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Internet of Things

Internet of Things (IOT) has become popular in all industries .Uses of IOT and its benefits have been eye-appealing in industry and commerce. Along with many other sectors of the economy, the revolutionary effect of digitalization is having an intense effect on logistic industry as well. IOT application will introduce different promising concept and design for innovation in supply chain and logistics. The IOT in Logistics with greater accuracy of execution can be achieved with minimal efforts and new possible roles will be opened for logistics operators to produces the goods with less cost. The IOT will have greater impact on various areas such as operational efficiency, safety and security, customer experience, and new business models in logistics. This paper mainly focused on the topic application and benefits of IOT on logistics industry. Moreover, this paper will describe the application and efficiency gains in the IOT applications. Finally, we will conclude this paper with next steps and future works planned for IOT to become a reality.
KEYWORDS: IOT, Fleet Management, Warehouse Management, Asset Tracking
1. INTRODUCTION:
Internet of Things (IOT) has become popular in any industry. Uses of IOT and its benefits have prominent in industry and commerce. Many possibilities and innovations can be realized with the help of deep intelligence provided for the logistics industry and its customers. In the field of freight transportation and logistics, the real-time data access and visibility is a crucial component to achieving great productivity and improve efficiency of a company. Many companies have already recognized the importance of different technologies and back office anchoring solutions, but the processes and operations are still challenging due to the uncertain nature of the different costs and rates in the industry. The IOT give sufficient visibility to track the company’s supply chain, results to improve the operational efficiency which produces the products with less costs. IOT application will introduce different promising concept and design for innovation in supply chain and logistics in the industry. The logistics processes with greater accuracy of execution can be achieved with nominal efforts and new possible roles will be opened for logistics operators. These advancements are quickly making its way in the logistics, and it completely improves the different business operations.

2. MEANING IOT AND LOGISTICS:
The Internet of Things refers to a physical tool or gadget that offers smart characteristics through connectivity, resulting in greater monitoring system, optimization, control, and automation.
Logistics is generally refers to the detailed organization and implementation of a complex operation. In a general business concept, logistics is the management of the flow of things between the point of origin and the point of consumption in order to meet requirements of customers or corporations. The logistics of physical items usually includes the integration of information flow, materials handling, Production, packaging, inventory, warehousing and often security
3. APPLICATION OF IOT IN LOGISTICS:
The IOT having revolutionary impact on logistic industry. The operations of logistic industry, their delivery and fulfillment are changing intensely, with combination of analytics, mobile computing, and cloud services, all of which are powered by the Internet of Things.
APPLICATION IF IOT IN LOGISTICS

