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/library/oar/handle/123456789/107791Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.date.accessioned | 2023-03-28T06:02:20Z | - |
| dc.date.available | 2023-03-28T06:02:20Z | - |
| dc.date.issued | 2022 | - |
| dc.identifier.citation | Sinagra, J. (2022). Smart secure homes: a solution to the cyber security threats in our smart homes (Bachelor's dissertation). | en_GB |
| dc.identifier.uri | https://www.um.edu.mt/library/oar/handle/123456789/107791 | - |
| dc.description | B.Sc. (Hons)(Melit.) | en_GB |
| dc.description.abstract | A smart home is made up of various smart devices connected to a network, each with a specific set of functions. These devices tend to simplify the lives of the users by providing services according to their requirements. Thus, resulting in a more comfortable, convenient and secure home. Problems occur when home cyber security systems are not strong enough (due to poor configuration or default passwords, for example) to stop unauthorized people from compromising a device connected to the network. In addition, some of the devices installed in smart homes do not have enough processing power to implement strong security features. These problems can be solved by placing a security device between the modem connecting to the Internet Service Provider (ISP) and the rest of the home network which aims to provide an extra layer of security in the network. This device can act as a firewall and/or an Intrusion Detection System (IDS). The aim of this project is to implement a security device, using either a personal computer or a Raspberry Pi, that secures a home network whilst requiring minimal technical know-how from the user. Snort 3, an IDS that features a new design and a superset of Snort 2, was used to inspect incoming requests to the network and warn the user if it detected a flood attack, such as an Internet Control Message Protocol (ICMP), Synchronize (SYN) or User Datagram Protocol (UDP) attack. Snort 3 was also configured to protect the internal network against such an attack. Results obtained during these attacks, such as network throughput, percentage Central Processing Unit (CPU) and memory usage, determined which device was the most efficient and provided the best performance. | en_GB |
| dc.language.iso | en | en_GB |
| dc.rights | info:eu-repo/semantics/restrictedAccess | en_GB |
| dc.subject | Home automation | en_GB |
| dc.subject | Computer security | en_GB |
| dc.subject | Machine learning | en_GB |
| dc.title | Smart secure homes : a solution to the cyber security threats in our smart homes | en_GB |
| dc.type | bachelorThesis | en_GB |
| dc.rights.holder | The copyright of this work belongs to the author(s)/publisher. The rights of this work are as defined by the appropriate Copyright Legislation or as modified by any successive legislation. Users may access this work and can make use of the information contained in accordance with the Copyright Legislation provided that the author must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the prior permission of the copyright holder. | en_GB |
| dc.publisher.institution | University of Malta | en_GB |
| dc.publisher.department | Faculty of 福利在线免费 and Communication Technology. Department of Communications and Computer Engineering | en_GB |
| dc.description.reviewed | N/A | en_GB |
| dc.contributor.creator | Sinagra, Jayden (2022) | - |
| Appears in Collections: | Dissertations - FacICT - 2022 Dissertations - FacICTCCE - 2022 | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 22BCE012.pdf Restricted Access | 3.73 MB | Adobe PDF | View/Open Request a copy |
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