Privacy Concerns, IoT Devices and Attacks in Smart Cities

Alnahari, Wael; Quasim, Mohammad Tabrez

doi:10.1109/icoten52080.2021.9493559

Cited by 5 publications

(3 citation statements)

References 20 publications

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“…The overall research consists of various plausibility studies for hardware, software and algorithms. The AI-based algorithmic evaluation is been initiated and published [4]. This systematic experimental evaluation presented in this paper is confined to understand the capability of input network interface(s) of Raspberry-Pi.…”

Section: Key Challenges To Consider In Raspberrymentioning

confidence: 99%

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Raspberry Pi-based Intelligent Cyber Defense Systems for SMEs and Smart-homes: An Exploratory Study

Tirumala

Nepal²,

Ray

2022

EAI Endorsed Trans Smart Cities

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Ongoing ransomware attacks have forced business to think about security of their resources. Recently, small- to-medium enterprises (SMEs) and Smart-homes have become easy targets for attackers since they don’t have cyber defense mechanism in place other than simple firewall systems which are quite vulnerable. Cyber defense systems are costly and often not within the budget of SMEs or families which inspired to think about low cost yet highly efficient cyber defense solutions. Regular individuals and families who use internet for day to day use often end-up becoming a possible resource for using them as Trojan or bitcoin nodes. This research explores the prospects of implementing a Raspberry Pi (Raspberry Pi)-based intelligent cyber- defense system (iCDS) for SME networks and Smart-homes to filter malicious contents from incoming traffic and detect malware using artificial intelligence. Primarily, the work presented in this paper tries to evaluate the hardware capability of network interfaces (both internal, and attached) of Raspberry Pi for handle high volumes of incoming traffic. For this, we measure the network performance of the Raspberry Pi using the speed test software and try to explore the possibility of a light weight machine learning (ML) based malware detection. The results show that the built in Ethernet interface outperforms the built in WiFi and external attached USB to Ethernet Adapter in terms of latency, download and upload throughput. Also, a new DNA based ML approach was successfully able to produce over 19.5% better accuracy rates of over classifier trained with hash-sequence. The experiment results further emphasise on the importance of generating complex malware signatures with variety to face existing threats which has taken a new form due to increase in malware based attacks, particularly for ransomware. The complexity of the generated malware is based on generic yet strong encryption principles which produced good results which is quite encouraging at this stage.

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Section: Key Challenges To Consider In Raspberrymentioning

confidence: 99%

“…Also, considering the recent events where gaming devices are used for mining bitcoins, there is a high chance for Smart-Homes being easy targets by hackers. Hence, the internal networks of SMEs and Smart-Homes have to be secured enough to prevent such external attacks [4].…”

Section: Introductionmentioning

confidence: 99%

Raspberry Pi-based Intelligent Cyber Defense Systems for SMEs and Smart-homes: An Exploratory Study

Tirumala

Nepal²,

Ray

2022

EAI Endorsed Trans Smart Cities

View full text Add to dashboard Cite

show abstract

“…This may, in turn, affect the adoption rate of IoT solutions in the home domain (Neupane et al, 2021). Therefore, researchers have called for further research on the effects of privacy and security on user adoption in the smart home domain (e.g., Ismagilova et al, 2020) and (Alnahari & Quasim, 2021). Despite this, even the few studies that have investigated the effects of privacy and security on IoT adoption in smart cities have mainly considered the whole city as the context of their study and from a broader organizational perspective (Ismagilova et al, 2020;Tawalbeh et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Users’ Privacy and Security Concerns that Affect IoT Adoption in the Home Domain

Schuster

Habibipour

2022

International Journal of Human–Computer Interaction

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Internet of things (IoT) technology must provide users with benefits that outweigh the costs and risks for it to be widely accepted and adopted. New functionality is continuously added, and costs decrease with the increasing volumes and technological advances; however, the risks also increase as technology becomes increasingly integrated into human lives. This survey study of 251 respondents investigated how users and different user groups perceive IoT security and privacy in the home domain, their trust in the involved parties, and how different types of measures, as suggested by the literature, can affect user adoption. The results indicate that people are particularly concerned about security and privacy and are fearful of breaches and misuse. A large majority of the people do not believe the products to be secure. Less than a third of the users trust manufacturers, service providers, and governments to uphold their privacy; this remarkably hinders IoT adoption.

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Enhanced mechanism to prioritize the cloud data privacy factors using AHP and TOPSIS: a hybrid approach

Khan,

Shoaib,

Husain

et al. 2024

J Cloud Comp

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Cloud computing is a new paradigm in this new cyber era. Nowadays, most organizations are showing more reliability in this environment. The increasing reliability of the Cloud also makes it vulnerable. As vulnerability increases, there will be a greater need for privacy in terms of data, and utilizing secure services is highly recommended. So, data on the Cloud must have some privacy mechanisms to ensure personal and organizational privacy. So, for this, we must have an authentic way to increase the trust and reliability of the organization and individuals The authors have tried to create a way to rank things that uses the Analytical Hieratical Process (AHP) and the Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS). Based on the result and comparison, produce some hidden advantages named cost, benefit, risk and opportunity-based outcomes of the result.In this paper, we are developing a cloud data privacy model; for this, we have done an intensive literature review by including Privacy factors such as Access Control, Authentication, Authorization, Trustworthiness, Confidentiality, Integrity, and Availability. Based on that review, we have chosen a few parameters that affect cloud data privacy in all the phases of the data life cycle. Most of the already available methods must be revised per the industry’s current trends. Here, we will use Analytical Hieratical Process and Technique for Order Preference by Similarity to the Ideal Solution method to prove that our claim is better than other cloud data privacy models. In this paper, the author has selected the weights of the individual cloud data privacy criteria and further calculated the rank of individual data privacy criteria using the AHP method and subsequently utilized the final weights as input of the TOPSIS method to rank the cloud data privacy criteria.

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Privacy Concerns, IoT Devices and Attacks in Smart Cities

Cited by 5 publications

References 20 publications

Raspberry Pi-based Intelligent Cyber Defense Systems for SMEs and Smart-homes: An Exploratory Study

Raspberry Pi-based Intelligent Cyber Defense Systems for SMEs and Smart-homes: An Exploratory Study

Users’ Privacy and Security Concerns that Affect IoT Adoption in the Home Domain

Enhanced mechanism to prioritize the cloud data privacy factors using AHP and TOPSIS: a hybrid approach

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