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3.1. REAL-TIME TRACKING
The Internet of Things has a huge potential to keep almost everything connected (e.g., assets, trucks, etc.) using embedded sensors, it provides unparalleled visibility into personnel, operations, equipment, and transactions. With the right IOT solution in place, companies can connect all assets across a centralized cloud network, and capture critical data to make sure everything is in order. As it facilitates assets tracking and remote fleet management, companies can dramatically ensure compliance, improve performance and ability, and reduce risk.
3.2. PREDICTIVE ASSET MAINTENANCE
In Predictive Asset Maintenance, the mobile technologies provide businesses line of sight into equipment, inventory and business processes. This asset intelligence allows organizations to increase their competence and capacity by providing them real-time data across their entire supply chain.
Though these types of solutions the transportation and logistics businesses make improvements over the years, leveraging them with enabling technologies like the IOT can give even more asset intelligence, leading to more informed decisions.
3.3. REAL TIME FLEET MANAGEMENT
Government and Industries that operate various number of vehicles are more often using fleet management solutions making the process more effective. These Solutions are GPS enabled along with added tracking technologies to collect real time data of their locations and operations of their vehicles. Fleet management solutions are able to connect and reaching millions of commercial vehicles resulting in tenfold increase in ten years.
Companies are positioning these solutions in three ways:
3.3.1. Physical asset movement and delivery
This includes fleets of largely semi-trailer trucks that transport goods to fulfill business’ and consumers’ orders. These fleets can handle from origin point to long distance or last-mile delivery.
3.3.2. Consumer transportation
This includes businesses and governments vehicles that are used to transport people from one destination to another.
3.3.3. Field-service vehicles
Vehicles that are operated mostly by businesses to transport employees for their job functions. Deploying the unending potential that IOT can offer, one must keep in mind the above mentioned points.
3.4. WAREHOUSE MANAGEMENT
Distribution centers, warehouses and yards form are the most critical units of the supply chain ecosystem. If a company manages to increase the performance of these units, it is converted into an increase in efficiency of the company’s functioning. As IOT becomes an essential part of the logistics industry, warehouses will track the equipment’s, inventory and vehicles via the cloud. This is enabled by thousands of machines connected to one another through RFID-tags. At a local level, the parcels and pallets would communicate with one another while at a global level, a company-based server will track their movements and progress of their journey regularly.
3.5. ROUTE OPTIMIZATION
An efficient route optimization scheme for the carriers can result in the elimination of 175 grams of carbon emission produced by every extra mile traveled by it. The impact of IOT enabled route optimization system which can save thousands of miles to be traveled by the carrier. IOT enabled route optimization further enhances the process by collaborating with all the units of the fleet which are dispersed over a large geography. These connected vehicles can communicate the crucial information in real time about the statistics which changes dynamically from region to region. Traffic congestion, weather conditions, and open routes can impact the time and distance traveled by the carriers in a great way and real-time information for the same can help the drivers to go for the most viable route for completion of the trip.
4. BENEFITS OF IOT IN LOGISTICS
4.1. The Existing Processes Can Be Improved
IOT in Logistics can transform how logistics work and also the operations of businesses. Better technical assistance in analytics will improve warehousing, thus reducing the existance of low stock and out of stock situations. IOT can be useful in better planning of production and optimizing the warehouse space. It will lead to improved assets utilization and better process efficiency.
4.2. Merging of Physical and Digital Aspects of the Supply Chain
The rise of IOT in Logistics can drives the merging of digital and physical processes of the supply chain. It will lead to better information collection at various stages of logistics management. Also, faster travelling of information will reduce the chances of asset loss as the information will reach the authorities in time.
4.3. High Visibility
The Large number of goods transfers between manufactures, suppliers, the centers of distribution, retailer and finally the customer. IOT in Logistics and Supply Chain will bring more visibility in the process through GPS and other such technologies that will provide adequate and accurate information about goods identity, locations and a several other essential tracking information. Due to IOT in Logistics and Supply Chain, traffic conditions and other issues related to the route can be monitored also. It will lead to better planning and more efficient ; productive processes.
5. SUCCESS FACTORS FOR IOT IN LOGISTICS:
? To successfully implement IOT in logistics will require strong collaboration, along with high levels of participation between different players and competitors within the supply chain. The shared end goal will be to create a thriving IOT ecosystem.
? Seamless interoperability for exchanging sensor information in heterogeneous environments.
? Establishment of trust and ownership of data and overcoming privacy issues in the IOT-powered supply chain.
? Clear focus on reference architecture for the IOT.
? Change in business mindset to embrace the full potential of the Internet of Things.
6. FUTURE OF IOT IN LOGISTICS:
The Internet of Things (IOT) has brought with it a whole load of changes in logistics industry. The capacity for more and more physical objects to connect to the internet and share data without human help has transformed the way the world works. In 2014, Gartner predicted a thirty-fold increase in the IOT-connected devices by about 2020 and consequently one will see radical impact on the functioning of our supply chain. The IOT regulates the logistics industry – both from a business and a consumer perspective. A report by IDC and SAP predicts that IOT will lead to a 15% productivity increase in delivery and supply chain performance, and many logistics experts are using these IOT resources to improve systems and supply networks, reduce costs, and look for opportunities to develop more revenue too.

