A novel approach for phishing detection using URL-based heuristic - 2014
Luong Anh Tuan Nguyen, Ba Lam To, Huu Khuong Nguyen, Minh Hoang Nguyen
Together with the growth of e-commerce transaction, Phishing - the act of stealing personal information - rises in quantity and quality. The phishers try to make fake-sites look similar to legitimate sites in terms of interface and uniform resource locator (URL) address. Therefore, the numbers of victim have been increasing due to inefficient methods using blacklist to detect phishing. This paper proposes a new phishing detection approach based on the features of URL. Specifically, the proposed method focuses on the similarity of phishing site's URL and legitimate site's URL. In addition, the ranking of site is also considered as an important factor to decide whether the site is a phishing site. The proposed technique is evaluated with a dataset of 11,660 phishing sites and 5,000 legitimate sites. The results show that the technique can detect over 97% phishing sites.
#Phishing #URL-Based #Heuristic
HOSS: an implementation of the combined finite-discrete element method Tập 7 Số 5 - Trang 765-787 - 2020
Earl E. Knight, Esteban Rougier, Zhou Lei, Bryan Euser, Viet T. Chau, Samuel Boyce, Ke Gao, Kurama Okubo, M. Froment
AbstractNearly thirty years since its inception, the combined finite-discrete element method (FDEM) has made remarkable strides in becoming a mainstream analysis tool within the field of Computational Mechanics. FDEM was developed to effectively “bridge the gap” between two disparate Computational Mechanics approaches known as the finite and discrete element methods. At Los Alamos National Laboratory (LANL) researchers developed the Hybrid Optimization Software Suite (HOSS) as a hybrid multi-physics platform, based on FDEM, for the simulation of solid material behavior complemented with the latest technological enhancements for full fluid–solid interaction. In HOSS, several newly developed FDEM algorithms have been implemented that yield more accurate material deformation formulations, inter-particle interaction solvers, and fracture and fragmentation solutions. In addition, an explicit computational fluid dynamics solver and a novel fluid–solid interaction algorithms have been fully integrated (as opposed to coupled) into the HOSS’ solid mechanical solver, allowing for the study of an even wider range of problems. Advancements such as this are leading HOSS to become a tool of choice for multi-physics problems. HOSS has been successfully applied by a myriad of researchers for analysis in rock mechanics, oil and gas industries, engineering application (structural, mechanical and biomedical engineering), mining, blast loading, high velocity impact, as well as seismic and acoustic analysis. This paper intends to summarize the latest development and application efforts for HOSS.
Một Giao Thức Giao Tiếp Tự Thích Ứng với Ứng Dụng Trong Máy Tính Phân Tán Hiệu Suất Cao Đồng Đẳng Dịch bởi AI - 2010
Didier El Baz, The Tung Nguyen
Một giao thức giao tiếp tự thích ứng được đề xuất cho máy tính phân tán đồng đẳng. Giao thức này có thể tự động cấu hình theo đặc điểm của ứng dụng và sự thay đổi cấu trúc bằng cách lựa chọn chế độ giao tiếp phù hợp nhất giữa các đồng đẳng. Giao thức được thiết kế để có thể sử dụng trong môi trường phi tập trung cho máy tính phân tán hiệu suất cao. Một bộ thí nghiệm tính toán đầu tiên cũng đã được trình bày và phân tích cho một ứng dụng tối ưu hóa, nghĩa là các vấn đề mạng luồng phi tuyến tính.
#giao thức giao tiếp #giao thức tự thích ứng #vi-giao thức #máy tính hiệu suất cao #máy tính đồng đẳng #tối ưu hóa phi tuyến #vấn đề dòng chảy mạng
LogSafe: Secure and Scalable Data Logger for IoT Devices - Trang 141-152 - 2018
Hung Nguyen, Radoslav Ivanov, Linh T.X. Phan, Oleg Sokolsky, James Weimer, Insup Lee
As devices in the Internet of Things (IoT) increase in number and integrate with everyday lives, large amounts of personal information will be generated. With multiple discovered vulnerabilities in current IoT networks, a malicious attacker might be able to get access to and misuse this personal data. Thus, a logger that stores this information securely would make it possible to perform forensic analysis in case of such attacks that target valuable data. In this paper, we propose LogSafe, a scalable, fault-tolerant logger that leverages the use of Intel Software Guard Extensions (SGX) to store logs from IoT devices efficiently and securely. Using the security guarantees of SGX, LogSafe is designed to run on an untrusted cloud infrastructure and satisfies Confidentiality, Integrity, and Availability (CIA) security properties. Finally, we provide an exhaustive evaluation of LogSafe in order to demonstrate that it is capable of handling logs from a large number of IoT devices and at a very high data transmission rate.
#cloud based #secure logger #intel software guard extensions #iot logger
