Mishra et al., 2023 - Google Patents
Dsmishsms-a system to detect smishing smsMishra et al., 2023
View HTML- Document ID
- 1525186449205201676
- Author
- Mishra S
- Soni D
- Publication year
- Publication venue
- Neural Computing and Applications
External Links
Snippet
With the origin of smart homes, smart cities, and smart everything, smart phones came up as an area of magnificent growth and development. These devices became a part of daily activities of human life. This impact and growth have made these devices more vulnerable to …
- 238000001514 detection method 0 abstract description 78
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/14—Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic
- H04L63/1441—Countermeasures against malicious traffic
- H04L63/1483—Countermeasures against malicious traffic service impersonation, e.g. phishing, pharming or web spoofing
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
- G06F21/50—Monitoring users, programs or devices to maintain the integrity of platforms, e.g. of processors, firmware or operating systems
- G06F21/55—Detecting local intrusion or implementing counter-measures
- G06F21/56—Computer malware detection or handling, e.g. anti-virus arrangements
- G06F21/562—Static detection
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/14—Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic
- H04L63/1408—Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic by monitoring network traffic
- H04L63/1425—Traffic logging, e.g. anomaly detection
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/14—Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic
- H04L63/1408—Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic by monitoring network traffic
- H04L63/1416—Event detection, e.g. attack signature detection
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
- G06F21/50—Monitoring users, programs or devices to maintain the integrity of platforms, e.g. of processors, firmware or operating systems
- G06F21/55—Detecting local intrusion or implementing counter-measures
- G06F21/554—Detecting local intrusion or implementing counter-measures involving event detection and direct action
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/14—Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic
- H04L63/1441—Countermeasures against malicious traffic
- H04L63/1458—Denial of Service
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/14—Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic
- H04L63/1441—Countermeasures against malicious traffic
- H04L63/145—Countermeasures against malicious traffic the attack involving the propagation of malware through the network, e.g. viruses, trojans or worms
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/36—Image preprocessing, i.e. processing the image information without deciding about the identity of the image
- G06K9/46—Extraction of features or characteristics of the image
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/14—Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic
- H04L63/1433—Vulnerability analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/20—Image acquisition
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
- G06F21/70—Protecting specific internal or peripheral components, in which the protection of a component leads to protection of the entire computer
- G06F21/82—Protecting input, output or interconnection devices
- G06F21/83—Protecting input, output or interconnection devices input devices, e.g. keyboards, mice or controllers thereof
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Mishra et al. | Dsmishsms-a system to detect smishing sms | |
Mishra et al. | Smishing Detector: A security model to detect smishing through SMS content analysis and URL behavior analysis | |
Salloum et al. | Phishing email detection using natural language processing techniques: a literature survey | |
Butt et al. | Cloud-based email phishing attack using machine and deep learning algorithm | |
El-Alfy | Detection of phishing websites based on probabilistic neural networks and K-medoids clustering | |
Rao et al. | PhishDump: A multi-model ensemble based technique for the detection of phishing sites in mobile devices | |
Mishra et al. | Implementation of ‘smishing detector’: An efficient model for smishing detection using neural network | |
Kumar Birthriya et al. | A comprehensive survey of phishing email detection and protection techniques | |
Anitha et al. | A new hybrid deep learning-based phishing detection system using MCS-DNN classifier | |
Shalke et al. | Social engineering attack and scam detection using advanced natural langugae processing algorithm | |
Nivedha et al. | Improving phishing URL detection using fuzzy association mining | |
Alanazi et al. | A hybrid NLP and domain validation technique for disposable email detection | |
Saraswat et al. | Phishing detection in e-mails using machine learning | |
Shoaib et al. | An investigation in detection and mitigation of smishing using machine learning techniques | |
Patil et al. | Learning to Detect Phishing Web Pages Using Lexical and String Complexity Analysis. | |
Butt et al. | Intelligent Phishing Url Detection: A Solution Based On Deep Learning Framework | |
Das et al. | Learning a deep neural network for predicting phishing website | |
NaliniPriya et al. | Phishing attack detection using machine learning | |
Shravasti et al. | Smishing detection: Using artificial intelligence | |
Innab et al. | Phishing Attacks Detection Using Ensemble Machine Learning Algorithms. | |
Mahmood et al. | A Smishing Detection Method Based on SMS Contents Analysis and URL Inspection Using Google Engine and VirusTotal | |
Akinwale et al. | Detection and binary classification of spear-phishing emails in organizations using a hybrid machine learning approach | |
Kawale et al. | Machine learning based phishing website detection | |
Rahim et al. | A survey on anti-phishing techniques: From conventional methods to machine learning | |
Saleem | The p-fryer: Using machine learning and classification to effectively detect phishing emails |