smarter home controller: a framework for...
TRANSCRIPT
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Semester research
Smarter Home Controller: A Framework for
Enhancing Home Security in Smart Grids
Author
Abdullah Almurayh
MSCS UCCS
[email protected] Purpose
Instructor
Dr. Edward Chow
Professor of Computer Science
Semester Research for
CS6910
Summer 2011
University of Colorado at Colorado Springs
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Abstract—Home automation commercial technologies have been deployed as smart grids have
extensively grown. Home automation raises the fact that home security needs an abundant amount
of attention. In fact, with home automation, all connected appliances are in a critical condition since
they are connected to the Internet. The term of cyber security can become an optimal explanation of
the most concerned at this point. However, home physical security can be enhanced in the case of
taking advantage of the home automation systems. This research proposes a framework that uses
smart appliance preferences as a guide of these appliances statuses. Any change in any appliance
status, can be considered normal or abnormal based on the appliance history. This helps the home
owners to improve their home security in case there is a cyber attack, physical attack, or a potential
failure. This paper describes the design of the framework and the underlying platform that is based
on multitier smart grids network including the controller area network CAN. The time frame was
not helpful to implement and evaluate the framework to prove that home automation systems can be
used positively to provide more effective home security with low cost.
Index Terms—Smart Grid, Power, Home gateway home controller, security, electricity.
1. INTRODUCTION
The growth of electric devices population causes more demands on electricity, which is a
reasonable motivation for managing power crisis and power outages. As a result, smart grids have become
an ideal solution to cover the need of more electricity efficiently and intelligently [1]. Home controllers,
on the other hand, enable home automation where a customer can remotely control his appliances to
achieve efficient power saving. In fact, smart grids and home controllers can be used to effectively defeat
against physical and cyber attacks.
In this research, a framework approach is described by taking advantage of smart grids and home
controllers to detect and defeat against both physical and cyber attacks. The approach can be adopted and
developed by home controller vendors. The approach uses the combination of smart appliances, home
controllers, gateways, and smart grids to provide significant security approach. This approach
fundamentally is based on a machine learning mechanism that describes the status of each smart appliance
as normal or abnormal, based on their history. The remainder of this research explains some
characteristics of smart grids, home area network, and controller area network that are used as essential
requirement for the approach. Some related work is addressed later on, followed by the framework
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modules and the design model. A Virtual example is given to emphasize possibility of implementing the
approach and to enclose the idea to the reader. That is followed by an indispensable discussion that
declares points that need to be considered in the future because these points are necessary as the research
is expended.
1.1 Motivation:
Home security is an important perspective in our lives. Security problems are a combination of
threats, vulnerabilities, and risks. In this research, I focused on two fundamental categories of Home
Security:
- Physical Security: Physical security is a phenomenon that exists in order to inhibit and prevent
criminals from entering a home physically.
- Cyber Security: Cyber security is an objective that implements protection of accessible
information and soft-property from larceny, attack, or intrusion.
Usually people subscribe for surveillance systems such as security cameras as an effective crime
solving tool. Other people, however, have a different perspective such as the cost of these systems.
Nevertheless, they still want effective security techniques that can defend, mitigate, or avoid unwanted
incidents. Consequently, the smart grids and home controllers have some practical techniques that make
them smarter than ever to provide the feasibility of both physical security and cyber security.
2. BACKGROUND:
2.1 Smart grids:
Smart grids are electrical grids that intelligently predict and respond to the behaviors of electric
power consumers [2]. Therefore, smart grids efficiently deliver reliable, economic, and maintainable
electricity services. Smart grids enable the opportunity for connected customers to be in charge and
achieve more power saving. In smart grids, not only do clients just consume energy, but also they produce
energy from different sources, such as wind power and solar power connected to power routers [3]. They
can concurrently use these alternate sources during the peak power demand to cover the power reductions
from utilities companies. To implement smart grids, the need for two-way communication is the core of
all smart grid creativities. In this methodology, the combination of global information communication
technologies along smart grids has certainly allowed both utility companies and consumers to be
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cooperatively related. Therefore, utility companies can obtain more information from their consumers, and
similarly, the consumers can receive more awareness about their energy consumption arrangements.
