrained environment. Moreover, we demonstrate that the overhead from the middleware components is below 2%

Boston University Choral Ensembles, April 25, 1995

This is the concert program of the Boston University Choral Ensembles performance on Tuesday, April 25, 1995 at 8:00 p.m., at the Tsai Performance Center, 685 Commonwealth Avenue, Boston, Massachusetts. Works performed were Make a Joyful Noise by Edward Gregson, In the Beginning by Edward Gregson, Ecco mormorar l'onde by Claudio Monteverdi, Dolcissimo uscignolo by Claudio Monteverdi, Like as the Culver on the Bared Bough by Halsey Stevens, and Three Selections from The Creation by Franz Joseph Haydn. Digitization for Boston University Concert Programs was supported by the Boston University Humanities Library Endowed Fund

COMPOUNDING OF BASEMAH LANGUAGE: An Effort to Understand the Uniqueness of Local Languages

The objectives of this research are to describe the compound and identify its kinds in Basemah language. Compound is words formed by combining roots, and the much smaller category of phrasal words, that is items that have internal structure of phrases but function syntactically as words. Compounds cannot be connected by conjunction (McCharty, 2002). This research employed a qualitative research design, as suggested by Sugiyono that qualitative is an artistic method because the process of the research is about art and it is called interpretive method because the result of data research is about interpretation of data which are found in the field (2013:7-8). Therefore, this study uses a descriptive method in describing the finding of the data. The method of this research is descriptive qualitative method. The result of this research shows that compounding in Basemah language is distinguished based on its structures: noun-adjective, noun-noun, noun-verb and compound with certain words that relate to Endocentric compound, exocentric compound and copulative compound

Unisonasi Dalam Makna Hotu-Ye Pada Relasi Islam-Kristen Di Halmahera Selatan

Penelitian bertujuan untuk mendeskripsikan dan benar-benar melihat realitas yang terjadi di masyarakat serta menganalisis pemahaman masyarakat Halmahera Selatan tentang makna Hotu-Ye dalam relasi umat beragama terlebih khusus Islam dan Kristen. Penelitian ini juga melihat bagaimana masyarakat Halmahera Selatan memaknai Hotu-Ye sebagai ruang dialog antar umat beragama, terlebih lagi melihat bagaimana Unionisasi terjadi dalam refleksi maupun relasi masyarakat yang ada di Halmahera Selatan. Adapun metode yang digunakan dalam penelitian ini adalah Metode penelitian Kualitatif, yang akan dilakukan dengan metode deskriptif. Hasil yang akan dicapai adalah bahwa Hotu-Ye mampu menjadi ruang dialog antar agama, juga menjadi Unisonasi dimana masyarakat Halmahera Selatan bisa hidup berdampingan dengan sesama tanpa melihat perbedaan agama. Hotu-Ye memiliki nilai- nilai yang dapat mendorong hidup yang harmonis dalam relasi dua agama yang berbeda dilihat dari makna Hotu-Ye itu sendiri.This study aims to describe and analyze the understanding of the people of South Halmahera about the meaning of Hotu-Ye in religious relations, especially Islam and Christianity. This study also looks at how the people of South Halmahera interpret Hotu-Ye, as a space for dialogue between religious communities, moreover in this study, we want to see how Unisonation occurs in reflection and community relations in South Halmahera in interpreting Hotu-Ye. The method used in this research is a qualitative research method, which will be carried out with a descriptive method. The result to be achieved is that Hotu-Ye is able to become a space for inter-religious dialogue, as well as a Unisonation where the people of South Halmahera can live side by side with each other regardless of religious differences, because Hotu-Ye has values that can encourage living in harmony within the community. The true relation of the two religions is seen from the meaning of Hotu-Ye itself

Regeneration Learning: A Learning Paradigm for Data Generation

Machine learning methods for conditional data generation usually build a mapping from source conditional data X to target data Y. The target Y (e.g., text, speech, music, image, video) is usually high-dimensional and complex, and contains information that does not exist in source data, which hinders effective and efficient learning on the source-target mapping. In this paper, we present a learning paradigm called regeneration learning for data generation, which first generates Y' (an abstraction/representation of Y) from X and then generates Y from Y'. During training, Y' is obtained from Y through either handcrafted rules or self-supervised learning and is used to learn X-->Y' and Y'-->Y. Regeneration learning extends the concept of representation learning to data generation tasks, and can be regarded as a counterpart of traditional representation learning, since 1) regeneration learning handles the abstraction (Y') of the target data Y for data generation while traditional representation learning handles the abstraction (X') of source data X for data understanding; 2) both the processes of Y'-->Y in regeneration learning and X-->X' in representation learning can be learned in a self-supervised way (e.g., pre-training); 3) both the mappings from X to Y' in regeneration learning and from X' to Y in representation learning are simpler than the direct mapping from X to Y. We show that regeneration learning can be a widely-used paradigm for data generation (e.g., text generation, speech recognition, speech synthesis, music composition, image generation, and video generation) and can provide valuable insights into developing data generation methods