Cyber Attacks, Countermeasures, and Protection Schemes- A State of the Art Survey

被引:0
作者
Shabut, Antesar M. [1 ]
Lwin, K. T. [1 ]
Hossain, M. A. [1 ]
机构
[1] Anglia Ruskin Univ, Chelmsford, Essex, England
来源
PROCEEDINGS OF 2016 10TH INTERNATIONAL CONFERENCE ON SOFTWARE, KNOWLEDGE, INFORMATION MANAGEMENT & APPLICATIONS (SKIMA) | 2016年
关键词
cyber security; cyber attacks; attack taxonomy; existing protection tools; INTELLIGENT PHISHING DETECTION; SYSTEM;
D O I
暂无
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
Thousands of cyber-attacks (fraudulent online activities to acquire users' sensitive information via email, during online transactions, live video streaming, online gaming and browsing) are launched every day against Internet users across the world. To prevent these attacks, researchers have responded with a number of protection systems. Currently, the methods which cyber-attackers use to conduct attacks is associated with exploiting humans. Such attacks are recorded more frequently than before, and they are more challenging to control. Traditional security countermeasures are unable to prevent breaches targeting the human element. This paper describes the state of the art of cyber security attacks, countermeasures, and protection tools related to everyday online activities. It provides a useful cyber-attack taxonomy and classification which helps to involve in a protection process to identify attacks and measures for cyber security. Existing protection schemes that target the cyber threats and risks are evaluated against three of our criteria for an effective measure: resilience to cyber-attacks' countermeasures; real-time support and needs-based action; and training and educational materials to increase users' awareness of cybercrimes. Potential features of smart solutions to cybercrime are also identified.
引用
收藏
页码:37 / 44
页数:8
相关论文
共 29 条
[1]   Phishing detection based Associative Classification data mining [J].
Abdelhamid, Neda ;
Ayesh, Aladdin ;
Thabtah, Fadi .
EXPERT SYSTEMS WITH APPLICATIONS, 2014, 41 (13) :5948-5959
[2]   Intelligent phishing detection system for e-banking using fuzzy data mining [J].
Aburrous, Maher ;
Hossain, M. A. ;
Dahal, Keshav ;
Thabtah, Fadi .
EXPERT SYSTEMS WITH APPLICATIONS, 2010, 37 (12) :7913-7921
[3]  
[Anonymous], 11 ANN NETW DISTRIB
[4]  
[Anonymous], INC CYBERCIEGE INTR
[5]  
[Anonymous], PHISH ED LAND PAG PR
[6]  
[Anonymous], IJCSNS INT J COMPUT
[7]  
[Anonymous], SEC FUT
[8]  
[Anonymous], 2016, Internet security threat report
[9]  
[Anonymous], DATA BREACHES UK HEA
[10]  
[Anonymous], PHISH TOOLS TECHN