MalFam: a comprehensive study on malware families with state-of-the-art CNN architectures with classifications and XAI

MalFam: a comprehensive study on malware families with state-of-the-art CNN architectures with classifications and XAI

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2024.

Xehetasun bibliografikoak
Egile Nagusiak:	Haque, Abid Hossain, Jahin, Labiba Ifrit, Katib, Sheikh Yasir Hossain, Tuhee, Saiwara Mahmud, Tasnia, Maisoon
Beste egile batzuk:	Hossain, Muhammad Iqbal
Formatua:	Thesis
Hizkuntza:	English
Argitaratua:	Brac University 2024
Gaiak:	Explainable artificial intelligence (XAI) Convolutional neural network (CNN) DenseNet Inception ResNet V2 VGG16 Comparative analysis Neural networks (Computer science) Artificial intelligence
Sarrera elektronikoa:	http://hdl.handle.net/10361/22824

Antzeko izenburuak

Exploring Alzheimer's disease prediction with XAI in various neural network models
nork: Rahman, Quazi Ashikur, et al.
Argitaratua: (2022)

Bank loan prediction using machine learning
nork: Mahottam, Parthosarothi, et al.
Argitaratua: (2023)

Exploring the intersection of machine learning and explainable artificial intelligence: An analysis and validation of ML models through XAI for intrusion detection
nork: Rahman, Masroor, et al.
Argitaratua: (2023)

PDFGuardian: An innovative approach to interpretable PDF malware detection using XAI with SHAP framework
nork: Rahman, Tahsinur, et al.
Argitaratua: (2023)

Towards devising an effective and reliable means of fish detection and classification through the exploration of various deep learning algorithms
nork: Farhan, Rafid, et al.
Argitaratua: (2024)

Heart attack prediction using machine learning and XAI
nork: Ahsan, Mumtahina
Argitaratua: (2023)

Explainable Deepfake video detection using Convolutional Neural Network and CapsuleNet
nork: Ishrak, Gazi Hasin, et al.
Argitaratua: (2022)

Automated detection of Malignant Lesions in the ovary using deep learning models and XAI
nork: Ifty, Md. Hasin Sarwar, et al.
Argitaratua: (2024)

Fundamentals of artificial neural networks /
nork: Hassoun, Mohamad H.
Argitaratua: (1995)

Blurring of inappropriate scenes in a video using image processing
nork: Islam, Rahat Shahriar, et al.
Argitaratua: (2019)

EAI4CC: deciphering lung and colon cancer categorization within a federated learning framework harnessing the power of explainable artificial intelligence
nork: Mim, Ankhi Akter, et al.
Argitaratua: (2024)

A decentralized learning-based approach to classify colorectal cancer using Deep Learning Leveraging XAI
nork: Mubin, Kazi Ehsanul, et al.
Argitaratua: (2022)

Prediction of glaucoma from fundus images leveraging transfer learning in deep neural network
nork: Ismail, Sayem Mohammad, et al.
Argitaratua: (2021)

Detection of intracranial hemorrhage on CT scan images using convolutional neural network
nork: Rahman, Afridi Ibn, et al.
Argitaratua: (2022)

Interpretable MOOC dropout prediction using different Ensemble Methods and XAI
nork: Khan, Labib Hasan, et al.
Argitaratua: (2023)

Personalization in federated recommendation system using SVD++ with explainability
nork: Patwary, Kabbya Kantam, et al.
Argitaratua: (2022)

A deep neural network approach for intelligent crop selection and yield prediction based on 46 parameters for agricultural zone-28 in Bangladesh
nork: Islam, Tanhim, et al.
Argitaratua: (2018)

An efficient approach to detect melanoma skin cancer using a custom CNN model
nork: Rahman, K.M Saidur, et al.
Argitaratua: (2023)

Making AI intelligible :
nork: Cappelen, Herman

Artificial Intelligence : a new synthesis /
nork: Nilsson, Nils J., 1933-
Argitaratua: (1998)

Artificial intelligence /
nork: Rich, Elaine
Argitaratua: (1991)

Artificial intelligence : a modern approach /
nork: Russell, Stuart J. (Stuart Jonathan)
Argitaratua: (2003)

Introduction to artificial intelligence /
nork: Charniak, Eugene
Argitaratua: (1985)

Principles of artificial intelligence /
nork: Nilsson, Nils J., 1933-
Argitaratua: (1980)

Artificial intelligence /
nork: Winston, Patrick Henry
Argitaratua: (1992)

Artificial intelligence at MIT : expanding frontiers /
Argitaratua: (1990)

Introduction to artificial intelligence /
nork: Jackson, Philip C., 1949-
Argitaratua: (1985)

Explainable AI (XAI) driven skin cancer detection using transformer and CNN based architecture
nork: Radiah, Faiza, et al.
Argitaratua: (2024)

Quantum lattice learning and explainable artificial intelligence for maternal and child healthcare
nork: Marvin, Ggaliwango
Argitaratua: (2022)

Implementing A.I based solutions to understand & predict consumer sentiment
nork: Bin Ahmed, Omar
Argitaratua: (2023)

Statistical mechanics of learning /
nork: Engel, A. (Andreas), 1957-
Argitaratua: (2001)

A deep learning approach for prediction of ADHD using brain structure
nork: Siam, Shafin Ahad, et al.
Argitaratua: (2024)

Detection and classification of Mango Leaf diseases utilizing convolutional neural network models
nork: Ferdous, Md.Rubaiat, et al.
Argitaratua: (2024)

Introduction to AI robotics /
nork: Murphy, Robin, 1957-
Argitaratua: (2000)

Intelligent systems and robotics /
Argitaratua: (2000)

Artificial intelligence : a modern approach /
nork: Russell, Stuart J. (Stuart Jonathan)
Argitaratua: (2016)

XOPSIS: an explainable AI method based on the order of preference by similarity to ideal solution
nork: Rahman, Anika
Argitaratua: (2024)

Image segmentation of X-Ray and optical images using U-Net/UNet++ based deep learning architecture
nork: Sharma, Tanmoyee, et al.
Argitaratua: (2021)

An Analysis on Bengali handwritten conjunct character recognition and prediction
nork: Munawar, Maazin, et al.
Argitaratua: (2021)

A deep learning approach for pneumonia classiﬁcation from chest X-Ray images with ensemble modelling and explainable AI
nork: Akhter, Nasrin
Argitaratua: (2023)