اینترنت اشیا

Open Access Article

1 - A Method to Get WSN Nodes Data by Web Clients through IoT Gateway Based on CoAP Protocol
M. R. Nikseresht H. Haj Seyyed Javadi Mahdi Mollamotalebi

20.1001.1.16823745.1397.16.4.9.1

The advancement of technology in the area of wireless sensor networks and the ability to use the Internet Protocol in small objects with limited resources (such as sensors) has changed the Internet landscape. How to communicate and how to exchange information is one of More

The advancement of technology in the area of wireless sensor networks and the ability to use the Internet Protocol in small objects with limited resources (such as sensors) has changed the Internet landscape. How to communicate and how to exchange information is one of the challenges of the Internet world of things. 6LoWPAN and CoAP standards for using web protocols in low-loss and low-power sensor networks (LLNs) are presented. The 6LoWPAN / CoAP protocol stack allows access to the sensor network through web protocols. This will facilitate the development of applications on the sensor network and access to them by the Internet. Each layer stack of the 6LoWPAN / CoAP protocol imposes overhead on interchange messages, and data overload in multichannel networks exacerbates energy consumption. In this paper, a method for reducing the overhead imposed on small and medium packets in multi-step networks based on 6LoWPAN / CoAP is presented using the scheduling and aggregation of CoAP packets on sensor nodes. In order to achieve the research objectives, measures such as the classification of CoAP requests / responses in terms of network priority (maximum allowed delay detection), scheduling and aggregation of incoming messages on sensor nodes (based on the maximum allowed delay of each), and opening messages aggregated in the destination , It has been done. The evaluation results of the proposed method indicate a reduction of energy consumption and network traffic for applications such as monitoring, in multi-step networks based on the 6LoWPAN/ CoAP protocol stack. Manuscript profile

Open Access Article

2 - Scheduling of IoT Application Tasks in Fog Computing Environment Using Deep Reinforcement Learning
Pegah Gazori Dadmehr Rahbari Mohsen Nickray

20.1001.1.16823745.1399.18.2.9.1

With the advent and development of IoT applications in recent years, the number of smart devices and consequently the volume of data collected by them are rapidly increasing. On the other hand, most of the IoT applications require real-time data analysis and low latency More

With the advent and development of IoT applications in recent years, the number of smart devices and consequently the volume of data collected by them are rapidly increasing. On the other hand, most of the IoT applications require real-time data analysis and low latency in service delivery. Under these circumstances, sending the huge volume of various data to the cloud data centers for processing and analytical purposes is impractical and the fog computing paradigm seems a better choice. Because of limited computational resources in fog nodes, efficient utilization of them is of great importance. In this paper, the scheduling of IoT application tasks in the fog computing paradigm has been considered. The main goal of this study is to reduce the latency of service delivery, in which we have used the deep reinforcement learning approach to meet it. The proposed method of this paper is a combination of the Q-Learning algorithm, deep learning, experience replay, and target network techniques. According to experiment results, The DQLTS algorithm has improved the ASD metric by 76% in comparison to QLTS and 6.5% compared to the RS algorithm. Moreover, it has been reached to faster convergence time than QLTS. Manuscript profile

Open Access Article

3 - Optimal and Sub-optimal Transmitter-Receiver Design in Dense Wireless Sensor Networks and the Internet of Things
Farzad H. Panahi Fereidoun H. Panahi Zahra Askarizadeh Ardestani

20.1001.1.16823745.1400.19.3.4.5

With the rapid development of new technologies in the field of internet of things (IoT) and intelligent networks, researchers are more interested than ever in the concept of wireless sensor networks (WSNs). The emergence of these densely structured networks in recent ye More