Source: Markets and Markets, 2015 (BI Intelligence)
The above chart shows the estimated spending on connected logistic solution. The estimated spending on connected logistic is 5$ in the year 2015and it is expected to grow 15$ in the year 2019 and 20$ in the year 2020 at global level.
7. CONCLUSION:
The IOT promises protracted payoffs for logistics operators and their business customers and end consumers. These benefits extend across the entire logistics value chain, including warehousing operations, freight transportation, and last-mile delivery. The IOT have great impact in the areas such as operational efficiency, safety and security, customer experience, and new business models. To successfully implement IOT in logistics will require strong collaboration, along with high levels of participation between different players and competitors within the supply chain, and a common willingness to invest. The shared end goal will be to create a thriving IOT ecosystem. But the advancements in the logistics will always depend on the ability of innovation of the logistics’ minds and operators.

Internet of Things

Internet of Things (IoT) is the advance transformative in the world of internet. IoT can possibly influence our lifestyles to be more convenient and also make our lives simpler. IoT device means physical devices connect to Internet base on traditional telecommunications with address, moreover could search and communicate each other by Raylin et al. (2014). Besides, IoT have a wide range of applications that consist of smart city, smart home, autonomous vehicles, smart traffic and parking control, smart metering and smart grids, industrial control systems and also medical and healthcare by (Kishore, 2017). The one particularly dangerous part of cybercrime is the threat forced by IoT botnets. With the developing trend of Internet empowered devices and the rise of the IoT, cybercrimes, for example, those carried out by IoT botnets turns into a major issue. Based on (Spamhous Malware Lab, 2018) report, IoT malware ranked second place found in 2017.

Figure 1.1 The ranking of malware in year 2017 (Spamhous Malware Lab, 2018)

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According to the (IT security company Kaspersky Rene Millman, 2017), the amount of malware targeting IoT devices more than doubled in 2016. The types of devices from which the attacks originated, over 63 percent of them were identified as DVR services or IP cameras, while about 20 percent were network devices and routers from major manufacturers. One percent were Wi-Fi repeaters and other network hardware, TV tuners, VOIP devices, Tor exit nodes, printers and ‘smart home’ devices. Some one in five, meanwhile, could not be identified. According to Antonakakis et al. (2017), the IP cameras, routers, DVRs and some other smart internet connected appliances are at risk of attack. The figure 1.2 describe the IoT botnets attack by country in year 2017. Based on Kaspersky Lab report, South Korea (46.43%) has the highest percentage of IoT botnet attacks compared to Canada, Turkey, and Lithuania (1.19% each) that has the lowest percentage of attacks.

Figure 1.2 IoT botnets attack by country in year 2017 (Rene, 2017)

In fact, the large number of uncertain devices with high computation power make them an easy and attractive target for attackers seeking to compromise these devices and use them to create large-scale IoT botnets by Elisa et al. (2017). According to (Robert, (2017), users are often unaware of their system being infected, as infected devices will stay idle until they receive commands from their commander to start an attack. A botnet is a group of hijacked Internet-connected devices, each injected with threats used to allow an attacker to control it from a remote location without the knowledge of the device’s rightful owner. From the perspective of hackers, these IoT devices are computing resources that can be used for any type of malicious purposes. Based on Felix report describe that the data privacy leaks because of the security issues in IoT devices. According to (Michael, 2017), keeping IoT devices secure costs time and money, but is crucial in many use cases.

Figure 1.3 Users affected from lack of security in IoT devices (Felix, 2015)

In this project it will focusing on the precipitous rise of Mirai and Hajime IoT botnets in devices that has been growth. According to (Bernard, 2017), The Mirai and Hajime IoT botnets are not new. Since as early as 2000, hackers have been using botnets by gaining access to unsecured devices (usually computers then) in order to create these attacks. The main purpose of IoT botnets attack are for spamming, identity theft, information stealing, reputation theft, botnet hosting services, click fraud, manipulating online polls and also attacking bank computers by (Sorensen, 2017). Some IoT botnets are also operated with worse intent, for example performing Distributed Denial-of-Service Attacks (DDoS) attacks.

