Intrusion Detection and Prevention Logical Sensing 

Intrusion Detection and Prevention In Smart Home
Using Logical Sensing

Rohit Shankar Ragmahale
Department of Computer Engineering
D Y Patil College of Engineering, Ambi
[email protected]

Abstract—Since last 4-5 decades the concept of home au-
tomation has been there. Peoples expectations regarding home
automation and security has changed a to large extent during the
course of time due to the advancement of technology and services.
Different automation systems over the time tried to provide
efficient convenient and safe way for home inhabitants to access
their homes. Irrespective of the change in user expectations,
advancement of technology, or change of time, the role of a
home automation system has remained the same. This paper
explains various security issues in current home automation
system and proposes an algorithm based on logical-sensing
to improve home security. Depending on the usage of home,
system classified home access points into primary and secondary
access points. This logic based sensing algorithm is developed
to identify abnormal behaviour of an user, also this system
considers the states of various access points. Goal is to develop
smart, cost-efficient, collaborative, robust smart lock. System is
using Arduino, ESP8266, proximity sensors, motion sensors and
other to identify user behaviour at secondary access points and
implement the logic based sensing algorithm. This whole system
will act as distributed lock working in sync with primary access
points lock in order to have more robust and smart locking
system. This System is cost-efficient as there are smart sensors
which are placed smartly at secondary access points from where
intrusion may occur.

Index Terms—internet of things (IoT), Home automation,
smart homes, Sensor Data.

I. INTRODUCTION

Researchers have been experimenting and improving the
concept of smart home since the late 1970s. As technology
advanced with time, electronic devices and internet became
more popular and affordable, so the concept of home automa-
tion and peoples expectation from a smart home has changed
dramatically. Modern smart home is a sophisticated combina-
tion of various Ubiquitous Computing Devices and Wireless
Sensor/Actor Networks. All these new user expectations, com-
plicated electronics and unpredictable user behaviour brought
new security challenges to the home automation front. The
concept of home automation security has also evolved with
time, sensors and actuators were integrated into the home to
detect, alert and prevent intrusions. In the past, an average
home had to deal with common slash and grab criminals, while
a modern home has to deal with sophisticated and tech savvy
attackers who know how to find vulnerabilities and manipulate
the security devices to gain access or cause distress to the

Prof. Dhanshree S. Kulkarni
Department of Computer Engineering
D Y Patil College of Engineering, Ambi
[email protected]

inhabitants. Despite smart home security being critical there
are some vulnerabilities in the existing systems.

Over the years researchers demonstrated various security
issues associated with the devices and technology used in
modern smart homes. The wireless sensor networks deployed
in modern smart homes for device to device communication
is vulnerable to various Routing and Wormhole attacks. All
these factors contributed to the rapid rise in home burglaries
over the past decade and demonstrates the importance of
Home Security in the modern world. Our previous works in
smart home security explains the changing role of modern
home security systems and defines the role of a modern home
automation system as, one capable of identifying, alerting and
preventing intrusion attempts in a home at the same time
preserving evidence of the intrusion or at- tempted intrusion
so that the perpetuator or perpetuators can be identified and
prosecuted. Intrusion detection functions include:

Observing and analyzing both user and system be-
haviours.

Analyzing system configurations and vulnerabilities

Patterns recognition for certain type of attacks

Analyzing abnormal activity patterns

Tracking user policy violations

A. Novelty

Ideal way to improve home security and defend against
intrusion is to recognize a homes inhabitants and identify their
position inside a home at all times without inconveniencing its
inhabitants. This is extremely challenging and complex, given
the unpredictable nature of human behaviour and home being
occupied by guests and other trusted people. Identifying access
points to a home and regulating access to them is the next
logical step towards securing a home. Normal user behaviour
at access points to a home adhere to a set of predictable
behaviours. These user behaviours when analyzed by our novel
logical sensing algorithms can differentiate between normal
and attack behaviours. Existing systems are able to secure the
primary access point of the home (i.e. Door) but windows,
balcony are always vulnerable to intrusion.To improve smart
home security by using smart logical sensing mechanism at
secondary access points which is integrated with smart lock
of primary access point of a home.