With the rapid development of new technologies in the field of internet of things (IoT) and intelligent networks, researchers are more interested than ever in the concept of wireless sensor networks (WSNs). The emergence of these densely structured networks in recent years has raised the importance of the use of telecommunications technologies, such as ultra-wideband (UWB) technology with high reliability, industrial applications, and appropriate communication security. However, there are still numerous concerns about the extent of inter-network interference, particularly owing to undesired spectral discrete lines in this technology. As a result, it is necessary to provide an optimal solution to eliminate interference and control the power spectrum, and then design the optimal transmitter-receiver structures while considering high sensitivities to the synchronization problem in WSNs based on UWB technology. These goals are pursued in the present study by employing the optimal spectral strategy in the signal model, the structure of the transmitter sensor, and then constructing the optimal or sub-optimal receiver sensor structures, the results of which indicate improved communication performance in WSNs. Manuscript profile

Open Access Article

4 - An Efficient Approach to Reduce Energy Consumption in Internet of Things Routing
M. Asgari M. Fathy Mohammad Shahverdy M. Soheili Nayer

20.1001.1.16823745.1398.17.3.14.1

The Internet of Things (IOT) is a new concept in the area of monitoring information transmission and remote control of things, existents and equipment that has been able to adapt itself with different industries and substructures easily. The information transmission wit More

The Internet of Things (IOT) is a new concept in the area of monitoring information transmission and remote control of things, existents and equipment that has been able to adapt itself with different industries and substructures easily. The information transmission with regard to the non-homogenous environment of internet of things has been a challengeable topic and use of routing methods by considering the limitations of processing, calculating, saving and communicating has been known as a necessary issue. Various algorithms with special applications have been already introduced in the domain of internet of things and wireless sensor networks that each one somehow has been successful in achieving the routing goals. Some proposed protocols in this field have used a tree structure for gathering the network information. These methods in selecting the parent or children of graph are affected by important challenges depending on the type of application. In this paper, at first, a general classification of advantages and defects of recent methods has been done in the domain of routing the internet of things and then a routing method service quality awareness in routing based on fuzzy system has been suggested. The results of simulations and assessment express that the suggested method in the tests of energy productivity, delay ratio and data delivery ratio have better performance than the recent methods. Manuscript profile

Open Access Article

5 - Providing lightweight mutual group authentication of Internet of Things
reza sarabi miyanaji sam jabbehdari nasser modiri

20.1001.1.16823745.1400.19.3.5.6

The Internet of things is becoming the largest computing platform and we are seeing an increase in the number of devices in this environment. In addition, most Things in this infrastructure have the computational power and memory constraints. They cannot perform complex More

The Internet of things is becoming the largest computing platform and we are seeing an increase in the number of devices in this environment. In addition, most Things in this infrastructure have the computational power and memory constraints. They cannot perform complex computational operations. These limitations have been ignored in most traditional authentication methods. Meanwhile, in the new methods of authentication of this environment, not much attention has been paid to the issue of scalability. Therefore, the need for a lightweight, scalable authentication is felt. In this paper, a lightweight authentication protocol is presented in which things are placed in different groups. In each group, a group manager node is considered and as an agent, it performs authentication on behalf of other members. Therefore, Authentication is done in groups, which makes the proposed protocol highly scalable. The proposed method reduces the computational cost of nodes and servers and provides privacy through node anonymity. In addition, it has forward-looking privacy without the use of asynchronous encryption and key agreement. The AVISPA tool has been used to confirm the security of the proposed method. In our method, the computation time of the node and server in authentication has been decreased by 7.8% and 3.5%, respectively, compared with reviewing protocols. Manuscript profile

Open Access Article

6 - Detecting Human Activities Based on Motion Sensors in IOT Using Deep Learning
Abbas Mirzaei fatemeh faraji

20.1001.1.16823745.1400.19.4.10.3

Control of areas and locations and motion sensors in the Internet of Things requires continuous control to detect human activities in different situations, which is an important challenge, including manpower and human error. Permanent human control of IoT motion sensors More

Control of areas and locations and motion sensors in the Internet of Things requires continuous control to detect human activities in different situations, which is an important challenge, including manpower and human error. Permanent human control of IoT motion sensors also seems impossible. The IoT is more than just a simple connection between devices and systems. IoT information sensors and systems help companies get a better view of system performance. This study presents a method based on deep learning and a 30-layer DNN neural network for detecting human activity on the Fordham University Activity Diagnostic Data Set. The data set contains more than 1 million lines in six classes to detect IoT activity. The proposed model had almost 90% and an error rate of 0.22 in the evaluation criteria, which indicates the good performance of deep learning in activity recognition. Manuscript profile

