1,769 research outputs found

    An IoT analysis framework: An investigation of IoT smart cameras' vulnerabilities

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    Security Analysis and Evaluation of Smart Toys

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    During the last years, interconnectivity and merging the physical and digital technological dimensions have become a topic attracting the interest of the modern world. Internet of Things (IoT) is rapidly evolving as it manages to transform physical devices into communicating agents which can consecutively create complete interconnected systems. A sub-category of the IoT technology is smart toys, which are devices with networking capabilities, created for and used in play. Smart toys’ targeting group is usually children and they attempt to provide a higher level of entertainment and education by offering an enhanced and more interactive experience. Due to the nature and technical limitations of IoT devices, security experts have expressed concerns over the effectiveness and security level of smart devices. The importance of securing IoT devices has an increased weight when it pertains to smart toys, since sensitive information of children and teenagers can potentially be compromised. Furthermore, various security analyses on smart toys have discovered a worryingly high number of important security flaws. The master thesis focuses on the topic of smart toys’ security by first presenting and analyzing the necessary literature background. Furthermore, it presents a case study where a smart toy is selected and analyzed statically and dynamically utilizing a Raspberry Pi. The aim of this thesis is to examine and apply methods of analysis used in the relevant literature, in order to identify security flaws in the examined smart toy. The smart toy is a fitness band whose target consumers involve children and teenagers. The fitness band is communicating through Bluetooth with a mobile device and is accompanied by a mobile application. The mobile application has been installed and tested on an Android device. Finally, the analyses as well as their emerged results are presented and described in detail. Several security risks have been identified indicating that developers must increase their efforts in ensuring the optimal level of security in smart toys. Furthermore, several solutions that could minimize security risks and are related to our findings are suggested, along with potentially interesting topics for future work and further research

    Addressing Insider Threats from Smart Devices

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    Smart devices have unique security challenges and are becoming increasingly common. They have been used in the past to launch cyber attacks such as the Mirai attack. This work is focused on solving the threats posed to and by smart devices inside a network. The size of the problem is quantified; the initial compromise is prevented where possible, and compromised devices are identified. To gain insight into the size of the problem, campus Domain Name System (DNS) measurements were taken that allow for wireless traffic to be separated from wired traffic. Two-thirds of the DNS traffic measured came from wireless hosts, implying that mobile devices are playing a bigger role in networks. Also, port scans and service discovery protocols were used to identify Internet of Things (IoT) devices on the campus network and follow-up work was done to assess the state of the IoT devices. Motivated by these findings, three solutions were developed. To handle the scenario when compromised mobile devices are connected to the network, a new strategy for steppingstone detection was developed with both an application layer and a transport layer solution. The proposed solution is effective even when the mobile device cellular connection is used. Also, malicious or vulnerable applications make it through the mobile app store vetting process. A user space tool was developed that identifies apps contacting malicious domains in real time and collects data for research purposes. Malicious app behavior can then be identified on the user’s device, catching malicious apps that were overlooked by software vetting. Last, the variety of IoT device types and manufacturers makes the job of keeping them secure difficult. A generic framework was developed to lighten the management burden of securing IoT devices, serve as a middle box to secure legacy devices, and also use DNS queries as a way to identify misbehaving devices

    Wireless networks

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    This module provides an introduction to wireless networks in general and wireless LANs in particular. It describes and explains what the different wireless technologies are, their main features, security issues, advantages, disadvantages and uses or applications.Peer ReviewedPostprint (published version

    Smart homes under siege: Assessing the robustness of physical security against wireless network attacks

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    © 2024 The Authors. Published by Elsevier Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY), https://creativecommons.org/licenses/by/4.0/Nowadays domestic smart security devices, such as smart locks, smart doorbells, and security cameras, are becoming increasingly popular with users, due to their ease of use, convenience, and declining prices. Unlike conventional non-smart security devices, such as alarms and locks, performance standards for smart security devices, such as the British TS 621, are not easily understandable by end users due to the technical language employed. Users also have very few sources of unbiased information regarding product performance in real world conditions and protection against attacks from cyber attacker-burglars and, as a result, tend to take manufacturer claims at face value. This means that, as this work proves, users may be exposed to threats, such as theft, impersonation (should an attacker steal their credentials), and even physical injury, if the device fails and is used to prevent access to hazardous environments. As such, this paper deploys several attacks using popular wireless attack vectors (i.e., 433MHz radio, Bluetooth, and RFID) against domestic smart security devices to assess the protection offered against a cyber attacker-burglar. Our results suggest that users are open to considerable cyber physical attacks, irrespective if they use lesser known (i.e., no name) or branded smart security devices, due to the poor security offered by these devices.Peer reviewe
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