1.1 Problem Statement (PS)

The number of malicious programs attacking the IoT has more than doubled in 2017. Worldwide, smart devices now number 6 billion, and many of them are vulnerable, making them a juicy prospect for intruders by (Kaspersky lab, 2017). The main problem of IoT devices are security issues. IoT devices do not have advanced security features and also do not change the default device settings, update passwords, or search for updated firmware until after an IoT botnets attack has occurred. Additionally, IoT devices are often designed with poor security or even none at all. Internet is already very complex to secure, with additional 9+ billion insecure IoT devices, the task has become more difficult by (Kishore, 2017). As users are often designed to be plugged in and forgotten about, the users often do not apply security updates and it is easy for an attack on such devices to go unnoticed. Besides, the machine learning uses to classify normal network flows that generated by IoT botnets. The machine learning also to enhance the accuracy of the data analysis for IoT botnets to be more scalable. The challenge is to separate and to filter the important data from the rest and interpret them in a valuable way by (Michael, 2017). According to the Swarnamugi et al. (2016), it is impossible for human to review and understand this data and doing so with traditional methods.

Table 1.1: Summary of Problem Statement (PS).
PS Problem Statement (PS)
PS1 Lack of security on IoT devices.
PS2 Machine learning is not efficient for IoT botnets detection.

1.2 Project Question (PQ)

The project questions are very important in order to help the successfulness and effectiveness of the project. At the end of this project, the user will know either each of the questions had been successfully done or not. This is also one of the way on achieving the objectives of this project.

Table 1.2: Summary of Project Question
PS PQ Project Question
PS1 PQ1 What kind of IoT botnets attack that possible infect in the devices and is there all the IoT botnets attack can be detected?
PS1 PQ2 How the basic operation and the alert will be received to the user effectively and is there any notified alert directly and urgently?
PS2 PQ3 How much easier and effective are the machine learning detection are being used?

1.3 Project Objectives (PO)

Table 1.3: Summary of Project Objectives
PS PQ PO Project Objective
PS1 PQ1 PO1 To study possible attacks which are used to infect IoT devices.
PS1 PQ1 ; PQ2 PO2 To analyze the behavior of IoT botnets attack based on basic mode of operations and communication.
PS2 PQ1, PQ2 ; PQ3 PO3 To measure the best method of machine learning network based on IoT botnets detection.
1.4 Project Scope

The scope of the project is going to be handled as follows:

• Focusing on the IoT botnets namely Mirai and Hajime that exploit in devices which may positively affect user behavior.
• Focusing on IoT botnets attack.
• This project will be use the machine learning as a platform that will detect the IoT botnets.
• This project also will also focus in Linux Operating System.

1.5 Expected Output

The goal of this project is to provides the machine learning techniques for effective detection of IoT botnets flows that have high predictive accuracy. This project also to study, understand, analyze and also summarize the behavior of IoT botnets attack using machine learning. Moreover, in this project need to test the machine learning based classification techniques on flow data captured from Mirai and Hajime botnets only. In addition, this project also need to test the machine learning technique in large-scale network set-ups.

1.6 Thesis Organization

1.7 Summary

As a conclusion, this chapter helps to comprehend the project background, the target that should be accomplish and issues happened before begun the project. Based on the related topic in this chapter which is the problem statement, project question, project objective, project scope and the expected output concludes that this study want to propose a new approach of machine learning that capable detect the IoT botnets. According to Vladimir et.al. (2017), the growing number of IoT botnets programs focusing on devices and related security incidents demonstrates how genuine the issues of smart device security are. Besides, this project gives the contribution on identify specific IoT botnets attack and its behavior. This project also gives contribution on how the machine learning can be used as simple as detection method in the real environment. The next chapter will be focusing on the literature review that will cover about the model approached and related work about the IoT botnets that affect unsecured devices indirectly give awareness to users how important to have advanced security features. Besides, this project approaches with a comparative analysis of machine learning method of the best results and concluding remarks.

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