Abstract
In general, the malicious hackers can infiltrate tens of thousands or millions of insecure computers, disable infrastructure, shut down networks, and access personal information. The hackers use some security vulnerabilities in the network to steal and use the required data. And things like the buck they do with advanced technologies are constantly providing them with the data they need, not just once and no matter how protective the firewalls on the Internet are, there is still an increase in cybercrime. This was affected the Quality of Service (QoS) of a wearable device. In this paper, an improved QoS model was proposed to enhance the IoT smart systems. This algorithm was helpful to prevent the smart IoT device from the vulnerable hacking. This system was compared with the existing algorithms, and the results are displayed the below sections. The suggested method performs more than 96 percent of input entry authentication and about 3 percent of password cracking actions. The source code security management was then upgraded to 99.9%. Finally, the number of updating difficulties for various device entries was decreased by 0.02 percent, and the number of privacy breaches was reduced by up to 0.32 percent. Hence, the proposed method was more secured and free from cyber security issues.
1. Introduction
We all need to be aware of cyber security issues. We also need to realize that there is an inherent risk associated with connecting to the Internet and more and more devices with each other. Homes and businesses continue to connect these networks and other smart devices to their networks, but surveillance cameras connected to the Internet can be hacked by SMART TV hackers [1]. Does almost half of the IoT devices fall? Although connected devices include everything from computers and smart phones to smart TVs and kitchen appliances, surveillance camera systems are generally hacked IoT devices. Many of these attacks revolve around the security of low-cost IP cameras [2]. That is, if one model has a defect, it can affect other models as well. Many IoT devices have been found to have bugs that allow attackers to remotely access or monitor the Internet, while others have bad passwords that cannot be changed. The insecure IoT product will theoretically provide a convenient way for hackers to connect to other devices connected to the network, regardless of device vulnerability [3]. When designing and selling new IoT products and solutions to advance beyond competition, people design solutions without first considering the security implications [4].
Basic security measures such as code analysis and implementation of postfinal security components are often taken after the product has been developed. In 2016, one of the largest cyberattacks was carried out by Mirai Botnet, which had 400,000 connected IoT computers, which carried out a series of high attacks [5]. Hundreds of services, including Twitter and Netflix, went offline for hours after service provider Tyne closed offline. Hackers deliberately target IoT security vulnerabilities, but do not attack computers [6]. But before a computer breach, sale loss, complaint, damage to your company image, or worse, keep in mind the most popular firmware flaws to make sure you do not open the front door of your network [7]. The wearable devices or wearable technologies are accessories or clothing that has a specific additional functionality. The main advantage of wearable computers, also called electronic devices, is the complete integration into the user daily life [8]. A person and a smart device are constantly communicating, but the gadget itself does not attract much attention and fits in harmoniously with reality [9].
Typically, high-tech wearable devices are controlled by a specific operating system and fitted with several standard technologies that provide their functionality. Classic technologies used include GPS, Bluetooth, Wi-Fi, GSM, 3G, accelerometer, compass, thermometer, and chronograph. Wearable devices will always do multitasking [10]. For example, a smart watch can not only show the time but also count the number of steps taken, announce incoming messages and calls, and track the user location [11]. It has become customary to see people wearing smart devices that can be worn. Typically, these smart watches or electronic straps are used to monitor fitness [2]. Due to the advanced technology of sensors, wearable devices are starting to encourage more people to be more active [12]. They help people set and achieve goals and provide a sense of motivation and reward when achieving these goals [13]. As technology has advanced so much, new limitations of wearable devices are helping people to their fitness. Here is a range of wearable accessories that can get you on a healthy lifestyle [14].
The Fitbit dominates the wearable device market. Its simple design, usability, and affordability make it an impressive wearable device. Continuous heart monitor means that your activity is constantly being recorded [15]. Keep track of how many calories you are burning, and make sure you are working at the right intensity. The Jaw-Bone is a device for fashion conscious fitness enthusiasts [16]. If you do not want to wear a bold smart watch and want something that looks beautiful, Jaw-Bone offers a wide variety of stylish and elegant accessories.
Jaw-Bone UP2 monitors your activity, sleep, and food record. The smart trainer provides you with customized insights to help you achieve your fitness goal. Microsoft has jumped on the bandwidth of wearable devices and has developed a device that can detect heart rate, exercise, calorie burning, and sleep quality [17]. Microsoft, as a device, connects the user to email, text, and calendar. The band has 11 sensors such as a barometer, ultraviolet monitor, and GPS [18]. The Activate Steel looks pretty cool on this list. If you have always moving, but want a sophisticated wearable device, the Activity is definitely the device to buy. It monitors daily activities such as running, walking, sleeping, and how many calories you burn [19]. It is water resistant up to 50 meters, which means you can use it to monitor your light swimming. This device requires charging as the replaceable battery lasts up to 8 months.
The Apple has acquired smart watches for those who want to get a piece of wearable functionality [20]. Apple Watch has released the Sport for fitness enthusiasts. With the silicone band, the Apple Watch Sport is lightweight and comfortable on the wrist while in operation. The clock includes a heart rate monitor and an accelerometer that monitors activity throughout the day. If you are an avid Apple user and want to sync everything with your iPhone, this is definitely a device.