B. Goals and Objective

To identify primary and secondary access points in a
home based on how they are used. Detect all user actions
at these access points

To detect and analyze user actions and behaviour after
change in state of an access point.

To identify insecure secondary access point and alert user
regarding the same.

To identify and isolate attack behaviour by analyzing
the user behaviour at various access points using our
logical sensing algorithm. Trigger warning or raise alarms
depending on the situation.

To perform trajectory mining using sensor data to trans-
formation from uncertain to deterministic trajectory data.

II. REVIEW OF LITERATURE

Now a days IoT research has grown exponentially, smart
home security has improved to next level. Still there are many
challenges in system:

A. From Homeowner’s Point of View

In many cases, money is motivation or the bottom line
for the common homeowner when choosing different
home automation products. People are either not aware,
misinformed, or do not care enough about several security
risks.

People in home are always of different backgrounds
mostly they are non technical, different age groups, guest
may come to home and homeowner can not expect all
these people will be careful about security mechanism in
home.

Portable devices like mobile phones, laptops uses home
network and these devices goes with user wherever they
go and gets connected to different networks. Attacker
could make use of these devices as a gateway to home
when user again connects to home network.

there can be a case when guest may feel insulted when
access gets denied to guest due to restricted access to few
people. Owner has to do some change in settings to allow
guests.

There is a big difference between what user thinks is im-
plemented of access control and the security mechanism
that are actually implemented.

B. From Security Engineer’s Point of View

Unlike in companies, one cant enforce policies or security
procedures that affect the convenience of people at home
or their guests.

People are careless about even simple security policies.

Home may consist of people of different age groups e.g.
Senior citizens which are not cable of understanding the
technical aspect of the security system is more vulnerable

to social engineering.

An attacker who hacks a home automation network can

cause a wide range of damage, including theft, vandalism,
emotional harm, permanent damage to electronic devices,

loss of reputation, financial damages, blackmail, environ-
mental damages, physical harm to a homes inhabitants,
granting unauthorized access to anyone.

• The mixed ownership of devices at home and guests
with varying technical knowledge and different intentions
compounds security issues at home.

V. Bellotti and K. Edwards, In their essay has presented
a framework for designing context-aware systems that are
both intelligible to their users and support the accountability
of other users and the system itself. From their proposed
principles, people begin to envision a set of requirements for
systems designed to support context-aware computing. This is
particularly true in cases where inferences about user behavior
or desire are separated from the applications with the domain
knowledge necessary to situate such inferences.

Alheraish discussed a home automation security system us-
ing Short Messaging Service (SMS). The unauthorized access
into the home is identified by monitoring the state of the home
door using LED and IR sensors. He proposed system that
allows legitimate users to control home lights and set the 4
digit passkey using SMS. The LED and IR sensors used to
identify intrusions could easily be spoofed by a sophisticated
attacker. Informing the user about an intrusion via SMS is not
a good practice, as the user may not be near to the phone to
receive the alert on time.

In system designed by Arun, the device fingerprint along
with username/password based security proposed that enables
the verification of user as well as the device used to access the
home, which significantly improves home security when they
are accessed over the internet. Unlike any previous approaches
to device fingerprinting, thay use geolocation data in their
algorithm which improves the fingerprint accuracy.

Yurur et al. proposed that context aware sensing vary
depending upon user environment, prior knowledge of recent
event patterns, user perception and context. Advanced sensing
techniques and high processing power makes context aware
sensing an expensive proposition for smart homes. In addition,
during context aware computing the system handles very
intimate and private information about a user and his habits,
which has to be shared for the concept to be implemented
successfully, this raises serious privacy issues.

Yuchen Yang and team has presented the security and
privacy issues in IoT applications and systems. They pre-
sented the limitations of IoT devices in battery and computing
resources, and dis- cussed possible solutions for battery life
extension and lightweight computing.

1) Battery Life Extension:

• Use Minimum Security mechanism
• Increase battery capacity
• Harvest energy from natural resource.

2) Lightweight Computation:

• In one line, conventional cryptography can not work on
IoT system.

III. SYSTEM ARCHITECTURE / SYSTEM OVERVIEW

IoT can be considered as a worldwide physical inter-
connected network, in which things can be connected and
controlled remotely. As more and more devices are equipped
with Motion or intelligent sensors, connecting things becomes
much easier.

