List of Titles

Quick View

Implicit feedback-based group recommender system for internet of things applications

- Guo, Zhiwei, Yu, Keping, Guo, Tan, Bashir, Ali, Imran, Muhammad, Guizani, Mohsen

Authors: Guo, Zhiwei , Yu, Keping , Guo, Tan , Bashir, Ali , Imran, Muhammad , Guizani, Mohsen
Date: 2020
Type: Text , Conference paper
Relation: 2020 IEEE Global Communications Conference, GLOBECOM 2020, Virtual Taipei, 7-11 December 2020 Vol. 2020-January
Full Text:
Reviewed:
Description: With the prevalence of Internet of Things (IoT)-based social media applications, the distance among people has been greatly shortened. As a result, recommender systems in IoT-based social media need to be developed oriented to groups of users rather than individual users. However, existing methods were highly dependent on explicit preference feedbacks, ignoring scenarios of implicit feedbacks. To remedy such gap, this paper proposes an implicit feedback-based group recommender system using probabilistic inference and non-cooperative game (GREPING) for IoT-based social media. Particularly, unknown process variables can be estimated from observable implicit feedbacks via Bayesian posterior probability inference. In addition, the globally optimal recommendation results can be calculated with the aid of non-cooperative game. Two groups of experiments are conducted to assess the GREPING from two aspects: efficiency and robustness. Experimental results show obvious promotion and considerable stability of the GREPING compared to baseline methods. © 2020 IEEE.

Metric learning-based few-shot malicious node detection for IoT backhaul/fronthaul networks

- Zhou, Ke, Lin, Xi, Wu, Jun, Bashir, Ali, Li, Jianhua, Imran, Muhammad

Authors: Zhou, Ke , Lin, Xi , Wu, Jun , Bashir, Ali , Li, Jianhua , Imran, Muhammad
Date: 2022
Type: Text , Conference paper
Relation: 2022 IEEE Global Communications Conference, GLOBECOM 2022, Virtual, online, 4-8 December 2022, 2022 IEEE Global Communications Conference, GLOBECOM 2022 - Proceedings p. 5777-5782
Full Text: false
Reviewed:
Description: The development of backhaul/fronthaul networks can enable low latency and high reliability, but nodes in future networks like Internet of Things (IoT) can conduct malicious activities like flooding attack and DDoS attack, which can decrease QoS of smart backhaul/fronthaul network. Timely detection of malicious nodes in future networks is significant for low-latency backhaul/fronthaul networks. However, conventional supervised learning-based detection models require abundant malicious training samples, while capturing adequate malicious samples can not meet the requirement of timely detection. In this paper, we propose a novel few-shot malicious node detection system for improving QoS of IoT backhaul/fronthaul network, which can detect malicious nodes with unknown malicious activities through a limited number of network traffic samples. In our proposed system, we first design a fresh IoT traffic sample processing approach, which integrates normal activity samples and known malicious activity samples to generate training pairs. Then, we design a metric learning-based malicious node detection model training method, which employs a contrastive loss over distance metric to distinguish between similar and dissimilar pairs of samples. Besides, the trained model can detect nodes with unknown malicious activities by comparing real-time samples with few-shot samples of malicious nodes. Finally, the proposed system is evaluated on a real-world IoT network dataset named N-BaIoT. The exhaustive experiment results show that our model can achieve an average accuracy around 97.67 % when detecting malicious nodes with unknown malicious activities, which is comparable to state-of-the-art supervised learning models while our model only needs 5-shot samples of malicious node. © 2022 IEEE.

