New Developments In Network Forensics - Tools and Techniques

被引:0
|
作者
Hunt, Ray [1 ,2 ,3 ,4 ]
机构
[1] Univ Canterbury, Dept Comp Sci, Christchurch, New Zealand
[2] Univ South Australia, Adelaide, SA, Australia
[3] Deakin Univ, Melbourne, Vic, Australia
[4] Edith Cowan Univ, Perth, WA, Australia
来源
2012 18th IEEE International Conference on Networks (ICON) | 2012年
关键词
network and digital forensics; intrusion detection; network forensic tools; malware; IP traceback; honeypot; critical infrastructure and botnet forensics;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Network forensics is a branch of digital forensics which has evolved recently as a very important discipline used in monitoring and analysing network traffic - particularly for the purposes of tracing intrusions and attacks. This paper presents an analysis of the tools and techniques used in network forensic analysis. It further examines the application of network forensics to vital areas such as malware and network attack detection; IP traceback and honeypots; and intrusion detection. Further, the paper addresses new and emerging areas of network forensic development which include critical infrastructure forensics, wireless network forensics, as well as its application to social networking.
引用
收藏
页码:376 / 381
页数:6
相关论文
共 50 条
  • [41] Neural projection techniques for the visual inspection of network traffic
    Herrero, Alvaro
    Corchado, Emilio
    Gastaldo, Paolo
    Zunino, Rodolfo
    NEUROCOMPUTING, 2009, 72 (16-18) : 3649 - 3658
  • [42] Improving Network Security Using Machine Learning Techniques
    Akbar, Shaik
    Chandulal, J. A.
    Rao, K. Nageswara
    Kumar, G. Sudheer
    2012 IEEE INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND COMPUTING RESEARCH (ICCIC), 2012, : 76 - 80
  • [43] Intrusion detection techniques in network environment: a systematic review
    Ayyagari, Maruthi Rohit
    Kesswani, Nishtha
    Kumar, Munish
    Kumar, Krishan
    WIRELESS NETWORKS, 2021, 27 (02) : 1269 - 1285
  • [44] Intrusion detection techniques in network environment: a systematic review
    Maruthi Rohit Ayyagari
    Nishtha Kesswani
    Munish Kumar
    Krishan Kumar
    Wireless Networks, 2021, 27 : 1269 - 1285
  • [45] Anomaly Detection by Using CFS Subset and Neural Network with WEKA Tools
    Jabez, J.
    Gowri, S.
    Vigneshwari, S.
    Mayan, J. Albert
    Srinivasulu, Senduru
    INFORMATION AND COMMUNICATION TECHNOLOGY FOR INTELLIGENT SYSTEMS, ICTIS 2018, VOL 2, 2019, 107 : 675 - 682
  • [46] Network Intrusion Detection for IoT Security Based on Learning Techniques
    Chaabouni, Nadia
    Mosbah, Mohamed
    Zemmari, Akka
    Sauvignac, Cyrille
    Faruki, Parvez
    IEEE COMMUNICATIONS SURVEYS AND TUTORIALS, 2019, 21 (03): : 2671 - 2701
  • [47] Empirical Framework for Situation Awareness Measurement Techniques in Network Defense
    Evangelopoulou, Maria
    Johnson, Christopher W.
    2015 International Conference on Cyber Situational Awareness, Data Analytics and Assessment (CyberSA), 2015,
  • [48] Intelligent Techniques for Detecting Network Attacks: Review and Research Directions
    Aljabri, Malak
    Aljameel, Sumayh S.
    Mohammad, Rami Mustafa A.
    Almotiri, Sultan H.
    Mirza, Samiha
    Anis, Fatima M.
    Aboulnour, Menna
    Alomari, Dorieh M.
    Alhamed, Dina H.
    Altamimi, Hanan S.
    SENSORS, 2021, 21 (21)
  • [50] Comparison of classification techniques applied for network intrusion detection and classification
    Aziz, Amira Sayed A.
    EL-Ola Hanafi, Sanaa
    Hassanien, Aboul Ella
    JOURNAL OF APPLIED LOGIC, 2017, 24 : 109 - 118