[go: up one dir, main page]

Khan et al., 2023 - Google Patents

TrustDroid: Enhancing Trust and Privacy for Android Mobile Phones by Preventing Riskware and SMS Malware

Khan et al., 2023

Document ID
6576855081729137150
Author
Khan A
Sharma I
Publication year
Publication venue
2023 2nd International Conference on Futuristic Technologies (INCOFT)

External Links

Snippet

Android mobile phones are widely targeted by SMS Malware and Riskware attacks for stealing users' private information like user credentials, pictures, videos, banking credentials etc. Android users are not aware of the incoming link or message and unintentionally allow …
Continue reading at ieeexplore.ieee.org (other versions)

Classifications

    • 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
    • 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
    • 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
    • G06F21/30—Authentication, i.e. establishing the identity or authorisation of security principals
    • G06F21/31—User authentication
    • G06F21/34—User authentication involving the use of external additional devices, e.g. dongles or smart cards
    • 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
    • G06F21/30—Authentication, i.e. establishing the identity or authorisation of security principals
    • G06F21/31—User authentication
    • G06F21/32—User authentication using biometric data, e.g. fingerprints, iris scans or voiceprints
    • 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
    • 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

Similar Documents

Publication Publication Date Title
Srivastava et al. XAI for cybersecurity: state of the art, challenges, open issues and future directions
Kumari et al. Verification and validation techniques for streaming big data analytics in internet of things environment
Andronio et al. Heldroid: Dissecting and detecting mobile ransomware
Dada et al. Performance evaluation of machine learning algorithms for detection and prevention of malware attacks
Kalla et al. Phishing detection implementation using databricks and artificial Intelligence
Shin et al. Focusing on the weakest link: A similarity analysis on phishing campaigns based on the att&ck matrix
Khan et al. TrustDroid: Enhancing Trust and Privacy for Android Mobile Phones by Preventing Riskware and SMS Malware
Birthriya et al. A comprehensive survey of social engineering attacks: taxonomy of attacks, prevention, and mitigation strategies
Thakral et al. Cybersecurity and ethics for IoT system: A massive analysis
Akram et al. A systematic literature review: usage of logistic regression for malware detection
Vähäkainu et al. Cyberattacks against critical infrastructure facilities and corresponding countermeasures
Ferreira Malicious URL detection using machine learning algorithms
Sendjaja et al. Cybersecurity in the digital age: Developing robust strategies to protect against evolving global digital threats and cyber attacks
Kshetri et al. algoXSSF: Detection and analysis of cross-site request forgery (XSRF) and cross-site scripting (XSS) attacks via Machine learning algorithms
Zala et al. Intrusion detection system using machine learning
Tabassum et al. A review on malicious URLs detection using machine learning methods
Mynuddin et al. Cyber security system using fuzzy logic
AlMasri et al. Detecting Spyware in Android Devices Using Random Forest
Amrollahi et al. A survey on application of big data in fin tech banking security and privacy
Chacko et al. Intrusion Detection using Machine Learning Techniques: An exhaustive review
Rasool et al. SHA-AMD: sample-efficient hyper-tuned approach for detection and identification of Android malware family and category
Amar et al. Weighted LSTM for intrusion detection and data mining to prevent attacks
Khan et al. SAndro: Artificial Intelligence Enabled Detection Framework of Adware Attacks on Android Machines
Zoghi Ensemble Classifier Design and Performance Evaluation for Intrusion Detection Using UNSW-NB15 Dataset
Aanonsen et al. Advanced Data Science Model for Detecting Intelligent Malware