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Showing 1 - 5 of
5 matches in All Departments
Data stealing is a major concern on the internet as hackers and
criminals have begun using simple tricks to hack social networks
and violate privacy. Cyber-attack methods are progressively modern,
and obstructing the attack is increasingly troublesome, regardless
of whether countermeasures are taken. The Dark Web especially
presents challenges to information privacy and security due to
anonymous behaviors and the unavailability of data. To better
understand and prevent cyberattacks, it is vital to have a forecast
of cyberattacks, proper safety measures, and viable use of
cyber-intelligence that empowers these activities. Dark Web Pattern
Recognition and Crime Analysis Using Machine Intelligence discusses
cyberattacks, security, and safety measures to protect data and
presents the shortcomings faced by researchers and practitioners
due to the unavailability of information about the Dark Web.
Attacker techniques in these Dark Web environments are highlighted,
along with intrusion detection practices and crawling of hidden
content. Covering a range of topics such as malware and fog
computing, this reference work is ideal for researchers,
academicians, practitioners, industry professionals, computer
scientists, scholars, instructors, and students.
The Dark Web is a known hub that hosts myriad illegal activities
behind the veil of anonymity for its users. For years now, law
enforcement has been struggling to track these illicit activities
and put them to an end. However, the depth and anonymity of the
Dark Web has made these efforts difficult, and as cyber criminals
have more advanced technologies available to them, the struggle
appears to only have the potential to worsen. Law enforcement and
government organizations also have emerging technologies on their
side, however. It is essential for these organizations to stay up
to date on these emerging technologies, such as computational
intelligence, in order to put a stop to the illicit activities and
behaviors presented in the Dark Web. Using Computational
Intelligence for the Dark Web and Illicit Behavior Detection
presents the emerging technologies and applications of
computational intelligence for the law enforcement of the Dark Web.
It features analysis into cybercrime data, examples of the
application of computational intelligence in the Dark Web, and
provides future opportunities for growth in this field. Covering
topics such as cyber threat detection, crime prediction, and
keyword extraction, this premier reference source is an essential
resource for government organizations, law enforcement agencies,
non-profit organizations, politicians, computer scientists,
researchers, students, and academicians.
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Robotic Process Automation
Romil Rawat, Rajesh Kumar Chakrawarti, Sanjaya Kumar Sarangi, Rahul Choudhary, Anand Singh Gadwal, …
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R5,440
R4,970
Discovery Miles 49 700
Save R470 (9%)
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Ships in 10 - 15 working days
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ROBOTIC PROCESS AUTOMATION Presenting the latest technologies and
practices in this ever-changing field, this groundbreaking new
volume covers the theoretical challenges and practical solutions
for using robotics across a variety of industries, encompassing
many disciplines, including mathematics, computer science,
electrical engineering, information technology, mechatronics,
electronics, bioengineering, and command and software engineering.
Robotics is the study of creating devices that can take the place
of people and mimic their behaviors. Mechanical engineering,
electrical engineering, information engineering, mechatronics,
electronics, bioengineering, computer engineering, control
engineering, software engineering, mathematics, and other subjects
are all included in robotics. Robots can be employed in a variety
of scenarios and for a variety of objectives, but many are now
being used in hazardous areas (such as radioactive material
inspection, bomb detection, and deactivation), manufacturing
operations, or in conditions where humans are unable to live (e.g.
in space, underwater, in high heat, and clean up and containment of
hazardous materials and radiation). Walking, lifting, speaking,
cognition, and any other human activity are all attempted by
robots. Many of today’s robots are influenced by nature, making
bio-inspired robotics a growing area. Defusing explosives, seeking
survivors in unstable ruins, and investigating mines and shipwrecks
are just a few of the activities that robots are designed to
undertake. This groundbreaking new volume presents a Robotic
Process Automation (RPA) software technique that makes it simple to
create, deploy, and manage software robots that mimic human
movements while dealing with digital systems and software. Software
robots can interpret what’s on a screen, type the correct
keystrokes, traverse systems, locate and extract data, and do a
wide variety of predetermined operations, much like people.
Software robots can do it quicker and more reliably than humans,
without having to stand up and stretch or take a coffee break.
The Dark Web is a known hub that hosts myriad illegal activities
behind the veil of anonymity for its users. For years now, law
enforcement has been struggling to track these illicit activities
and put them to an end. However, the depth and anonymity of the
Dark Web has made these efforts difficult, and as cyber criminals
have more advanced technologies available to them, the struggle
appears to only have the potential to worsen. Law enforcement and
government organizations also have emerging technologies on their
side, however. It is essential for these organizations to stay up
to date on these emerging technologies, such as computational
intelligence, in order to put a stop to the illicit activities and
behaviors presented in the Dark Web. Using Computational
Intelligence for the Dark Web and Illicit Behavior Detection
presents the emerging technologies and applications of
computational intelligence for the law enforcement of the Dark Web.
It features analysis into cybercrime data, examples of the
application of computational intelligence in the Dark Web, and
provides future opportunities for growth in this field. Covering
topics such as cyber threat detection, crime prediction, and
keyword extraction, this premier reference source is an essential
resource for government organizations, law enforcement agencies,
non-profit organizations, politicians, computer scientists,
researchers, students, and academicians.
Data stealing is a major concern on the internet as hackers and
criminals have begun using simple tricks to hack social networks
and violate privacy. Cyber-attack methods are progressively modern,
and obstructing the attack is increasingly troublesome, regardless
of whether countermeasures are taken. The Dark Web especially
presents challenges to information privacy and security due to
anonymous behaviors and the unavailability of data. To better
understand and prevent cyberattacks, it is vital to have a forecast
of cyberattacks, proper safety measures, and viable use of
cyber-intelligence that empowers these activities. Dark Web Pattern
Recognition and Crime Analysis Using Machine Intelligence discusses
cyberattacks, security, and safety measures to protect data and
presents the shortcomings faced by researchers and practitioners
due to the unavailability of information about the Dark Web.
Attacker techniques in these Dark Web environments are highlighted,
along with intrusion detection practices and crawling of hidden
content. Covering a range of topics such as malware and fog
computing, this reference work is ideal for researchers,
academicians, practitioners, industry professionals, computer
scientists, scholars, instructors, and students.
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