Resistance of IoT Sensors against DDoS Attack in Smart Home Environment

Smart devices along with sensors are gaining in popularity with the promise of making life easier for the owner. As the number of sensors in an Internet of Things (IoT) system grows, a question arises as to whether the transmission between the sensors and the IoT devices is reliable and whether the user receives alerts correctly and in a timely manner. Increased deployment of IoT devices with sensors increases possible safety risks. It is IoT devices that are often misused to create Distributed Denial of Service (DDoS) attacks, which is due to the weak security of IoT devices against misuse. The article looks at the issue from the opposite point of view, when the target of a DDoS attack are IoT devices in a smart home environment. The article examines how IoT devices and the entire smart home will behave if they become victims of a DDoS attack aimed at the smart home from the outside. The question of security was asked in terms of whether a legitimate user can continue to control and receive information from IoT sensors, which is available during normal operation of the smart home. The case study was done both from the point of view of the attack on the central units managing the IoT sensors directly, as well as on the smart-home personal assistant systems, with which the user can control the IoT sensors. The article presents experimental results for individual attacks performed in the case study and demonstrates the resistance of real IoT sensors against DDoS attack. The main novelty of the article is that the implementation of a personal assistant into the smart home environment increases the resistance of the user’s communication with the sensors. This study is a pilot testing the selected sensor sample to show behavior of smart home under DDoS attack.

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A Context-Aware Information Model for Elderly Homecare Services in a Smart Home

Volume 5: 35th Design Automation Conference, Parts A and B ◽

10.1115/detc2009-86673 ◽

2009 ◽

Cited By ~ 1

Author(s):

Feng Zhou ◽

Jianxin Roger Jiao ◽

Songlin Chen ◽

Daqing Zhang

Keyword(s):

Home Environment ◽

Smart Home ◽

Rough Set Theory ◽

Research Problem ◽

Information Model ◽

Context Aware ◽

Sensor Platform ◽

Smart Home Environment ◽

Manual Assistance

One of the critical situations facing the society across the globe is the problem of elderly homecare services (EHS) due to the aggravation of the society coupled with diseases and limited social resources. This problem has been typically dealt with by manual assistance from caregivers and/or family members. The emerging Ambience Intelligence (AmI) technology suggests itself to be of great potential for EHS applications, owing to its strength in constructing a pervasive computing environment that is sensitive and responsive to the presence of human users. The key challenge of AmI implementation lies in context awareness, namely how to align with the specific decision making scenarios of particular EHS applications. This paper proposes a context-aware information model in a smart home to tackle the EHS problem. Mainly, rough set theory is applied to construct user activity models for recognizing various activities of daily living (ADLs) based on the sensor platform constructed in a smart home environment. Subsequently, issues of case comprehension and homecare services are also discussed. A case study in the smart home environment is presented. Initial findings from the case study suggest the importance of the research problem, as well as the feasibility and potential of the proposed framework.

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Cybersecurity Attacks in Vehicle-to-Infrastructure Applications and Their Prevention

Transportation Research Record Journal of the Transportation Research Board ◽

10.1177/0361198118799012 ◽

2018 ◽

Vol 2672 (19) ◽

pp. 66-78 ◽

Cited By ~ 7

Author(s):

Mhafuzul Islam ◽

Mashrur Chowdhury ◽

Hongda Li ◽

Hongxin Hu

Keyword(s):

Denial Of Service ◽

Data Communication ◽

Point Of View ◽

Environmental Benefits ◽

Connected Vehicle ◽

Ddos Attack ◽

Stop Sign ◽

Vehicle To Infrastructure ◽

The Impact

A connected vehicle (CV) environment is comprised of diverse computing infrastructure, data communication and dissemination, and data collection systems that are vulnerable to the same cyberattacks as all traditional computing environments. Cyberattacks can jeopardize the expected safety, mobility, energy, and environmental benefits from CV applications. As cyberattacks can lead to severe consequences such as traffic incidents, it has become one of the primary concerns in CV applications. In this paper, we evaluate the impact of cyberattacks on the vehicle-to-infrastructure (V2I) network from a V2I application point of view. Then, we develop a novel V2I cybersecurity architecture, named CVGuard, which can detect and prevent cyberattacks on the V2I applications. In designing CVGuard, key challenges, such as scalability, resiliency and future usability were considered. A case study using a distributed denial of service (DDoS) attack on a V2I application, “Stop Sign Gap Assist (SSGA)” application, shows that CVGuard was effective in mitigating the adverse safety effects created by a DDoS attack. In our case study, because of the DDoS attack, conflicts between the minor and major road vehicles occurred at an unsignalized intersection, which could have caused crashes. A reduction of conflicts between vehicles occurred because CVGuard was in operation. The reduction of conflicts was compared based on the number of conflicts before and after the implementation and operation of the CVGuard security platform. Analysis revealed that the strategies adopted by CVGuard were successful in reducing the conflicts by 60% where a DDoS attack compromised the SSGA application at an unsignalized intersection.

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Vulnerabilities in IoT Devices for Smart Home Environment

Proceedings of the 5th International Conference on Information Systems Security and Privacy ◽

10.5220/0007583306150622 ◽

2019 ◽

Cited By ~ 1

Author(s):

Luís Costa ◽

João Barros ◽

Miguel Tavares

Keyword(s):

Home Environment ◽

Smart Home ◽

Smart Home Environment ◽

Iot Devices

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Inference of Human Intentions in Smart Home Environments

International Journal of Robotics Applications and Technologies ◽

10.4018/ijrat.2013070103 ◽

2013 ◽

Vol 1 (2) ◽

pp. 26-42

Author(s):

Katsunori Oyama ◽

Carl K. Chang ◽

Simanta Mitra

Keyword(s):

Home Environment ◽

Smart Home ◽

Context Aware ◽

Different Types ◽

Human Intention ◽

Smart Home Environment ◽

System Requirements ◽

Context Aware System ◽

Context Models

Most of context models have limited capability in involving human intention for system evolvability and self-adaptability. Human intention in context aware systems can evolve at any time; however, context aware systems based on these context models can provide only standard services that are often insufficient for specific user needs. Consequently, evolving human intentions result in changes in system requirements. Moreover, an intention must be analyzed from tangled relations with different types of contexts. In the past, this complexity has prevented researchers from using computational methods for analyzing or specifying human intention in context aware system design. The authors investigated the possibility for inferring human intentions from contexts and situations, and deploying appropriate services that users require during system run-time. This paper presents an inference ontology to represent stepwise inference tasks, and then evaluate contexts surrounding a user who accesses PCs through a case study of the smart home environment.

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