vulnerability testing using single board computer

Streamlining “Smart Grid End Point Devices” Vulnerability Testing Using Single Board Computer Mohammed Saleh*, Nedaa Baker Al Barghuthi*, Khadija Alawadhi*, Fatima Sallal*, Azzeddine Ferrah* * Higher Colleges of Technology United Arab Emirates {msaleh1, Nedaa.Albarghuthi, H002272641, H002250984, aferrah}@hct.ac.ae

Abstract—The fourth industrial revolution is characterized by the digital transformation of industries that will vitally alter the way we live and work. Globally, developed and developing cities are eager to transform themselves into future cities or smart cities. Within the context of the smart city, a wide range of stakeholders interact to manage public services including the smart grid. A smart home is the ultimate pillar of a smart city and the classic approaches of providing untested and unsecured smart technologies to home tenants may lead to fading of satisfaction and losing ground. Several DDoS attacks that shut down portions of the internet were fueled by bots created from hacked connected devices, like internet-connected cameras and DVRs. It can also theoretically include other connected IoT (Internet Of Things) devices such as Smart CCTV Cameras, smart meters and other Smart Grid end point devices that are used for the safety and security of the Grid. CCTV cameras are increasingly in smart home and Smart Grid networks for monitoring the usage of sub-electrical power station for security, operation and maintenance. This paper proposes and evaluates a prototype of a portable reliable, cost effective and simple to use vehicle for security testing Smart Grid end point devices using single board computer as a starting point for identifying the vulnerabilities, leading to consumer confidence and satisfaction. Keywords—IoT, Smart Home; Smart Grid; Single Board Computer; Vulnerability Testing; Smart Camera (keywords)

I.

INTRODUCTION

The digital transformation of industries fueled by the fourth industrial revolution is customarily accompanied with providing users with a wide range of choices and more convenient alternatives

in the smart grid and the smart homes connected to the grid. These advancements is inciting stakeholders to thrive staying up-to-date with the latest technology. A smart home connected to the smart grid consists of modern devices that provide owners with the luxury of remotely controlling various appliances; this has in many cases proven to assist in controlling expenses and saving time while providing the user with flexibility and convenience. Consequently, the number of home devices connected to the Internet is rapidly growing. Researchers expect that there will be over 20 billion smart devices connected to the internet, currently there are 6 billion connected devices online globally. Few years ago, it used to be just computers that were connected to the Internet but now with IoT, almost everything can have internet capabilities and have the potential to be online such as smart cars and e-locks. IoT is increasingly considered the new technology trend. On another hand, the unsecured smart devices have a potential of being hacked by external users. This was highlighted in the news recently when Twitter services were temporarily down following the DDOS attack on Dyn fueled by bots created from hacked connected devices, like internet-connected cameras and DVRs. [2] Although the implementation of smart homes appears to be the ideal alternative to our traditional homes to adopt to the smart grid, users must be aware that these devices may be accompanied with various security flaws that if not acknowledged can become a threat to the user. Security and privacy are one of the fundamental aspects that an individual requires in their smart home as shown in figure 1a. [1]

(A) CLIENT SIDE THREATS [1]

(B) CCTV IN SMART GRID NETWORKS [3] FIGURE 1 SMART GRID END POINTS

Considering these devices may be prone to attackers attempting to penetrate their privacy, penetration testing on these devices can be accomplished to identify potential risk as the first step to mitigate them [1]. To facilitate this process, a single board computer Raspberry Pi is used as the vehicle to host the Kali Linux operation system and the penetrations testing tools. Using the mentioned devices and tools provides a reliable, cost effective and simple to use vehicle for security testing IoT home Devices and smart grid networks and demonstrating potential risks in poorly designed or maintained ones. II.

PROBLEM STATEMENT

The purpose of this research paper is to design a prototype for a low cost security testing system for smart cities IoT devices that will shed light on potential risks in existing low cost smart home devices and smart grid end point devices and eventually increases cyber security awareness, thus this paper will focus on the real problems that exist in smart cities. Smart CCTV cameras are used for security and to monitor unusual electrical system and electric wire, and improper usage of smart meters in smart homes and smart grid networks [3]. Many unsecure low cost smart IoT devices are freely sold online and people rely on these unsecured cheap products looking to turn their home into a smart one. Unfortunately these products contains many vulnerabilities that allow potential hackers to have full control on them in awake of inadequate awareness level about the potential risks in smart home devices connected to the internet and to home networks. This paper will test if these devices are secured enough and able to protect people’s privacy and

monitor smart meters efficiently before using them at home seeking to have secure smart home and secure smart grid environments. People should be aware of different types of threats might inherited in these smart devices because most of them are designed to run on a low voltage and without firewall nor proper secured web application on them. Usually the end-users buy smart devices with lack of cyber security knowledge. Furthermore, this paper shed light to end-users and developers on the importance of cyber security on smart home devices and smart grid resources. This paper highlights a significance vulnerability testing method to be applied on smart devices to test if they are safe, robust and secure to add them in smart homes connected to the grid in order to protect smart cities resources, thus the test exposes real problems existed in smart home devices. While, a surveillance device is used for testing purposes in our project, the same concept can be used to test smart meters, elocks and more. III.