Open Access Article

7 - Reliable and Energy Efficient Deployment Optimization of Internet of Things Applications in Cloud and Fog Infrastructure by Using Cuckoo Search Algorithm
Yaser Ramzanpoor میرسعید حسینی شیروانی

20.1001.1.16823745.1400.19.4.11.4

Deployment applications of internet of things (IoT) in fog infrastructure as cloud complementary leads effectively computing resource saving in cloud infrastructure. Recent research efforts are investigating on how to better exploit fog capabilities for execution and su More

Deployment applications of internet of things (IoT) in fog infrastructure as cloud complementary leads effectively computing resource saving in cloud infrastructure. Recent research efforts are investigating on how to better exploit fog capabilities for execution and supporting IoT applications. Also, the distribution of an application’s components on the possible minimum number of fog nodes for the sake of reduction in power consumption leads degradation of the service reliability level. In this paper, a hybrid meta-heuristic algorithm based on cuckoo search algorithm is presented for static deployment the components of IoT applications on fog infrastructure in the aim of trade-off between efficient power usage, reduction in the effect of one point of failure and boosting the application reliability against failure. The results of simulations show that the proposed approach in this paper reduces the power consumption of fog network and meets the quality of service requirement of IoT application with the high reliability level. Manuscript profile

Open Access Article

8 - A Patient Identification and Authentication Protocol to Increase Security
Afsaneh Sharafi Sepideh Adabi Ali Movaghar Salah Al-Majed

20.1001.1.16823745.1401.20.1.7.1

Today, with the ever-expanding IoT, information technology has led the physical world to interact more with stimuli, sensors, and devices. The result of this interaction is communication "anytime, anywhere" in the real world. A research gap that can be felt in addition More

Today, with the ever-expanding IoT, information technology has led the physical world to interact more with stimuli, sensors, and devices. The result of this interaction is communication "anytime, anywhere" in the real world. A research gap that can be felt in addition to providing a multi-layered and highly secure protocol (a protocol that simultaneously performs authentication) and at the same time has a low computational burden. Therefore, in the field of health and treatment and for the purpose of remote monitoring of patients with physical and mental disabilities (such as patients with cerebral palsy and spinal cord amputation) there is an urgent need for a very safe protocol. The protocol we propose in this study is a two-layer protocol called "Identification-Authentication" which is based on EEG and fingerprint. Also, our authentication step is the modified Diffie-Hellman algorithm. This algorithm needs to be modified due to a security problem (the presence of a third person) that the proposed method is able to authenticate the patient with very high accuracy and high speed by receiving the patient's fingerprint and EEG signal. The proposed protocol was evaluated using data from 40 patients with spinal cord injury. The implementation results show more security of this protocol, Validity of the proposed protocol is checked and the processing time of authentication stage is decrease to 0.0215 seconds. Manuscript profile

Open Access Article

9 - Mutual Continuous Lightweight Authentication Based on Node Prioritization Using Traffic Rates for Internet of Things
reza sarabi miyanaji sam jabbehdari nasser modiri

20.1001.1.16823745.1401.20.2.5.1

Today, billions of devices are connected via the Internet of Things, often through insecure communications. Therefore, security and privacy issues of these devices are a major concern. Since devices in IoT are typically resource-constrained devices, the security solutio More

Today, billions of devices are connected via the Internet of Things, often through insecure communications. Therefore, security and privacy issues of these devices are a major concern. Since devices in IoT are typically resource-constrained devices, the security solutions of this environment in terms of processing and memory must be secure and lightweight. However, many existing security solutions are not particularly suitable for IoT due to high computation. So there is a need for a lightweight authentication protocol for IoT devices. In this paper, a mutual lightweight authentication protocol between nodes with limited resources and IoT servers is introduced that uses node prioritization based on traffic rates. This scheme is light due to the use of lightweight XOR and Hash operations. The proposed is resistant to cyber-attacks such as eavesdropping attack, and replay attack. The proposed is also secure using the AVISPA tool in the Dolev-Yao threat model. The security risks of this scheme are low compared to other lightweight methods. In addition, the proposal is compared with existing authentication schemes reduces the computational cost, protects privacy through anonymity of nodes, and provides forward secrecy. In our method, the execute time of authentication is reduced by 15% compared to the other methods. Manuscript profile