Cloud based secure service providing for IoTs using blockchain

- Rehman, Mubariz, Javaid, Nadeem, Awais, Muhammad, Imran, Muhammad, Naseer, Nidal

Authors: Rehman, Mubariz , Javaid, Nadeem , Awais, Muhammad , Imran, Muhammad , Naseer, Nidal
Date: 2019
Type: Text , Conference paper
Relation: 2019 IEEE Global Communications Conference, GLOBECOM 2019, Waikoloa, 9-13 December 2019
Full Text: false
Reviewed:
Description: Internet of Things (IoTs) is widely growing domain of the modern era. With the advancement in technologies, the use of IoTs devices also increases. However, security risks regarding service provisioning and data sharing also increases. There are many existing security approaches. However, these approaches are not suitable for IoTs devices due to their limited storage and computation resources. These secure approaches also require a specific hardware. With the invention of blockchain technologies, many security risks are eliminated. Blockchain also supports data sharing mechanism. In this paper, we proposed a secure service providing mechanism for IoTs using blockchain. We introduced cloud nodes for maintaining the validity states of edge service providers. The edge node reputation is considered as a service rating given by end users. Incentive is given to edge servers after validation of service codes. Incentive is in the form of cryptocurrency. Incentive and edge node reputation values are stored in cloud node and are updated with respect to time. Smart contract is proposed to check the validity state of the edge servers. Smart contract is also used for the comparison and verification of the service codes provided by edge servers. In our proposed system, we perform service authentication at both cloud and edge server layer. Moreover, Proof of Authority (PoA) is used as a consensus mechanism. PoA enhanced overall performance of our proposed system. By experimental analysis, it is shown that our proposed model is suitable for resource constrained devices. © 2019 IEEE.

Security of Internet of Things devices : ethical hacking a drone and its mitigation strategies

- Karmakar, Gour, Petty, Mark, Ahmed, Hassan, Das, Rajkumar, Kamruzzaman, Joarder

Authors: Karmakar, Gour , Petty, Mark , Ahmed, Hassan , Das, Rajkumar , Kamruzzaman, Joarder
Date: 2022
Type: Text , Conference paper
Relation: 2022 IEEE Asia-Pacific Conference on Computer Science and Data Engineering, CSDE 2022, Gold Coast, Australia, 18-20 December 2022, Proceedings of IEEE Asia-Pacific Conference on Computer Science and Data Engineering, CSDE 2022
Full Text: false
Reviewed:
Description: Internet of Things (IoT) is enabling us to introduce cost-effective, innovative and intelligent services in business, industrial, and government application domains. Despite these huge potential benefits of IoT applications, since the backbone of IoT is Internet and IoT connects numerous heterogeneous devices, IoT is vulnerable to many different attacks and thus has been a honey pot to the cybercriminals and hackers. For this reason, the attacks against IoT devices are increasing sharply in recent years. To prevent and detect these attacks, ethical hacking of different IoT devices are of paramount importance. This is because the lesson learnt from these ethical hackings can be exploited to develop effective and robust strategies and mitigation approaches to protect IoT devices from these attacks. There exist a few ethical hacking techniques reported in the literature such as hacking Android phones, Windows XP virtual machine and a DNS rebinding attack on IoT devices. In this paper, we implement an approach for the ethical hacking of a Drone and then hijack it. As an outcome of lesson learnt, the mitigation approaches on how to reduce the hacking on a drone is presented in this paper. © 2022 IEEE.

Measuring trustworthiness of IoT image sensor data using other sensors' complementary multimodal data

- Islam, Mohammad, Karmakar, Gour, Kamruzzaman, Joarder, Murshed, Manzur

Authors: Islam, Mohammad , Karmakar, Gour , Kamruzzaman, Joarder , Murshed, Manzur
Date: 2019
Type: Text , Conference proceedings , Conference paper
Relation: 18th IEEE International Conference on Trust, Security and Privacy in Computing and Communications/13th IEEE International Conference on Big Data Science and Engineering, TrustCom/BigDataSE 2019 p. 775-780
Full Text: false
Reviewed:
Description: Trust of image sensor data is becoming increasingly important as the Internet of Things (IoT) applications grow from home appliances to surveillance. Up to our knowledge, there exists only one work in literature that estimates trustworthiness of digital images applied to forensic applications, based on a machine learning technique. The efficacy of this technique is heavily dependent on availability of an appropriate training set and adequate variation of IoT sensor data with noise, interference and environmental condition, but availability of such data cannot be assured always. Therefore, to overcome this limitation, a robust method capable of estimating trustworthy measure with high accuracy is needed. Lowering cost of sensors allow many IoT applications to use multiple types of sensors to observe the same event. In such cases, complementary multimodal data of one sensor can be exploited to measure trust level of another sensor data. In this paper, for the first time, we introduce a completely new approach to estimate the trustworthiness of an image sensor data using another sensor's numerical data. We develop a theoretical model using the Dempster-Shafer theory (DST) framework. The efficacy of the proposed model in estimating trust level of an image sensor data is analyzed by observing a fire event using IoT image and temperature sensor data in a residential setup under different scenarios. The proposed model produces highly accurate trust level in all scenarios with authentic and forged image data. © 2019 IEEE.
Description: E1