TECHNICAL BACKGROUND

The use of smart devices is growing up at home to help people facilitate their daily activities. These devices are connected online and in many cases 24*7. They are key components of home automation, smart homes and smart grid networks in order to computerize and facilitate the ability to control items around the house—from smart locks, window shades to advanced surveillance cameras in a simple and inexpensive way. It is not science fiction any more to water your garden, control air-conditioning thermostat and setting up a lamp to turn on and off at your request from an application running on your mobile [4].

Consumers may not realize the price they pay for living in the future. There are other types of danger that we should be more concerned about that are getting less attention. For example, newly installed surveillance camera could turn on by providing a window for a hacker to spy on someone. Computers are becoming second hand tool. Smartphones are increasingly dominating its usage to connect to these gadgets and some experts predict that in few years, smartphones will be main computing device rather than the classical computer one. Developers are always reminding computer and laptop users to secure their devices by setting up firewalls, updating software’s and updating patches, however, we are less told about the security of the information flowing in and out of the smart home devices. In smart home, all of smart equipment; like audio equipment, video equipment, light equipment, air-condition control, camera and window curtain control; are connected to the Internet of Things to provide automatic control of devices [5]. In this paper we proposed and tested a design for secured testing smart home devices and smart grid networks. The core of this design is a low cost single board computer loaded with easy to use penetration testing tools and in particular a third generation Raspberry Pi. The proposed solution method is an easy usage testing environment which can be used and bundled with additional open-source NoMachine graphical desktop sharing system to the Raspberry Pi device. [6] A. Software and Tools Facilitating the penetration testing requires using range of programs and tools with relatively minimum programing skills and knowledge. The gadget used in our research is a smart surveillance camera. The proposed Raspberry Pi based testing system is used to for testing the smart camera looking for any vulnerabilities and exploit the discovered ones seeking to demonstrate the lack of security in these smart devices. Software and tools that are used in this test are grouped according to their purpose. There are software used for scanning for the vulnerabilities such as Nessus vulnerability scanner. The Kali Linux operating system is a rich environment with many useful built-in tools used for penetration testing and forensic investigations [7]. Moreover, Fiddler web debugger tool is used in this experiment, it allows to intersect the communication channel and able to extract confidential information from the connected line [8]. In additional, an Angry IP scanner is used as

well in this experiment to scan and detect the IP address of the smart CCTV camera which is used in this experiment. Tight VNC and PuTTY tools were used for remote access to Raspberry Pi device. [9] B. Hardware Components The vehicle used to incubate the test is a low cost single board computer; in particular the third generation Raspberry Pi Model B, 8 GB Micro SD card, Ethernet Cable, HDMI wire, monitor, USB keyboard, mouse and USB power supplier. C. Design

The first draft of our proposed prototype was a virtual 3D smart home design with various smart devices such as smart light, smart access door and smart CCTV Camera as shown in figure 1b. In this research the penetration testing is conducted on a smart CCTV camera as a part of smart grid network. This test can also be applied on any other smart devices in smart cities. Eventually this will increase the cyber security awareness to maintain security on these smart devices. IV.

INTEGRATION AND IMPLEMENTATIONS

A. Raspberry A single board computer third generation Raspberry Pi model B was selected for testing smart home system. It has built-in Wi-Fi 802.11n and Bluetooth 4.0 connectivity features. Also, it includes a quad-core 64bit ARM Cortex A53 running at 1.2 GHz means approximate 50% faster than Pi 2 as shown in figure 2. [10]

FIGURE 2 RASPBERRY PI 3 BOARD

The main goal of having this single board computer type is for its mobility, reduction of cost and simplicity since Raspberry Pi 3 is considered as an affordable easy way to use real computer device. Furthermore, it is easy to use different type of operating system by changing only its bootable SD card memory. The board size is small and more practical to use. The first stage is to

prepare the Raspberry board [11]. To set up the board, it requires to install Raspbian image on its SD memory card. Once the installation process is completed, the card is plugged into Raspberry board and connected to LCD using HDMI cable and the keyboard and mouse is connected as well to the Raspberry board. Once the Raspberry board is ready, the next stage is to install Kali Linux OS and the required tools on the SD memory card needed to perform the vulnerability testing. The Raspberry board is remotely managed by a laptop. This can be implemented by using RJ45 cable to connect between them and disabling the SSH feature on the raspberry board. The IP address of the raspberry is obtained by using the Angry IP scanner which scan the entire network and detect the IP of the device as shown in figure 3.

V.

RESULTS AND DISCUSSION

A. Surveillance Camera In the research experiment, the vulnerability testing was performed on surveillance camera used in a smart home. It is easy to extract the IP of the camera by using Angry IP scanner or by scanning the network using Nmap command. In this test Nessus scanner tool was used to scan the vulnerabilities of the smart camera as shown in figure 5.