The Samsung Gear S2 is similar to the Apple Watch. It can perform the functions of a regular smart watch, but this device emphasizes fitness within design. The straps are made of a silicone-like material, which is dust proof, and it is water resistant up to 3 meters. The application monitors your activity throughout the day and changes the application. The quick information is accessed from the gear screen. There is a built-in heart rate monitor to monitor your heart rate before and after the procedure. With the success of the first generation of the Moto 360, Motorola has acquired the Moto 360 Sport. It has IP67 dust and water resistance, making it durable for heavy workouts. The Moto 360 Sport has 7 sensors, including a heart rate monitor, accelerometer, and ambient light sensor. Lightweight silicone pads are available in Black, White, and Flame Orange. Even with high usage, the battery will last for a whole day. You can add your Moto 360 Sport with a wireless charging doc. The main contribution of this method is to increase the efficiency of the given tasks and to create an efficient system. This efficiency is further enhanced when its contribution to the various organizations in general is emphasized.
2. Literature Review
Reference [1] performs a study about IoT and vulnerable activities of a network. In that, the most subtle cybercrime committed on most IoT achievements affects not only those noises but also the trust of the person or company that uses them. The authors [21] began researching security vulnerabilities in some applications designed using IoT devices. According to them, security vulnerabilities in IoT devices are very dangerous and costly. They [22] introduced smart systems for securing IoT devices in a smart building environment monitoring system. Here, all the communication subchannels are interlinked with each other with Wi-Fi communication medium. There, the communication link issues are arrived, and the security threatening issues are created by the edge nodes of the communication channel.
They [23] introduced a Spectral Resource Optimization technique for classified the primary and secondary user management in a 5G communication network environment. In that, the primary users of a network getting higher priority compare then the secondary users. Because the primary users have license to use the spectrum band and the secondary users utilize the spectrum band in the random time manor, so the primary users are getting more priority level. This work [24] provided a smart mechanism of Joint resource allocation. Here, the radio resource of the network can allocate both the primary and secondary users without any connection lost. So the user groups (both primary and secondary users) are unable to suffer the resource utilization problem. Then, the authors include here an admission control technique to the user groups. This controls the secondary user occupancy of the spectrum.
The authors [25] proposed a Reinforcement Learning-based Computation Resource Allocation technique to separate the specific resources to the user group of a network. There the primary user attributes are registered, and the secondary user group attributes are not registered. So the entry of primary users can register in a sequential manner and the entries of secondary users are in random manner. The authors [26] analysed the traffic issues between the user groups of the network. The conjugation occurs when the primary users and secondary users tried to access the network at the same time. At that time, more emphasis will be placed on the primary users and they will be allowed to enter. Meanwhile, the secondary user will then have to wait. As the waiting time increases, then the chances of exiting the network increase.
The authors [27] provided an energy efficient approach between the primary and secondary users. If the bandwidth allocation was increased, then the spectrum utilization automatically increased. In a cut-off range, the number of secondary users utilizing more energy of the network shows the inefficiency of the network, because the primary users utilize very low energy. Another difficulty with IoT devices is determining whether or not they have been hacked. It is difficult to monitor the security status of all IoT devices. As a result, many hacked computers continue to run without the user knowledge. Then, it compromises the data and privacy. The authors [8] introduced Three-Dimensional Block-chain Architecture for secure the IoT devices. This work [9] provides a case study about building a security framework for smart cities. This is one of the reasons why smart homes are not yet widely accepted. This is a scary one of the situations in which a system designed for the happiness of a client is a major obstacle to their privacy at home.
3. Proposed System
The proposed algorithm as in Figure 1 can enhance the QoS of the IoT devices from cyber security attacks. Cyber threats are common on IoT systems. Like many new technologies in the market, buyers are eager to use the new IoT features. At the same time, users should be aware of the very specific security concerns associated with IoT systems and the need to protect such devices from cyberattacks. In order to increase the Quality of Service in general, there must be a variety of security systems in place. The proposed algorithm as shown emphasizes this and contains 4 important points. All the commands given in the authentication management section indicate that the correct amount of permits must be obtained. Also, if the correct password is incorrect, there will be no data protection so it must be verified as well. We also need to protect a variety of privacy data.
The general wearable human body inputs are captured by the smart sensors. Then, these sensor inputs are move on to the IoT devices. This is a very important phase because this is the place the entire imported sensor details started to transmit over the other locations. Then all the imported details are stored in a secured server. This was accessed by the proposed algorithm structure which is shown in Figure 2. These proposed models always verify the protection of the secured connection. If the given input details are correct, then this allows the user to access the details. All the access gateway processes are performed by the access point (AP), and finally, these details are stored in the cloud server.
3.1. Password Changing Module
Always change the default passwords. Use secure and specialized passwords for user accounts, Wi-Fi networks, and wired computers. Do not use predictable words or keys such as “password” or “123456.”
3.2. VPN Data Network Module
Use VPN for IoT devices at home. Use a reputable VPN to encrypt data sent over your home or public Wi-Fi network.