Open Access Article

10 - Improving IoT Botnet Anomaly Detection Based on Dynamic Feature Selection and Hybrid Processing
Boshra Pishgoo Ahmad akbari azirani

20.1001.1.16823745.1401.20.2.8.4

The complexity of real-world applications, especially in the field of the Internet of Things, has brought with it a variety of security risks. IoT Botnets are known as a type of complex security attacks that can be detected using machine learning tools. Detection of the More

The complexity of real-world applications, especially in the field of the Internet of Things, has brought with it a variety of security risks. IoT Botnets are known as a type of complex security attacks that can be detected using machine learning tools. Detection of these attacks, on the one hand, requires the discovery of their behavior patterns using batch processing with high accuracy, and on the other hand, must be operated in real time and adaptive like stream processing. This highlights the importance of using batch/stream hybrid processing techniques for botnet detection. Among the important challenges of these processes, we can mention the selection of appropriate features to build basic models and also the intelligent selection of basic models to combine and present the final result. In this paper, we present a solution based on a combination of stream and batch learning methods with the aim of botnet anomaly detection. This approach uses a dynamic feature selection method that is based on a genetic algorithm and is fully compatible with the nature of hybrid processing. The experimental results in a data set consisting of two known types of botnets indicate that on the one hand, the proposed approach increases the speed of hybrid processing and reduces the detection time of the botnets by reducing the number of features and removing inappropriate features, and on the other hand, increases accuracy by selecting appropriate models for combination. Manuscript profile

Open Access Article

11 - SQ-PUF: A Resistant PUF-Based Authentication Protocol against Machine-Learning Attack
Abolfazl Sajadi Bijan Alizadeh

Physically unclonable functions (PUFs) provide hardware to generate a unique challenge-response pattern for authentication and encryption purposes. An essential feature of these circuits is their unpredictability, meaning that an adversary cannot sufficiently predict fu More

Physically unclonable functions (PUFs) provide hardware to generate a unique challenge-response pattern for authentication and encryption purposes. An essential feature of these circuits is their unpredictability, meaning that an adversary cannot sufficiently predict future responses from previous observations. However, machine learning algorithms have been demonstrated to be a severe threat to PUFs since they are capable of accurately modeling their behavior. In this work, we analyze PUF security threats and propose a PUF-based authentication mechanism called SQ-PUF, which can provide good resistance to machine learning attacks. In order to make it harder to simulate or predict, we obfuscated the correlation between challenge-response pairs. Experimental results show that, unlike existing PUFs, even with a large data set, the SQ-PUF model cannot be successfully attacked with a maximum prediction accuracy of 53%, indicating that this model is unpredictable. In addition, the uniformity in this model remains almost the same as the ideal value in A-PUF. Manuscript profile

Open Access Article

12 - Proposing a Detection and Mitigation Approach for DDoS Attacks on SDN-Based IoT Networks
fatemeh MotieShirazi Seyedakbar Mostafavi

20.1001.1.16823745.1402.21.2.12.5

Internet of Things (IoT) is a network of objects on which objects can communicate with other objects. The Internet of Things is currently constantly under numerous attacks due to technical, legal and human problems. One of the most important of these attacks is the Deni More

