[go: up one dir, main page]

Da-Yu et al., 2019 - Google Patents

Extracting Suspicious IP Addresses from WhatsApp Network Traffic in Cybercrime Investigations

Da-Yu et al., 2019

Document ID
8246223069274169874
Author
Da-Yu K
Chang E
Fu-Ching T
Publication year
Publication venue
2019 21st International Conference on Advanced Communication Technology (ICACT)

External Links

Snippet

Sniffers are among the commonest approaches for capturing network traffic activities and collecting digital evidences in cybercrime investigations. The ubiquity of instant messaging (IM) apps on smartphones has provided criminals with communication channels that are …
Continue reading at ieeexplore.ieee.org (other versions)

Classifications

    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L63/00Network architectures or network communication protocols for network security
    • H04L63/14Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic
    • H04L63/1408Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic by monitoring network traffic
    • H04L63/1425Traffic logging, e.g. anomaly detection
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04MTELEPHONIC COMMUNICATION
    • H04M3/00Automatic or semi-automatic exchanges
    • H04M3/22Supervisory, monitoring, management, i.e. operation, administration, maintenance or testing arrangements
    • H04M3/2281Call monitoring, e.g. for law enforcement purposes; Call tracing; Detection or prevention of malicious calls
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L63/00Network architectures or network communication protocols for network security
    • H04L63/14Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic
    • H04L63/1408Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic by monitoring network traffic
    • H04L63/1416Event detection, e.g. attack signature detection
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04MTELEPHONIC COMMUNICATION
    • H04M7/00Interconnection arrangements between switching centres
    • H04M7/006Networks other than PSTN/ISDN providing telephone service, e.g. Voice over Internet Protocol (VoIP), including next generation networks with a packet-switched transport layer
    • H04M7/0078Security; Fraud detection; Fraud prevention
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L63/00Network architectures or network communication protocols for network security
    • H04L63/30Network architectures or network communication protocols for network security for supporting lawful interception, monitoring or retaining of communications or communication related information
    • H04L63/306Network architectures or network communication protocols for network security for supporting lawful interception, monitoring or retaining of communications or communication related information intercepting packet switched data communications, e.g. Web, Internet or IMS communications

Similar Documents

Publication Publication Date Title
Ahmed et al. Whatsapp network forensics: Discovering the ip addresses of suspects
McCoy et al. Shining light in dark places: Understanding the Tor network
Chaabane et al. Digging into anonymous traffic: A deep analysis of the tor anonymizing network
Khan et al. A comprehensive review on adaptability of network forensics frameworks for mobile cloud computing
Sakib et al. Using anomaly detection based techniques to detect HTTP-based botnet C&C traffic
Sudozai et al. Forensics study of IMO call and chat app
Mazhar Rathore et al. Exploiting encrypted and tunneled multimedia calls in high-speed big data environment
Wijesinghe et al. An enhanced model for network flow based botnet detection
De Luca Fiscone et al. Network forensics of WhatsApp: a practical approach based on side-channel analysis
Guan et al. An empirical analysis of plugin-based tor traffic over SSH tunnel
Tsai et al. WhatsApp network forensics: Discovering the communication payloads behind cybercriminals
Agrawal et al. A survey on analyzing encrypted network traffic of mobile devices
Barbosa et al. Simpleweb/university of twente traffic traces data repository
Aryeh et al. Graphical analysis of captured network packets for detection of suspicious network nodes
Heidemann et al. Uses and challenges for network datasets
Alotibi et al. Behavioral-based feature abstraction from network traffic
Da-Yu et al. Extracting Suspicious IP Addresses from WhatsApp Network Traffic in Cybercrime Investigations
Lin et al. A cloud-based forensics tracking scheme for online social network clients
Buric et al. Challenges in network forensics
Sarhan et al. VoIP Network Forensics of Instant Messaging Calls
Umrani et al. Network forensic analysis of Twitter application on Android OS
Wrana et al. The spectre of surveillance and censorship in future internet architectures
Ibrahim et al. Modelling based approach for reconstructing evidence of VoIP malicious attacks
Pilli et al. Data reduction by identification and correlation of TCP/IP attack attributes for network forensics
Sudozai et al. Signatures of viber security traffic