An improved DDoS detection using hybrid N-Gram heuristic technique
Distributed denial-of-service (DDoS) is a type of attack that has existed since 1990, in which the volume and intensity of DDoS continues to increase. At the end of 2014, it was reported that the DDoS attack was the most popular attack technique (ArborNetworks, 2014). Thus, DDoS is one of the major...
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my.uthm.eprints.43502022-01-16T01:03:12Z http://eprints.uthm.edu.my/4350/ An improved DDoS detection using hybrid N-Gram heuristic technique Maslan, Andi Muhammmad, Kamarudin Malik T58.5-58.64 Information technology TA190-194 Management of engineering works Distributed denial-of-service (DDoS) is a type of attack that has existed since 1990, in which the volume and intensity of DDoS continues to increase. At the end of 2014, it was reported that the DDoS attack was the most popular attack technique (ArborNetworks, 2014). Thus, DDoS is one of the major threats of cyberspace and a major cyber security issue. DDoS is referred to as the preferred weapon of hackers as it has proven to be a permanent threat to users, organizations and infrastructure on the Internet (BussinessWeek, 2014). A survey of over 5,000 companies found that 37% of Distributed Denial of Service (DDoS) attacks damaged the company's reputation, causing subscriber trust to decrease. Customer loss and reputation damage is one of the most feared consequences of DDoS attacks (39%). This fear even exceeds the cost of recovery from DDoS attacks (28%), or loss of revenue caused by downtime related to it (26%). The survey also found that more than half of the companies surveyed lost business data (57%), or access to sensitive and important business information (56%). As a result of DDoS attacks also affect the company's trading activities (42%) (Warta Ekonomi.co.id, Jakarta. Juli 2016). On the other hand, network attacks represent a risk to the integrity, confidentiality and availability of resources provided by the organization[1]. Penerbit UTHM Ibrahim, Rosziati Jamel, Sapi'ee 2017 Book Section PeerReviewed text en http://eprints.uthm.edu.my/4350/1/Chapter%206_DEISS_S1.pdf Maslan, Andi and Muhammmad, Kamarudin Malik (2017) An improved DDoS detection using hybrid N-Gram heuristic technique. In: Research Book – Data Engineering and Information Security Series 1. Penerbit UTHM, Batu Pahat, Johor, pp. 41-57. ISBN 9789672110583 |
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T58.5-58.64 Information technology TA190-194 Management of engineering works Maslan, Andi Muhammmad, Kamarudin Malik An improved DDoS detection using hybrid N-Gram heuristic technique |
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Distributed denial-of-service (DDoS) is a type of attack that has existed since 1990, in which the volume and intensity of DDoS continues to increase. At the end of 2014, it was reported that the DDoS attack was the most popular attack technique (ArborNetworks, 2014). Thus, DDoS is one of the major threats of cyberspace and a major cyber security issue. DDoS is referred to as the preferred weapon of hackers as it has proven to be a permanent threat to users, organizations and infrastructure on the Internet (BussinessWeek, 2014). A survey of over 5,000 companies found that 37% of Distributed Denial of Service (DDoS) attacks damaged the company's reputation, causing subscriber trust to decrease. Customer loss and reputation damage is one of the most feared consequences of DDoS attacks (39%). This fear even exceeds the cost of recovery from DDoS attacks (28%), or loss of revenue caused by downtime related to it (26%). The survey also found that more than half of the companies surveyed lost business data (57%), or access to sensitive and important business information (56%). As a result of DDoS attacks also affect the company's trading activities (42%) (Warta Ekonomi.co.id, Jakarta. Juli 2016). On the other hand, network attacks represent a risk to the integrity, confidentiality and availability of resources provided by the organization[1]. |
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Ibrahim, Rosziati |
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Ibrahim, Rosziati Maslan, Andi Muhammmad, Kamarudin Malik |
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Book Section |
author |
Maslan, Andi Muhammmad, Kamarudin Malik |
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Maslan, Andi |
title |
An improved DDoS detection using hybrid N-Gram heuristic technique |
title_short |
An improved DDoS detection using hybrid N-Gram heuristic technique |
title_full |
An improved DDoS detection using hybrid N-Gram heuristic technique |
title_fullStr |
An improved DDoS detection using hybrid N-Gram heuristic technique |
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An improved DDoS detection using hybrid N-Gram heuristic technique |
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improved ddos detection using hybrid n-gram heuristic technique |
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Penerbit UTHM |
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2017 |
url |
http://eprints.uthm.edu.my/4350/1/Chapter%206_DEISS_S1.pdf http://eprints.uthm.edu.my/4350/ |
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