Quick View

Blockchain leveraged task migration in body area sensor networks

- Uddin, Ashraf, Stranieri, Andrew, Gondal, Iqbal, Balasubramanian, Venki

Authors: Uddin, Ashraf , Stranieri, Andrew , Gondal, Iqbal , Balasubramanian, Venki
Date: 2019
Type: Text , Conference proceedings , Conference paper
Relation: 25th Asia-Pacific Conference on Communications, APCC 2019 p. 177-184
Full Text:
Reviewed:
Description: Blockchain technologies emerging for healthcare support secure health data sharing with greater interoperability among different heterogeneous systems. However, the collection and storage of data generated from Body Area Sensor Net-works(BASN) for migration to high processing power computing services requires an efficient BASN architecture. We present a decentralized BASN architecture that involves devices at three levels; 1) Body Area Sensor Network-medical sensors typically on or in patient's body transmitting data to a Smartphone, 2) Fog/Edge, and 3) Cloud. We propose that a Patient Agent(PA) replicated on the Smartphone, Fog and Cloud servers processes medical data and execute a task offloading algorithm by leveraging a Blockchain. Performance analysis is conducted to demonstrate the feasibility of the proposed Blockchain leveraged, distributed Patient Agent controlled BASN. © 2019 IEEE.
Description: E1

Cyber attacks in mechatronics systems based on Internet of Things

- Chowdhury, Abdullahi

Authors: Chowdhury, Abdullahi
Date: 2017
Type: Text , Conference proceedings , Conference paper
Relation: 2017 IEEE International Conference on Mechatronics, ICM 2017; Gippsland, Victoria; 13th-15th February 2017 p. 476-481
Full Text: false
Reviewed:
Description: Internet of things (IoT) systems are becoming multidisciplinary day by day and integrating more and more mechanical, electrical, electronics, control and information disciplines. This integration is making mechatronics systems based on IoT easily available for public uses. Government organisations, different industries, healthcare systems and individual users are using these systems to store different kind of public, private, confidential and classified information. This is attracting cyber attackers to make cyber and cyber physical attacks to these systems. Currently, security policy researchers of both industries and academic institutes are analysing existing cyber attacks and are developing different types of techniques to protect the systems against potential cyber-threats and cyber attacks. This paper analyses the increasing exploitation of IoT based mechatronics system, which has created more opportunities for the current cybercrimes. Contemporary and important mitigation approaches for cyber-crimes have also been articulated in this paper. © 2017 IEEE.
Description: Proceedings - 2017 IEEE International Conference on Mechatronics, ICM 2017

A patient centric agent assisted private blockchain on hyperledger fabric for managing remote patient monitoring

- Wadud, Md Anwar, Amir-Ul-Haque Bhuiyan, T., Uddin, Md Ashraf, Rahman, Md Motiur

