Botnets

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advanced botnet detection techniques
Age Group_Uncategorized
Age Group_Uncategorized
analysis
architecture
automatic-update
B01=Georgios Kambourakis
B01=Marios Anagnostopoulos
B01=Peng Zhou
B01=Weizhi Meng
Big Data
blockchain security
Bot Herder
botnet
Botnet Detection
botnet ecosystem
Botnet-as-a-Service
C2 Channel
Category1=Non-Fiction
Category=UBL
Category=UR
Category=URD
Category=URH
Category=UT
Category=UYF
cloud
COP=United Kingdom
Covert Channels
cryptocurrency mining
cryptocurrency mining threats
cybercrime
cybersecurity research
Data Set
DDoS attack
defense
Delivery_Pre-order
Destination IP Address
detection
DNS Traffic
DoS Attack
economics
eq_bestseller
eq_computing
eq_isMigrated=2
eq_nobargain
eq_non-fiction
Evasion Mechanisms
ICMP
infiltration
Information Hiding Techniques
Internet of Things
Internet-of-things based botnets
IoT
IoT Device
IP Address
IRC Protocol
IRC Server
Language_English
Launch DDOS Attack
malware analysis
mobile botnet
Mobile Botnets
monitoring
Network Steganography
P2P Botnets
PA=Temporarily unavailable
peer-to-peer (P2P) botnet
peer-to-peer networks
Port Tcp
Price_€100 and above
PS=Active
Public IP Address
security
Social Bots
social network
softlaunch
state-of-the-art botnet architectures
steganography methods
TCP Connection
traffic
Unsupervised Machine Learning
Unsupervised Ml Algorithm
void countermeasures

Product details

  • ISBN 9780367191542
  • Weight: 800g
  • Dimensions: 156 x 234mm
  • Publication Date: 08 Oct 2019
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Hardback
  • Language: English
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This book provides solid, state-of-the-art contributions from both scientists and practitioners working on botnet detection and analysis, including botnet economics. It presents original theoretical and empirical chapters dealing with both offensive and defensive aspects in this field. Chapters address fundamental theory, current trends and techniques for evading detection, as well as practical experiences concerning detection and defensive strategies for the botnet ecosystem, and include surveys, simulations, practical results, and case studies.

Dr. Marios Anagnostopoulos received his Ph.D. degree in information and

communication systems engineering from the Department of Information and

Communication Systems Engineering, University of the Aegean, Greece, in 2016.

The title of his doctoral thesis was “DNS as a multipurpose attack vector.”

Currently, he is Post-Doctoral Research Fellow in the Norwegian University of

Science and Technology (NTNU). Prior to joining NTNU, he worked as Post-

Doctoral Research Fellow in the Singapore University of Technology and Design

(SUTD). His research interests are in the fields of network security and privacy,

mobile and wireless networks security, cyber-physical security, and blockchain in

security and privacy.

Dr. Georgios Kambourakis received the Ph.D. degree in information and communication

systems engineering from the Department of Information and Communications

Systems Engineering, University of the Aegean, Greece, where he is

currently an associate professor, and the head of the department. His research

interests are in the fields of mobile and wireless networks security and privacy. He

has over 120 refereed publications in the aforementioned fields of study. For more

information, please visit http://www.icsd.aegean.gr/gkamb.

Dr. Weizhi Meng is currently an assistant professor in the Cyber Security Section,

Department of Applied Mathematics and Computer Science, Technical University

of Denmark (DTU), Denmark. He received his Ph.D. degree in computer science

from the City University of Hong Kong (CityU), China. Prior to joining DTU, he

worked as a research scientist in Institute for Infocomm Research, A*Star, Singapore,

and as a senior research associate in CS Department, CityU. He won the Outstanding

Academic Performance Award during his doctoral study and is a recipient of

the Hong Kong Institution of Engineers (HKIE) Outstanding Paper Award for

Young Engineers/Researchers in both 2014 and 2017. He is also a recipient of Best

Paper Award from ISPEC 2018 and Best Student Paper Award from NSS 2016. His

primary research interests are cyber security and intelligent technology in security,

including intrusion detection, smartphone security, biometric authentication, HCI

security, trust management, blockchain in security, and malware analysis.

Dr. Peng Zhou is currently an associate professor at Shanghai University. He has

received his Ph.D. degree from the Hong Kong Polytechnic University and

worked as a research fellow in Singapore Nanyang Technological University for

one year. His research interests include network security, computer worms and

propagation, and machine learning.