3.3. Software Updating Module
Make regular software updates. Install the famous cyber security software on your computers, tablets, and smart phones.
3.4. App Information Module
When it comes to smart phones, be careful. Read the privacy policies of the apps you use often, and see if they plan to use your data and other information. Devices are smart because they collect more personal data.
3.5. Social Media Module
Social sharing features may reveal personal information such as your location and alert others when you are away from home. It can be used to track the activities of cyber criminals. This could lead to a cyber-stalking problem or other real-world threats.
4. Results and Discussion
The proposed QoS-based IoT Management Algorithm 1 (IoT-QA) for smart IoT systems was compared with the existing Three-Dimensional Block-chain (TDB) model and the Internet of Things based on the Optimization Algorithm (IoT-OA). The performance comparison was given in the following. The Network Simulator tool is used in this enhanced mode. In general, it is necessary to calculate the various measurements of the cochlea taking into account the improvements of all the data. In that order, these applications are implemented by this tool.
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4.1. Authentication Management
Where the firmware has weak authentication functionality, hackers can quickly gain access to the devices. These algorithms can range from single-factor and password-based authentication to cryptographic algorithms that could be vulnerable to Proud Force attacks. The authentication management is nothing but the ratio between the number of accepted entries and the number of total entries. If the authentication ratio was increased, then the system is more reliable. The proposed system achieves 94% authentication. Figure 3 demonstrates the comparison of entry authentication of existing TDB, IoT-OA, and proposed IOT-QA.
4.2. Password Hash Management
Most computer firmware includes hard code passwords that users cannot change or passwords that users often do not change by default. All of these results make the settings relatively simple for the hacker. One bonnet used the default passwords on IoT devices to launch D-DoS attacks, which affected more than 2.5 million IoT devices worldwide. The password cannot be changed while it is fixed. If the password modification was less, then the system gets more protection. The proposed system achieves 6% password issues. Figure 4 demonstrates the comparison of password management issues of existing TDB, IoT-OA, and proposed IOT-QA.
4.3. Source Code Management
Open-source code enables rapid advancement of advanced IoT products using open-source tools and libraries lying down. However, IoT devices are often third-party, unpublished, or documented. Because of the use of open source modules from untapped appearance, the firmware is often left unprotected, making it an attractive target for hackers. If the source code protection is increased, then the system gets more protection. The proposed system achieves 91% source code management. Figure 5 demonstrates the comparison of password management issues of existing TDB, IoT-OA, and proposed IOT-QA.
4.4. Privacy Breach Management
If a hacker detects an insecure IoT gadget leaking an IP address, it can be used to point to certain locations. Virtual private networks (VPNs) are recommended for securing IoT connections (VPNs). If the VPN users’ entry restriction was increased, then the system gets high security. The proposed system achieves 9% source privacy breach management. Figure 6 demonstrates the comparison of privacy breach issues of existing TDB, IoT-OA, and proposed IOT-QA.
4.5. Device Update Management
As the market for IoT products grows, companies are producing them faster. Manufacturers, on the other hand, are less cautious about IoT device-related threats and security concerns because they focus on demand and competition. Many computers on the market do not receive regular security updates. If the device updated regularly, then the security vulnerabilities are reduced. The proposed system achieves 8% device failure management. Figure 7 demonstrates the comparison of device update issues of existing TDB, IoT-OA, and proposed IOT-QA.
5. Conclusion
Hackers have recently seized control of automobiles, trains, and dams. IoT machines are extremely sensitive to hacking and covert recruiting in order to attack the digital world. This poses a huge danger to Internet security. IoT and embedded devices create a new challenge for ethical hackers attempting to identify security flaws. Globally, the media and governments are becoming increasingly worried about their own security weaknesses. In the authentication management, the proposed algorithm allows almost 92% of authorized users. So the unknown members are not allowed in the network. Then, the password management issues raised just 8% in the proposed algorithm. This shows the protection of the network. The source code management was 90% achieved. So, the data modification issues are reduced. The privacy beach issues are raised just 10%. This shows all the VPN users safely use their network without any interference. Finally, the device software updating issues are arrived just 7%. This shows all the installed software on the current version. Hence, the proposed model for smart IoT Systems was provided the Quality of Service while being compared with the existing Three-Dimensional Block-chain (TDB) model and the Internet of Things based on the Optimization Algorithm (IoT-OA). The future enhancement of this proposed model is to update the energy efficiency and power optimization parameters to transport the different instructions from the source to destination.
Data Availability
The data used to support the findings of this study are included within the article. Further data or information is available from the corresponding author upon request.
Conflicts of Interest
The authors declare that there are no conflicts of interest regarding the publication of this paper.
Acknowledgments
The authors appreciate the supports from Ambo University, Ethiopia, for the research and preparation of the manuscript. The authors thank Dr. N.G.P. Arts and Science College, Vellore Institute of Technology, St. Ann’s College of Engineering & Technology, Ramco Institute of Technology, BV Raju Institute of Technology, and Siddaganga Institute of Technology for providing assistance in this work.