[go: up one dir, main page]

Hashemi et al., 2008 - Google Patents

Detecting intrusion transactions in databases using data item dependencies and anomaly analysis

Hashemi et al., 2008

View PDF
Document ID
10935864717161697093
Author
Hashemi S
Yang Y
Zabihzadeh D
Kangavari M
Publication year
Publication venue
Expert Systems

External Links

Snippet

The purpose of the intrusion detection system (IDS) database is to detect transactions that access data without permission. This paper proposes a novel approach to identifying malicious transactions. The approach concentrates on two aspects of database …
Continue reading at www.researchgate.net (PDF) (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
    • G06F21/554—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
    • G06F21/316—User authentication by observing the pattern of computer usage, e.g. typical user behaviour
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/30286—Information retrieval; Database structures therefor; File system structures therefor in structured data stores
    • G06F17/30587—Details of specialised database models
    • 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
    • G06F21/60—Protecting data
    • G06F21/62—Protecting access to data via a platform, e.g. using keys or access control rules
    • G06F21/6218—Protecting access to data via a platform, e.g. using keys or access control rules to a system of files or objects, e.g. local or distributed file system or database

Similar Documents

Publication Publication Date Title
Alam et al. Phishing attacks detection using machine learning approach
Liu et al. Log2vec: A heterogeneous graph embedding based approach for detecting cyber threats within enterprise
Nguyen et al. Design and implementation of intrusion detection system using convolutional neural network for DoS detection
Bilge et al. Riskteller: Predicting the risk of cyber incidents
JP7302019B2 (en) Hierarchical Behavior Modeling and Detection Systems and Methods for System-Level Security
Basnet et al. Rule-based phishing attack detection
CN119254489B (en) Information network security self-defense method and system based on trusted computing
Kim et al. Empirical evaluation of SVM-based masquerade detection using UNIX commands
Stolfo et al. A comparative evaluation of two algorithms for windows registry anomaly detection
Srivastava et al. Database Intrusion Detection using Weighted Sequence Mining.
Dutt et al. Real-time hybrid intrusion detection system using machine learning techniques
Alazab et al. Using response action with intelligent intrusion detection and prevention system against web application malware
Sahasrabuddhe et al. Survey on intrusion detection system using data mining techniques
Mohammadi et al. New class‐dependent feature transformation for intrusion detection systems
EP4024252B1 (en) A system and method for identifying exploited cves using honeypots
Hashemi et al. Detecting intrusion transactions in databases using data item dependencies and anomaly analysis
Datta et al. Real-time threat detection in ueba using unsupervised learning algorithms
Sohrabi et al. Detecting intrusion transactions in database systems: a novel approach
Montaruli et al. Raze to the ground: Query-efficient adversarial html attacks on machine-learning phishing webpage detectors
Adebiyi et al. An SQL injection detection model using chi-square with classification techniques
Niranjan et al. Security in data mining-a comprehensive survey
Elshoush et al. Intrusion alert correlation framework: An innovative approach
Patil et al. Learning to Detect Phishing Web Pages Using Lexical and String Complexity Analysis.
CN117792741A (en) Network attack detection and source tracing method based on behavioral characteristic analysis
Wei et al. WebHound: a data-driven intrusion detection from real-world web access logs