A Novel Graph-based Mechanism for Identifying Traffic Vulnerabilities in Smart Home IoT

Jia, Yizhen; Xiao, Yinhao; Yu, Jiguo; Cheng, Xiuzhen; Liang, Zhenkai; Wan, Zhiguo

doi:10.1109/infocom.2018.8486369

Cited by 55 publications

(24 citation statements)

References 9 publications

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“…Therefore, consuming considerable amount of time. Luo et al [17], proposed a technique that performs reverse engineering of IoT protocols, to identify the message format of [18] verified the effectiveness graph-based analysis on a smart home system prototype. The prototype consisted of a smartphone controlling a smart light pulp and a Google home speaker.…”

Section: Detecting Iot Network Vulnerabilitiesmentioning

confidence: 98%

SIEM-based detection and mitigation of IoT-botnet DDoS attacks

Al-Duwairi

Al-Kahla

AlRefai

et al. 2020

IJECE

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The Internet of Things (IoT) is becoming an integral part of our daily life including health, environment, homes, military, etc. The enormous growth of IoT in recent years has attracted hackers to take advantage of their computation and communication capabilities to perform different types of attacks. The major concern is that IoT devices have several vulnerabilities that can be easily exploited to form IoT botnets consisting of millions of IoT devices and posing significant threats to Internet security. In this context, DDoS attacks originating from IoT botnets is a major problem in today’s Internet that requires immediate attention. In this paper, we propose a Security Information and Event Management-based IoT botnet DDoS attack detection and mitigation system. This system detects and blocks DDoS attack traffic from compromised IoT devices by monitoring specific packet types including TCP SYN, ICMP and DNS packets originating from these devices. We discuss a prototype implementation of the proposed system and we demonstrate that SIEM based solutions can be configured to accurately identify and block malicious traffic originating from compromised IoT devices.

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Section: Detecting Iot Network Vulnerabilitiesmentioning

confidence: 98%

SIEM-based detection and mitigation of IoT-botnet DDoS attacks

Al-Duwairi

Al-Kahla

AlRefai

et al. 2020

IJECE

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“…There are also many complex models based on mathematical theories solving network vulnerabilities. An idea proposed in [155] was based on a novel graph mechanism that analyzed the network traffics to show weak elements of IoT infrastructure. In [156] was proposed a gateway system that controls the networking domain of IoT home infrastructure.…”

Section: B Security In Data Managementmentioning

confidence: 99%

Smart Homes: How Much Will They Support Us? A Research on Recent Trends and Advances

et al. 2021

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The advances in the Internet of Things (IoT) provide several chances to develop a variety of innovations supporting smart home users in several industries including healthcare, energy management, etc. Ubiquitous support by intelligent appliances at modern homes, which constantly work to gather information can help us to solve everyday issues. In this paper, we present a comparative study of recent advances in smart home development. The study aims to present the main trends in this field. During the analysis of the research reports and patents, we identify the propositions that constitute the main research streams. Through extensive analysis, we provide an outlook on the wide spectrum of the proposed solutions. We also analyze the main market to present which publishers are leading with the innovative science in this field. We also show the leaders of science and technology in the World. Finally, we define the ratio of the developments and outline the next stage of the development in the smart home industry. INDEX TERMS Internet of Things (IoT), smart home, healthcare, energy management, security. I. INTRODUCTION O VER time, the type of home was evolving. The shape of the house was evolving during ages, cultural revolutions, and climate changes. We have divided our homes into rooms devoted to sleeping, cooking, work, children, sanitary needs, warehousing, etc. People started to settle in various locations and continents.

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“…3). Android's container-based Keystore system 8 supports the protection of private keys used to authenticate the MMEEs to the LMM. Furthermore, if not embedded in the OS, we assume that MMEEs are only installed from official sources, e. g., Google Play Store, to restrict the deployment of modified implementations.…”

Section: A Implementation and General Set-upmentioning

confidence: 99%

“…1) Effectiveness: We evaluate DEMONS' effectiveness using existing smart home attacks identified by [8] and relying on our attacker model (cf. Sec.…”

Section: B Security Evaluationmentioning

confidence: 99%

DEMONS: Extended Manufacturer Usage Description to Restrain Malicious Smartphone Apps

Fink

Serror

Wehrle

2021

2021 IEEE 46th Conference on Local Computer Networks (LCN)

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The growing popularity of the consumer IoT intensifies the risks for security and privacy breaches. It typically suffices to successfully attack a single IoT device to access the home network illicitly. This observation emphasizes the need for in-network security, complementing each device's security mechanisms with additional network-layer protection. Recently, the IETF proposed Manufacturer Usage Description (MUD) to limit network traffic of IoT devices to their required minimum. However, the tangled communication of IoT devices, e.g., connections to smartphones and smart speakers, is not covered by MUD. We propose Distributed Enforcement of MUD on Smartphones (DEMONS), extending central enforcement of MUD with distributed enforcement at authenticated smartphones to mitigate the threats of malicious apps and IoT devices by filtering malicious traffic close to its origin and preventing further spread. We discuss the security gains and demonstrate that the introduced overhead regarding latency, bandwidth, and power consumption has a negligible performance impact.Index Terms-security and privacy, smart home, Internet of Things, access control, policy-based network security, MUD

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A Novel Graph-based Mechanism for Identifying Traffic Vulnerabilities in Smart Home IoT

Cited by 55 publications

References 9 publications

SIEM-based detection and mitigation of IoT-botnet DDoS attacks

SIEM-based detection and mitigation of IoT-botnet DDoS attacks

Smart Homes: How Much Will They Support Us? A Research on Recent Trends and Advances

DEMONS: Extended Manufacturer Usage Description to Restrain Malicious Smartphone Apps

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