dc.contributor.advisor | Kazi, Sadia Hamid | |
dc.contributor.author | Nur, Md. Walid Bin | |
dc.date.accessioned | 2018-01-03T04:30:08Z | |
dc.date.available | 2018-01-03T04:30:08Z | |
dc.date.copyright | 2017 | |
dc.date.issued | 2017 | |
dc.identifier.other | ID 13101112 | |
dc.identifier.uri | http://hdl.handle.net/10361/8878 | |
dc.description | This thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2017. | en_US |
dc.description | Cataloged from PDF version of thesis report. | |
dc.description | Includes bibliographical references (page 33-35). | |
dc.description.abstract | IoT has the potential to affect our ways of life. It is the next step of Internet where
all the physical objects around us will be connected to each other. According to
Gartner, by 2020 there will be over 26 billion connected devices. However, the
security of such a big network of interconnected devices is of paramount
importance. According to a report from Russian-based Kaspersky Labs, botnets -
not spam, viruses or worm- currently pose the biggest threat to the
Internet.However, few works that have been done on this issue in the recentpast are
not successful on themselves alone. In this paper, I present an in depth
understanding of the problem and propose a mechanism to counter this issue. My
proposal is based on Transductive Confidence Machines, which was previously
proposed as a mechanism to provide confidence measures on classification
decisions. It proposes to make use of this algorithm with the help of honeypot to
collect attack data and uses these data to make the system more proficient. | en_US |
dc.description.statementofresponsibility | Md. Walid Bin Nur | |
dc.format.extent | 35 pages | |
dc.language.iso | en | en_US |
dc.publisher | BRAC University | en_US |
dc.rights | BRAC University thesis are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. | |
dc.subject | IoT | en_US |
dc.subject | DDoS attack | en_US |
dc.subject | Honeypot | en_US |
dc.subject | TCM-kNN | en_US |
dc.title | Analysis on IOT Botnet and DDOS attack | en_US |
dc.type | Thesis | en_US |
dc.contributor.department | Department of Computer Science and Engineering, BRAC University | |
dc.description.degree | B. Computer Science and Engineering | |