Results 71 to 80 of about 12,725 (233)
, 2022 DoH-DGA-Malware-Traffic-HKD (csv_files.zip, l3-malware.csv, pcap_files.zip, and README.txt): If you use the dataset, please be sure to cite the following paper.Rikima Mitsuhashi, Yong Jin, Katsuyoshi Iida, Takahiro Shinagawa, and Yoshiaki Takai ...
Jin, Yong +4 more
core +1 more source
DQN‐Guided Subset‐Induced OCSVM Kernel Approximation for Imbalanced Anomaly Detection
IEEJ Transactions on Electrical and Electronic Engineering, EarlyView.Anomaly detection under limited normal data remains a fundamental challenge due to severe class imbalance and scarcity of anomalies. We propose a novel framework that reformulates support vector selection in One‐Class SVM as a sequential decision‐making problem.
Wenqian Yu, Jiaying Wu, Jinglu Hu
wiley +1 more source
Intrusion detection and management over the world wide web [PDF]
, 2010 As the Internet and society become ever more integrated so the number of Internet users continues to grow. Today there are 1.6 billion Internet users. They use its services to work from home, shop for gifts, socialise with friends, research the family ...
Luan, Hai Ying, Hai Ying Luan
core
IEEE AccessThe cyber realm is overwhelmed with dynamic malware that promptly penetrates all defense mechanisms, operates unapprehended to the user, and covertly causes damage to sensitive data.
Faiza Babar Khan +5 more
doaj +1 more source
Smart malware detection on Android [PDF]
Security and Communication Networks, 2015 AbstractNowadays, because of its increased popularity, Android is target to a growing number of attacks and malicious applications, with the purpose of stealing private information and consuming credit by subscribing to premium services. Most of the current commercial antivirus solutions use static signatures for malware detection, which may fail to ...
Laura Gheorghe +6 more
openaire +1 more source
, 2022 This book constitutes the refereed proceedings of the 7th International Conference on Detection of Intrusions and Malware, and Vulnerability Assessment, DIMVA 2010, held in Bonn, Germany, in July 2010.The 12 revised full papers presented together with ...
core +1 more source
Graph neural network‐based attack prediction for communication‐based train control systems
CAAI Transactions on Intelligence Technology, EarlyView.Abstract The Advanced Persistent Threats (APTs) have emerged as one of the key security challenges to industrial control systems. APTs are complex multi‐step attacks, and they are naturally diverse and complex. Therefore, it is important to comprehend the behaviour of APT attackers and anticipate the upcoming attack actions.
Junyi Zhao +3 more
wiley +1 more source
Detecting Malware with Information Complexity
CoRR, 2015 This work focuses on a specific front of the malware detection arms-race, namely the detection of persistent, disk-resident malware. We exploit normalised compression distance (NCD), an information theoretic measure, applied directly to binaries. Given a zoo of labelled malware and benign-ware, we ask whether a suspect program is more similar to our ...
Nadia Alshahwan +3 more
openaire +2 more sources
, 2016 The prevalence of mobile devices has increased rapidly in recent years. People store valuable data like personal and financial information on those devices.
Kamil Akhuseyinoglu +3 more
core +1 more source
BlockDroid: detection of Android malware from images using lightweight convolutional neural network models with ensemble learning and blockchain for mobile devices [PDF]
PeerJ Computer ScienceDue to the increase in the volume and diversity of malware targeting Android systems, research on detecting this harmful software is steadily growing. Traditional malware detection studies require significant human intervention and resource consumption ...
Emre Şafak +3 more
doaj +2 more sources