IoT aims to connect different things over the networks.
As a key technology in integrating heterogeneous systems or
devices, service-oriented architecture (SOA) can be applied to
support IoT.

The architectural design of IoT is concerned with ar-
chitecture styles, networking and communication, smart ob-
jects, Web services and applications, business models and
corresponding process, cooperative data processing, security,
etc.From the technology perspective, the design of an IoT
architecture needs to consider extensibility, scalability, modu-
larity, and interoperability among heterogeneous devices.

As things might move or need reatime interaction with their
environment, an adaptive architecture is needed to help devices
dynamically interact with other things. The decentralized and
heterogeneous nature of IoT requires that the architecture
provides IoT efficient event-driven capability. Thus, SOA
is considered a good approach to achieve interoperability
between heterogeneous devices in a multitude of way

Fig. 1. SOA for Smart Home Security System

1) Sensing Layer: In the sensing layer, the wireless smart
systems with tags or sensors are able to automatically sense
and exchange information among different devices. These
technology advances significantly improve the capability of
IoT to sense and identify things or environment.

2) Controller Layer: In the controller layer, different sen-
sors are controlled by micro-controller e.g. Arduino. Controller
processes/compare the sensor data to make certain decisions
locally and sends data over network to server. It accepts data
from server and set the device state accordingly.

3) Networking Layer: The role of networking layer is to
connect all things together and allow things to share the
information with other connected things. In addition, the

networking layer is capable of aggregating information from
existing IT infrastructures (e.g., business systems, transporta-
tion systems, power grids, health-care systems, ICT systems,
etc.). Services provided by things are typically deployed in a
heterogeneous network and all related things are brought into
the service Internet.

4) Service layer: Service layer relies on the middle-ware
technology that provides functionalities to seamlessly integrate
services and applications in IoT. The middleware technology
provides the IoT with a cost-efficient platform, where the
hardware and software plat- forms can be reused. A main
activity in the service layer involves the service specifications
for middle- ware, which are being developed by various
organizations.

IV. SYSTEM ANALYSIS

System analyzes various access points in a home to identify
different improbable scenarios within a smart home during
its operation. Access points are inherent in the structure of a
home, which can be used for entering and exiting a home.
In a typical home these natural access points are front door,
back door, balcony doors and windows. Even though window
is not a normal access point it can be used as one, most
likely by an intruder depending on the situation. Physical
access to a home is only possible through these access points
unless serious structural alterations are made to a home.
These serious structural alterations can not be made without
drawing attention to the act itself, like blasting or destroying
a wall to create an entrance. So, managing access at these
access points is crucial in securing a home.

Based on the purpose of the access points, the system
classifies access points into primary and secondary. In a home,
when an access point is used by its inhabitants as a primary
means to enter and exit from their home, it is categorized as
primary access point like the front door, back door etc. On the
other hand, secondary access points like the window, balcony
door etc. also provide entry/exit to a home but they are rarely
used for that purpose because there are other convenient ways
in and out of a home for a legitimate user.

A. Intrusion Prevention Algorithm

Front door is the primary access point to any home, inhab-
itants use this door as the main way in and out of their home.
Depending upon the architecture and inhabitant needs, there
can be one or more primary access points. Whenever a home
changes state from occupied to empty the algorithm checks if
the secondary access points to the home are secure. If not, it
issues a warning to the user to secure the secondary access
points.

Fig. 2 shows the flowchart of the secondary access point
checking when the home becomes empty. In this way, using
simple mechanism user can do intrusion prevention.

B. Intrusion Detection Algorithm

The balcony door and window form the secondary access
points in a home. In a typical home, the window is not used

Fig. 2. Intrusion Prevention Algorithm

as the main access point to and from a home. Usually window
opens into a relatively secure and private area, sometimes
even a few floors up. So, these window can remain open for
long periods of time when the house is occupied. When the
home becomes empty an observant, resourceful and proficient
intruder can use this window to gain access to the home,
in order to avoid that, window must be closed when the
home becomes empty. Moreover, when the home is empty
the window should not be opened under any circumstances.

