Results 71 to 80 of about 97,198 (223)

A Hybrid Framework for Stock Price Forecasting Using Metaheuristic Feature Selection Approaches and Transformer Models Enhanced by Temporal Embedding and Attention Pruning

Applied AI Letters, Volume 7, Issue 1, February 2026.
Workflow of the proposed hybrid BWO‐Transformer framework for stock price prediction. ABSTRACT Accurately predicting stock prices remains a major challenge in financial analytics due to the complexity and noise inherent in market data. Feature selection plays a critical role in improving both computational efficiency and predictive performance. In this
Amirhossein Malakouti Semnani, Sohrab Kordrostami, Amirhossein Refahi Sheikhani, Mohammad Hossein Moattar   +3 more
wiley   +1 more source

Large-Scale Analysis on Anti-Analysis Techniques in Real-World Malware

IEEE Access, 2022
To dynamically identify malicious behaviors of millions of Windows malware, anti-virus vendors have widely been using sandbox-based analyzers. However, the sandbox-based analysis has a critical limitation that anti-analysis techniques (i.e., Anti-sandbox
Minho Kim, Haehyun Cho, Jeong Hyun Yi
doaj   +1 more source

PlaceRaider: Virtual Theft in Physical Spaces with Smartphones [PDF]

, 2012
As smartphones become more pervasive, they are increasingly targeted by malware. At the same time, each new generation of smartphone features increasingly powerful onboard sensor suites.
Crandall, David, Kapadia, Apu, Rahman, Zahid, Templeman, Robert   +3 more
core  

The Influence of Big Data‐Driven Educational Technologies on College Teaching Development

Engineering Reports, Volume 8, Issue 2, February 2026.
Exploring the impact of big data on college instructors: enhancing teaching, fostering professional growth, and addressing challenges in data adoption and privacy. ABSTRACT The rapid development of big data and mobile Internet technologies has significantly influenced the instructional growth of college instructors. This study investigated how big data
Ling Yu, Wenye Li, Ying Luo
wiley   +1 more source

A3CM: Automatic Capability Annotation for Android Malware

IEEE Access, 2019
Android malware poses serious security and privacy threats to the mobile users. Traditional malware detection and family classification technologies are becoming less effective due to the rapid evolution of the malware landscape, with the emerging of so ...
Junyang Qiu, Jun Zhang, Wei Luo, Lei Pan, Surya Nepal, Yu Wang, Yang Xiang   +6 more
doaj   +1 more source

Security Toolbox for Detecting Novel and Sophisticated Android Malware

, 2015
This paper presents a demo of our Security Toolbox to detect novel malware in Android apps. This Toolbox is developed through our recent research project funded by the DARPA Automated Program Analysis for Cybersecurity (APAC) project.
Deering, Tom, Holland, Benjamin, Kothari, Suresh, Mathews, Jon, Ranade, Nikhil   +4 more
core   +1 more source

Malware and Malware Detection Techniques: A Survey

International Journal for Research in Applied Science and Engineering Technology, 2022
Abstract: Malicious software is a kind of software or codes which took some: private data, information from the PC framework, its tasks is to do only malicious objectives to the PC framework, without authorization of the PC clients. The effect of malicious software are worsen to the client.
Sahil Sehrawat, Dr. Dinesh Singh
openaire   +1 more source

A Machine Learning Framework for Detecting and Preventing Cyber‐Attacks in Industrial Cyber‐Physical Systems

Engineering Reports, Volume 8, Issue 1, January 2026.
Proposed cyber physical system security framework. ABSTRACT The increasing adoption of cyber‐physical systems (CPS) in Industry 4.0 has heightened vulnerability to cyber threats. This study proposes a machine learning–based intrusion detection framework, DBID‐Net, to effectively identify and prevent attacks in CPS environments. The framework integrates
Anurag Sinha, Rejuwan Shamim, Mihika Mahendra, Trupti Mohota, G. Madhukar Rao, Mohammad Nadeem Ahmed, Mohammad Rashid Hussain, Satyam Solanki, Tanish Ranjan, Bhaskar, Mini Kumari, Karan Dixit, Vyom Modi, Syed Immamul Ansarullah, Mohd Asif Shah   +14 more
wiley   +1 more source

Explainable AI With Imbalanced Learning Strategies for Blockchain Transaction Fraud Detection

Engineering Reports, Volume 8, Issue 1, January 2026.
Research methodology pipeline for blockchain fraud detection. ABSTRACT Blockchain networks now support billions of dollars in daily transactions, making reliable and transparent fraud detection essential for maintaining user trust and financial stability.
Ahmed Abbas Jasim Al‐Hchaimi, M. A. Khalifa, Walid El‐Shafai   +2 more
wiley   +1 more source

Generating Synthetic Malware Samples Using Generative AI

IEEE Access
Malware attacks have a significant negative impact on organizations of varied scales in the field of cybersecurity. Recently, malware researchers have increasingly turned to machine learning techniques to combat sophisticated obfuscation methods used in ...
Tiffany Bao, Kylie Trousil, Quang Duy Tran, Fabio Di Troia, Younghee Park   +4 more
doaj   +1 more source