Based on that, a dynamic pricing mechanism can be accomplished to provide the consumers with
consumption viewer feedback using In-Home displays that monitor home energy consumption. Further,
by implementing a system for home automation, consumers can control their appliances remotely via web
based applications or smart phone applications. In fact, the result of the smart grids revelation emphasizes
that the future of smart grids is capable to achieve more intelligence, economic efficiency, world
connectivity, people interactivity, more opportunity and choices, living improvement, and security
enhancement. In order to accomplish smart grids across the world, there must be initiatives by
governments and the energy suppliers to improve the way of using electric power. In addition, customers
need to be cooperative to succeed with smart grids globally. Smart grids enable active participation by
consumers to accommodate all generation and storage options. Smart grids enable new products, services
and markets and optimize beneficial utilization and operating efficiency. In general, smart grids have
some features that mark them as intelligent grids. However, since smart grids share some common
networking requirements, they must implement security concepts including complete privacy.
Furthermore, smart grids must ensure maximum availability, fault tolerance, and have the flexibility to
cover the same disparate territories as the grid itself.
2.2 Communications in the Smart Grid
Grid communication architecture today uses the Internet, networked communications and the
large-scale deployment of wide-area broadband wireless networking technology [4]. As shown in figure 1,
there are several commonly used networks that involve in grid communications architecture:
1. Wide Area Network (WAN):
WAN is a distribution network that uses open standards to provide wide coverage communications
to smart grid devices such as substations, capacitor banks, and voltage regulators.
2. Neighborhood Area Network (NAN):
NAN is a metering network that uses open standards to create a wireless network among meters
and Advanced Metering Infrastructure (AMI) devices [5].
3. Home Area Network (HAN):
HAN is a consumer network that use open standards to provide customizable consumer solutions
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at low costs and enable a variety of smart grid consumer solutions.
Figure 1: Multi-tier smart grids network architecture
2.3 In-Home Smart Devices:
An In-Home Smart Device (IHSD) is home equipment that provides the consumer with tools to
monitor and control energy use and have better management (see figure 2) [6]. An IHSD is based on a
network that provides two-way communication between the smart appliances and portal applications for
managing the home remotely. Managing these appliances is enabled through web based applications or
smart phones based software. The IHSD provides information about the energy usage and functional tools
to change energy usage to achieve lower the energy costs. The IHSD increases the understanding of how
energy is being consumed in the home. In-Home smart devices communicate with each other and with
smart appliances via Controller Area Network (CAN).
2.4 Controller Area Network (CAN):
CAN is a network that allows smart devices to communicate with each other In-Home area.
Originally, CAN was developed in the automotive industry as an in-vehicle network. In 1993, CAN
became the international standard known as ISO 11898. CAN is a based on the broadcast communication
mechanism network with rate up to 1Mbit per second. In a CAN network, many short messages are
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Figure 2: In-Home Smart Devices connectivity
broadcasted to the entire network, which provides for data consistency in every node of the system.
Controller area networks are enabled to communicate with other networks by implementing the following:
1) Communications Protocols:
Controller area networks have diversity of In-Home connection methods. Most of them are wireless
communications protocols due to the ease of usability and lowering wiring cost. A popular protocol is
called ZigBee which is used for wireless networks based on the IEEE 802.15.4 specification [7]. ZigBee
has become the most attractive technique in the system environments because of open standard, low-cost,
and low power characteristics. Another protocol is named Wi-Fi which is an exclusive standard for
wirelessly connecting electronic devices such as computers, video game consoles, smartphones, or digital
audio players. Wi-Fi can connect to the Internet via a wireless network access point [8]. A New Standard
in wireless remote control protocol is named Z-Wave [9]. Z-Wave allows home electronics communicate
with each other and allows the consumer to control these devices remotely. Z-Wave uses low-power radio
waves that easily travel through walls. A new home wireless protocol is named HomePlug that was
developed to be a certification profile of the IEEE 1901 PLC standard [10]. HomePlug targets smart grid
applications such as smart meters, home appliances and plug-in electric hybrid vehicles.
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2) CAN gateways:
Gateways and bridges enable CAN-based networks to be linked to networks and other networks with other
protocols. A gateway between a CAN and another communication network maps the protocols of the
individual networks. For example, a message can be sent from an end-user across the internet using
TCP/IP protocol and then through different networks such as an Ethernet network or wireless network, the
message can be delivered to a smart appliance within a Controller area Networks.
3) Home Controller Device
A home controller device is a smart controller that enables the ability of having a local or remote
monitoring service and control of the smart appliances (explained later). The smart home controller is also
a system that consists of embedded controller, a communications protocol converter and terminal device
[11]. Smart home controllers allow the home owner to manage it and other smart devices by connecting
them to the internet through CAN gateways.