After the initial state change the algorithm keeps observing
the window for a specific interval of time called window
observation time; the window state during this time is called
intermediate state of the window. Fig. 3 shows the flowchart
intrusion detection at the secondary access point. The algo-
rithm observes the motion and proximity sensor values during
the window observation time to identify user actions at an
access point

This system proposes the use of motion and proximity
sensors to detect user behaviour at secondary access points.
The motion and proximity sensors placed near the secondary
access point i.e window inside the home are triggered before
the window is opened. When user opens a window from inside
and goes away motion proximity sensor will be triggered
before and after the window state change. When someone
enters an empty home using window, they are entering from
outside so, the motion and proximity sensors will not be
triggered before the window is opened. Once the window
is opened and the user enters the home the motion and
proximity sensors placed inside the home will be triggered.
The algorithm keeps monitoring the state of the window, so
in an empty home when the window door is opened from
outside the system triggers intrusion detection mechanisms.

Fig. 3. Intrusion Detection Algorithm

Fig. 4. Intrusion Detection Algorithm States Chart

V. CONCLUSION

The system detects user actions at secondary access points
in a home using different sensors. These detected user actions
and behaviours are compared with normal user behaviour
at various access points to identify intrusions or intrusion
attempts. Access point data is stored in a data base on cloud
platform with access limited to authorized personals.
This paper proposed cost-effective, Simple-to-use, Lower-
maintenance, Easily adaptable security system to secure sec-
ondary access points of smart home.

ACKNOWLEDGMENT

I wish to thank all the people who gave us an unending
support right from the idea was conceived. I express my
sincere and profound thanks to our Head of the Department
and my Guide Prof. Dhanshree S. Kulkarni for their guidance
and motivation for completing my work, and I am also
thankful to all those who directly or indirectly guided and
helped me in preparation of this paper.

REFERENCES

[1]  Li Da Xu, Senior Member, IEEE, Wu He, and Shancang Li, Internet of
Things in Industries: A Survey, IEEE TRANSACTIONS ON INDUS-
TRIAL INFORMATICS, VOL. 10, NO. 4, NOVEMBER 2014

[2]  ArunCyrilJose1andRezaMalekian2,SmartHomeAutomationSecurity:
A Literature Review Human-Comput. Smart Computing Review, vol. 5,
no. 4, August 2015

[3]  N. Komninos, Member, IEEE, E. Philippou and A. Pitsillides, Senior
Member, IEEE, Survey in Smart Grid and Smart Home Security: Issues,
Challenges and Counter- measures, IEEE COMMUNICATION SUR-
VEYS TUTORIALS, VOL. 16, NO. 4, FOURTH QUARTER 2014.

[4]  A.Alheraish,Design and implementation of home automation sys-
tem,IEEETrans. Consum. Electron., vol. 50, no. 4, pp. 10871092, Nov.
2004

[5]  ARUN CYRIL JOSE1, REZA MALEKIAN1, (MEMBER, IEEE), AND
NING YE, Improving Home Automation Security; Integrating Device
Fingerprinting Into Smart Home IEEE Access, August 29, 2016

[6]  V. Bellotti and K. Edwards, Intelligibility and accountability: Human
considerations in context aware systems, Human-Comput. Interaction,
vol. 16, no. 2, pp. 193212, Dec. 2001

[7]  O. Yurur, C. H. Liu, and W. Moreno, A survey of context-aware
middleware designs for human activity recognition, IEEE Commun. Mag.,
vol. 52, no. 6, pp. 2431, Jun. 2014

[8]  S. Saponara and T. Bacchillone, Network architecture, security issues,
and hardware implementation of a home area network for smart grid, J.
Comput. Netw. Commun., vol. 12, Nov. 2012, Art. no. 534512

[9]  Yuchen Yang, Longfei Wu, Guisheng Yin, Lijie Li, and Hongbin Zhao,
A Survey on Security and Privacy Issues in Internet-of-Things IEEE
INTERNET OF THINGS JOURNAL, VOL. 4, NO. 5, OCTOBER 2017

[10] A. Z. Alkar and U. Buhur, An Internet based wireless home automation
system for multifunctional devices, IEEE Trans. Consum. Electron., vol.
51, no. 4, pp. 11691174, Nov. 2005.

[11] UNODC International Burglary, Car Theft and Housebreaking Statistics