Internet of Things (IoT) is a network of objects on which objects can communicate with other objects. The Internet of Things is currently constantly under numerous attacks due to technical, legal and human problems. One of the most important of these attacks is the Denial of Service (DoS) attack, in which normal network services are out of service and it is impossible for objects and users to access the server and other resources. Existing security solutions have not been able to effectively prevent interruption attacks in Internet of Things services. Software-oriented network (SDN) is a new architecture in the network based on the separation of the control and data plane of the network. Programmability and network management capability by SDN can be used in IoT services because some IoT devices send data periodically and in certain time intervals. SDN can help reduce or prevent the data flood caused by IoT if properly deployed in the data center. In this article, a method to detect DDoS attacks in Internet of Things based on SDN is presented and then an algorithm to reduce DDoS attacks is presented. The proposed method is based on the entropy criterion, which is one of the most important concepts in information theory and is calculated based on the characteristics of the flow. In this method, by using two new components on the controller to receive incoming packets and considering the time window and calculating entropy and flow rate, a possible attack is detected in the network, and then based on the statistics of the flow received from the switches, the certainty of the attack is determined. Compared to the existing methods, the proposed method has improved 12% in terms of attack detection time and 26% in terms of false positives/negatives. Manuscript profile

Open Access Article

13 - Machine Learning-Based Security Resource Allocation for Defending against Attacks in the Internet of Things
Nasim Navaei Vesal Hakami

Nowadays, the Internet of Things (IoT) has become the focus of security attacks due to the limitation of processing resources, heterogeneity, energy limitation in objects, and the lack of a single standard for implementing security mechanisms. In this article, a solutio More

Nowadays, the Internet of Things (IoT) has become the focus of security attacks due to the limitation of processing resources, heterogeneity, energy limitation in objects, and the lack of a single standard for implementing security mechanisms. In this article, a solution will be presented for the problem of security resources allocating to deal with attacks in the Internet of Things. Security Resource Allocation (SRA) problem in the IoT networks refers to the placement of the security resources in the IoT infrastructure. To solve this problem, it is mandatory to consider the dynamic nature of the communication environments and the uncertainty of the attackers' actions. In the traditional approaches for solving the SRA, the attacker works over based on his assumptions about the system conditions. Meanwhile, the defender collects the system's information with prior knowledge of the attacker's behavior and the targeted nodes. Unlike the mentioned traditional approaches, this research has adopted a realistic approach for the Dynamic Security Resources Allocation in the IoT to battle attackers with unknown behavior. In the stated problem, since there is a need to decide on deploying several security resources during the learning periods, the state space of the strategies is expressed in the combinatorial form. Also, the SRAIoT problem is defined as a combinatorial-adversarial multi-armed bandit problem. Since switching in the security resources has a high cost, in real scenarios, this cost is included in the utility function of the problem. Thus, the proposed framework considers the switching cost and the earned reward. The simulation results show a faster convergence of the weak regret criterion of the proposed algorithms than the basic combinatorial algorithm. In addition, in order to simulate the IoT network in a realistic context, the attack scenario has been simulated using the Cooja simulator. Manuscript profile

Open Access Article

14 - Friendship Selection Based on Social Features in Social Internet of Things
Mohammad Mahdian S.Mojtaba Matinkhah

The Social Internet of Things (SIoT) network is the result of the union of the Social Network and the Internet of Things network; wherein, each object tries to use the services provided by its friends. In this network, to find the right friend in order to use the right More

The Social Internet of Things (SIoT) network is the result of the union of the Social Network and the Internet of Things network; wherein, each object tries to use the services provided by its friends. In this network, to find the right friend in order to use the right service is demanding. Great number of objects' friends, in classical algorithms, causes increasing the computational time and load of network navigation to find the right service with the help of friendly objects. In this article, in order to reduce the computational load and network navigation, it is proposed, firstly, to select the appropriate object friend from a heuristic approach; secondly, to use an adapted binary cuckoo optimization algorithm (AB-COA) which tries to select the appropriate friendly object to receive the service according to the maximum response capacity of each friendly object, and finally, adopting the Adamic-Adar local index (AA) with the interest degree centrality criterion so that it represents the characteristics of the common neighbors of the objects are involved in the friend selection. Finally, by executing the proposed algorithm on the Web-Stanford dataset, an average of 4.8 steps was obtained for reaching a service in the network, indicating the superiority of this algorithm over other algorithms. Manuscript profile

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