4) Smart appliances
A smart appliance is a characterized device that is able to use communication media to send and receive
information. Smart appliances are supplied with computer chips that can sense the need of power that
appliances need [12]. In a smart appliance, the transmission system is partially turned off to enable the use
of efficient power usage. Furthermore, home owners can schedule smart appliances to work and do their
jobs without human intervention. An important influence is that smart appliances enable smart access that
allows home owners to control and monitor appliances from outside of the home. Likewise, smart
appliances can alert home owners if there are serious conditions that exist [13]. Figure 3 shows the
architecture of a controller area network that interacts with outer networks such as NAN, LAN, and WAN.
Important components such as smart appliances and home controllers must be implemented in the CAN to
accomplish the intelligence of the smart home.
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Figure 3: controller area network architecture
3. RELATED WORK
1) Fire-Detection System: This paper presents a network-based fire detection system via the controller
area network (CAN) [14]. In my research, I use controller area network as well to detect abnormal
behaviors that help in home security.
2) Smart Digital Door Lock for the Home Automation: This paper proposes a smart digital door lock
system for home automation [15]. However, in my research, I do not propose additional equipment to
improve the home security. Instead, the same idea can be implemented based on smart grids platform.
3) Context-Aware Middleware for Controlling Home Appliances: This paper describes the context-aware
middleware providing an automatic home service based on a user’s preferences at a smart home [16].
Additional research is needed for adopting a different machine learning algorithm such as SVM (support
vector machine) and comparing the prediction ratio. In my research, on the other hand, I propose a
framework that uses three modules that work cooperatively based on machine learning mechanism to
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enhance home security based on the appliances preferences.
4. PROPOSED FRAMEWORK
I propose a framework for detecting abnormal home activities based on the smart appliances
preferences and historic behaviors. This framework enables more security practices using home
controllers to implement better secure living in smart grids. In fact, there are two evaluation matrices:
physical security and cyber security. In term of physical security, the framework can involve in detecting a
physical presence entering a home while cyber security indicates that the framework helps to detect
attacks aimed to the home appliances regardless of how the attack occurs.
4.1 The Framework Modules
The framework consists of three modules:
1) Learner Module:
The learner module approach is based on machine learning mechanism that allows the home
controller to examine home appliances behaviors based on historical and interrelated data that is captured
and logged. The learner module can be used in this approach takes advantage of the captured data to learn
and determine characteristics of the home appliances. For example, a refrigerator is probably working for
a long time without being turned off. Hence, the learner recognizes this characteristic that generally
represents the status of the refrigerator. Unfortunately, this module has to deal with the interference of the
various appliances that have different systems and manners. Consequently, that makes the design of a
good learner exceptionally difficult, especially in such complex environments. The module monitors how
the appliances behave and then illustrates the relations between the observed variables. A major focus of
machine learning research is to automatically learn to recognize complex patterns and make it easy for the
Detector Module (explained next) to intelligently detect mischievous actions based on the collected data.
Therefore, the learner must generalize and simplify the given behaviors to create a valuable log that can be
practically used by the other Module. The Learner Module needs to be adaptive by maintaining the
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collected status data. That means when a permanent behavior of a certain appliance has changed, it does
not necessarily indicate an abnormal behavior, which could be a normal behavior. This element increases
the difficulty and lies in the fact that new legitimate behavior changes cannot be considered as negative
actions.
2) Detector Module:
The detector module observes any progressing behavior and compares it to its appliance
preferences that have been learned and stored by the learner module. Based on an algorithm, the detector
module can determine whether the action is normal or abnormal. In the case where a behavior is abnormal
regardless of what shape its misbehaving is, the next module must react immediately.
3) Reporter Module:
The reporter module cannot function without a provocation coming from the previous modules. It
functions by sending a message to the consumer in three ways: a message to the home controller screen, a
copy of the message to the web-based center, and finally another copy is also sent to the consumer’s
phone or it could be a call from home.
4.2 The Framework Design:
Figure 4 illustrates the design of the framework that simply uses the existing home smart platform
which consists of:
1) Smart Appliance: This device must be smart to communicate with the smart home controller providing
practical information, especially about its status.
2) Smart Home Controller: It is considered as the heart of the design since it functions for the entire
framework. It uses the three modules (explained in section 4.1) to enhance home security.