Authors: Wadud, Md Anwar , Amir-Ul-Haque Bhuiyan, T. , Uddin, Md Ashraf , Rahman, Md Motiur
Date: 2020
Type: Text , Conference paper
Relation: 11th International Conference on Electrical and Computer Engineering, ICECE 2020 p. 194-197
Full Text: false
Reviewed:
Description: Recently, during the COVID-19 situation, the requirement and importance of tracking patients from a remote location have increased significantly. Most patients now prefer to obtain their doctor's care and check their health status through their mobile phone call, Skype, Facebook Messenger, or other online resources. There is, however, a major concern about the privacy of patients when using online resources. Patients usually choose to keep their information confidential, which should be only accessible to authorized individuals. The most current remote patient monitoring system is organization-centric and patient's privacy and security rely on healthcare providers' mercy. Blockchain technologies have attracted the attention of researchers for designing eHealth applications to provide patients with secure and privacy-preserving health services. Blockchain researchers have recently proposed some models for remote patient monitoring systems. However, most of those researchers have applied public blockchains where health data is available to all participants with the property of data tamper-proof. In this paper, we propose a novel remote patient monitoring model using a decentralized private blockchain to protect patient's privacy and increase the system's efficiency. The private blockchain will be implemented on Hyperledger Fabric where a Patient-centric Agents (PCA) manage patient's data and coordinate authorization to form a secure channel to transmit data to the private blockchain. A hybrid consensus by combining Proof of Integrity (PoI) and Proof of Validity (PoV) is used to protect data privacy and integrity when retrieving data from a blockchain-based cloud database. Finally, the Merkle Tree algorithm was used for data processing and authentication when collecting data and uploading it to a cloud database. © 2020 IEEE.

Cybersecurity risks in meat processing plant and impacts on total productive maintenance

- Chundhoo, Vickram, Chattopadhyay, Gopinath, Karmakar, Gour, Appuhamillage, Gayan

Authors: Chundhoo, Vickram , Chattopadhyay, Gopinath , Karmakar, Gour , Appuhamillage, Gayan
Date: 2021
Type: Text , Conference paper
Relation: 2021 International Conference on Maintenance and Intelligent Asset Management; ICMIAM 2021, Ballarat; 12-15 December 2021
Full Text: false
Reviewed:
Description: Technological changes have been happening in production facilities including food manufacturing industries in an ever-increasing rate. This includes advancement in data capture devices, signal processing, communication capabilities and automated process control systems such as Internet of Things. It is more challenging where production systems are highly reliant on automation and robotics. Remote performance monitoring and controls are becoming progressively vulnerable due to risks associated with cyber security and corporate espionage. May 2021 cyber-Attack forced JBS meats USA to pay 11m in ransom money to stop any further disruptions in services. This heavily impacted JBS global operations including JBS Australian food manufacturing facilities. Food production facilities in Australia have critical control points supported by smart technologies as part of their food safety management systems. Cyber-Attacks on production facilities could result in financial, operational, health and safety consequences. As survey by the Australian Cyber Security Centre in 2020 revealed that Australian small businesses are impacted by cybercime each year with a loss of 300m. To present the potential cyber security threats and their associated risk level, a case study is presented based on the processing and manufacture of meat products in Australia. From this case study, to protect the meat industries from attacks, we identify cyber security attacks and their possible mitigation strategies. This research shows cyber security attacks can severely affect Overall Equipment Effectiveness which motivate us to embed cyber security as an additional pillar in existing 8 pillars Total Productive Maintenance. If cyber security is added as additional pillar, it will improve the quality of end products and overall productivity of manufacturing industries. © 2021 IEEE.

Security challenges and solutions for 5G HetNet

- Sharma, Aakanksha, Balasubramanian, Venki, Jolfaei, Alireza

Authors: Sharma, Aakanksha , Balasubramanian, Venki , Jolfaei, Alireza
Date: 2020
Type: Text , Conference paper
Relation: 19th IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom) p. 1318-1323
Full Text: false
Reviewed:
Description: The exponential growth of smartphones and other smart communicating devices has led to the proliferation of the Internet of Things (IoT) applications. Literature shows, one person will have more than six intelligent connected devices in future. The existing network infrastructure and bandwidth will be unable to accommodate the growing number of smart connected devices, therefore, achieving the expected Quality of Service (QoS) and Quality of Experience (QoE) remains a challenge. The advent and deployment of 5G network bring a massive number of innovative network services and exceptional user experience by providing superior data rates. Despite numerous benefits that 5G offers, the security and privacy in 5G is a challenge due to the existing large number of heterogeneous networks (HetNet). To harvest the numerous benefits of 5G, it is imperative to provide adequate protection mechanisms to maintain the user and data privacy in growing HetNet. This article comprehensively addresses the existing security issues in 5G HetNet and solutions for the identified problems in the HetNet edge. © 2020 IEEE.

Showing items 1 - 10 of 10