FIGURE 5 SUCCESSFUL CONNECTION TO RASPBERRY

FIGURE 3 ANGRY IP SCANNER TOOL RESULT

After that, PuTTy utility is configured on the laptop to establish a new SSH session to access to the board from the laptop by using the IP address of the board. VNC viewer software is used to access remotely to the raspberry board as shown in figure 4.

B. Nessus Nessus is a vulnerability scanner that can scan BOARD all the vulnerabilities existed on the smart device by providing its IP address only. This scanner is one of the most popular scanners that provides a summary page of the discovered vulnerabilities with its severity levels [12]. In our experiment, there were 14 vulnerabilities discovered on the smart device as shown in figure 6.

FIGURE 6 NESSUS OUTPUT RESULTS

FIGURE 4 VNC CONNECTION RASPBERRY

C. Kali Operating System Kali is Linux distribution made for penetration testing and security auditing. It has a wide range of built-in tools that helps the pen-tester to complete the assignment. Furthermore, it is an open source platform maintained and funded by Offensive Security. Kali OS is considered most

advanced penetration testing distribution by having more than 300 pen-testing tools such as SQL map for exploiting SQL injection vulnerabilities, Nmap that helps in scanning the running services on the entire network [7]. On Raspberry Pi you can have many operating systems in one single board with different purpose, in this test, exploiting vulnerabilities in surveillance camera was conducted via Kali OS. Installing Kali OS in the Raspberry board required 8 GB SD card; inserted in the laptop, Kali OS is freely available in Kali official site, once the image complete plug the card into the slot in Raspberry. A login page of Kali will displayed that’s mean configuring another image in the board was successfully. [13] During the penetration testing; after few steps of implementation, access was gained to the surveillance camera in the smart home which can be connected to the smart grid in the real life 24*7 without the knowledge of the owner only by getting the IP address. The reason of easily access to the system because of weak authentication since many users do not modify the default username and password. There are more tools used to test the security of the camera but in this test we used specific tools for demonstration purposes. D. Fiddler

It is one of web debugging tools that extracts critical information of the asset such as server name, username and passwords. Furthermore, it provides cookies information which can lead to session hijacking [8]. For this project, Fiddler was used to capture the credential information of the login page during authentication process. There are many tools can work as Fiddler and more efficiency such as BurpSuite, which is widely used for pen-testing purpose [6]. It can intercepts all request and response between the browser and target application even if it uses secure technologies such as HTTPS. Also has a feature to display and manipulate the hacked session channel. VI.

CONCLUSION

Smart home devices and Smart Grid end point devices are increasingly invading our homes and our daily life, however the security aspect of these devices is strangely overlooked. Although, DDoS attacks are not new attacks, alarmingly the attack on Dyn was conducted via connected smart

devices; like cameras; used to form CCTV botnet such as the recently Mirai botnet. Hackers recently developed new types of malware which scans the Internet for IoT devices in order to connect and compromise those devices. The market is flooded with smart home devices that are sharing the same basic weaknesses which are less secured and with basic functions required them to accept requests from any web user. This combination makes them easy targets for hackers to launch ransomware attacks or build harmful botnets by flooding them with millions of malicious nonsense requests in a very sophisticated way. Currently, security is not the main enabler for IoT neither there is currently regulations on security shielding in IoT on the device. Kaspersky highlighted IoT security flaws threats and demonstrated them with example of hacked smart homes, fitness trackers, government CCTV systems and many more. Wind River proposed addressing security throughout the device lifecycle, from the initial design to the operational environment. End use awareness of modern technology; like smart home; should ensure they have tested and are aware of the security level and act based on that. A smart home prototype's security level has been tested, the results were shocking as we came to realize several data was obtained using a wide range of easily accessible applications that have allowed the user unauthorized access, eventually invading other people's privacy. The applications have allowed the user to monitor and have full access to the devices in smart home. Not only does this give access to personal information, but it may also aid an individual with bad intentions on committing various serious crimes. REFERENCES [1] Anthony R. Metke and Randy L. Ekl, “Security Technology for Smart Grid Networks”, Smart Grid, IEEE Transactions on, vol. 1, no. 1, June 2010 [2] Farouk, S. (2017). Security specialists warn of penetrating home cameras [Online]. Available: https://translate.googleusercontent.com/translate_c?depth =1&hl=en&prev=search&rurl=translate.google.ae&sl=ar &sp=nmt4&u=http://www.albayan.ae/across-theuae/news-and-reports/2017-01-231.2835540&usg=ALkJrhiPT5YztnEQO5a_PjR5kAPt2gT qow [3] K. Thananunsophon, C. Pavaganun and P.P. Yupapin, “Community Monitoring and Security using Intelligent Camera in EAT Smart Grids”, 2nd International Science, Social Science, Engineering and Energy Conference 2010: Engineering Science and Management, pp. 332336, 2011.

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