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3) Gateway: A home gateway is a mechanism or device that connects a controller area network to the wide
area network. Implementing the gateway means opening the home to the internet which is necessary for
recognizing the consumer whenever an unusual incident happens.
4) End-User Access: Access to the information of the home is necessary for the consumer to browse or
view information about the home appliances. It is also required for the smart home controller to alert the
consumer in case an incident occurs.
Figure 4: controller area network architecture
4.3 Virtual Example:
Assuming the refrigerator is a smart appliance and connected to the smart home controller as
shown in figure 4. Firstly: during the initial work, the learner module collects data about the refrigerator
such as how usually it is turned on, the time it is working, and the number of times of being turned off,
and so on. The information in Table 1 shows a virtual history for the refrigerator including date, time, and
status. Based on the provided information about the particular machine, the detector module understands
that all times this machine must be running. Assuming two abnormal situations here: the machine is
having failure or it is being occupied. Furthermore, let us assume one of these abnormal situations has
happened to the machine which means the status is changed to 0. Therefore, the detector module must
compare the current status (0) with the learned status and decide whether this is a normal or not. If not, the
reporter module has to notify the consumer immediately via calling, emailing, or text messaging.
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Date Time Status
07-22-2011 09:57:26 1
07-22-2011 09:59:32 1
07-22-2011 10:01:11 1
07-29-2011 02:11:42 1
07-29-2011 02:13:10 1
07-29-2011 02:15:02 1
08-13-2011 14:37:59 1
08-13-2011 14:39:40 1
08-13-2011 14:41:49 1
Table1: Status history logger of an appliance.
4.4 Behavior classification:
Class A: Normal:
This class exists when any normal action occurs. Assuming an appliance indicates a usual status,
so that the learner module learns the appliance is normally in this status. However, when the status has
change to another status, normally, the learner module considers that a normal status as well (see Section
7).
Class B: Abnormal:
This class indicates that a normal status has changed abnormally to another status. There are two
possible abnormal situations:
1) Failure: This situation exists when there is a partial or complete failure in the appliance. This
situation is considered abnormal while it is less risky compared to the next situation.
2) Attack: this situation exists when one of the following two possible situations occurs:
a. Physical attack: It exists when a criminal physically enters a home.
b. Cyber-attack: It exists when accessible information gets attacked causing a compromise to the
home controller or appliances.
7. DISCUSSION
Home security is an important characteristic that people and researchers should cooperate with
each other in order to enable all possible and costless home security methods. Smart grids can be used as
an easy way to implement more effective home security in many ways, including the approach that this
research demonstrates (see Section 3). In fact, the research is not completed,yet, I believe it is worthy that
home controller vendors are able to adapt it. Unfortunately, two things prevent me from achieving
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implementation of this approach. One is that it is difficult to obtain a development kit that provides a
design environment for engineering the approach. Another considerable factor is that of the cost of
purchasing the development kits including software, reference designs, cables, and programming
hardware could be unaffordable [17]. In addition, even if the development kit or an actual home controller
is provided, it needs a skilled person or an engineer to develop the approach. Finally, the time frame was
such that there was not enough time to simulate the approach or even implement an algorithmic process
that solves the approach. Furthermore, if the algorithm is not precisely implemented, false positives may
result by the machine learning. This perspective mandatorily needs to be taken into account and
implemented perfectly.
8. FUTURE WORK
As future work, there are some implementations that the approach still needs. First, the approach
needs an algorithm to implement the three modules (mentioned in section 4). Second, the approach needs
to be simulated to ensure the integrity and to evaluate the implemented algorithm. Third, the approach
should be developed on a development kit to ensure the functionality and to evaluate it. Finally, if the
approach succeeds, it can be adapted by home controller vendors to enable more home security choices.
9. CONCLUSION
In conclusion, this research addresses an opportunity of implementing a new method of home
security. Smart grids have become a future and it is capable to enable home security features by enabling
this approach or it may be a different approach that can be implemented as well in home controllers.
Essentially, the approach seems effectively applicable in the existing smart grids environments. The
approach is expandable and hopefully it can be enhanced and enabled soon.
ACKNOWLEDGMENT
I would like to thank all those who have helped me to achieve this research project. First, I would
like to thank Dr. Edward Chow for his help, support, and inspiration for the research. I gratefully
appreciate his trust in me and giving me the opportunity to lead the decision and research in this scope.
He always gives advice and potential challenges that need to be considered in the research field. Second, I
would like to thank CS6910 class participants who provided some beneficial suggestions in proposing this
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research in the classroom.
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