a survey on next generation computing iot issues and ... · keywords ² internet of things (iot),...

A Survey on Next generation Computing IoT Issues

and Challenges

Anurag Shukla

Department of Computer Science & Engineering

National Institutes of Technology

Raipur, India

[email protected]

Sarsij Tripathi

Department of Computer Science & Engineering

National Institutes of Technology

Raipur, India

[email protected]

Abstract— With the popularity of the Internet of things (IoT),

an enormous number of sensors and smart object, which is

heterogeneous in nature deployed into a network, send/receive

data through the internet on the web. It is tedious to secure the

communicated data and the device identity otherwise it cannot be

adopted by their natives. But, existing security techniques that

are very popular on the Internet are too complex to integrate on

small, constrained objects. While initiating security through some

protocol and techniques, the life of battery operated sensor can

be reduced, so there is need to provide a proper balance between

security and energy. This paper presents a survey of existing

security protocols applied on IoT, their comparison and possible

solution for various attacks

Keywords— Internet of Things (IoT), Challenges and Issues,

Security, Possible Solutions, Energy and Quality of Services (QoS).

I. INTRODUCTION

With the progress in wireless communication, Pervasive

computing and mobile computing, resulted in a new model

known as the internet of things (IoT). IoT is attracting a lot of

researchers and industrial innovation. The definition for the

IoT could be as the ubiquitous and global networks, which

offer various applications for controlling and monitoring the

physical world activities of the information collection, data

cleaning, processing and analysis of data generated by IoT

sensors. These IoT devices have in built computation and

sensing capabilities such as RFID, GPS, actuators, LAN and

wireless LAN (Zhao & Ge, 2013). These "things" could

interact with each other (machine-to-machine (M2M)

communication) by making request and response for data and

sensing the real world attributes like temperature, pressure,

etc. These devices can be bind to the internet and could be

managed and operated remotely (Xu, Ding, Zhao, Hu & Fu,

2013; Wei & Qi, 2011).

It can be seen as a network of wide-range devices that

introduces not only the various security issues available in

sensor devices, mobile communication, and the internet, but

also some abnormal and accentuated issues like user and

network privacy, sensor life cycle (energy consumption),

secure routing and quality of service among these devices

(Zhao & Ge, 2013).

In the last few years, IoT became a hot topic in industry

and academic research. IoT is expanding everywhere and

supports a complete view of the real world and high level of

interaction with the physical world (Atzori, Iera & Morabito,

2010; Gubbi, Buyya & Marusic, 2010). Such areas are smart

transportation system; Energy monitoring system, e-

healthcare is just a few examples where IoT will be applicable.

The reorganization of IoT will largely depend on reliable

communication, network, system architecture, data

computation, resource allocation, and pervasive computing

technology, which provides efficient, secure, and physically as

well as cyber interconnectivity. The main agenda of it is the

device interconnection within the network, routing between

the networks, and specifically the last one dynamic security

level mechanism for the various nodes according their real

need by considering various parameters: energy and

computation capabilities. With increasing number of

interconnected devices on the internet (as shown in figure 2),

the daunting challenge is to secure the node network from

possible threats and attacks. People will feel insecure to

migrate their devices on the internet if there is a possibility of

being controlled or attacked from unauthorized person or

machine over the network (Ericsson, 2011).

International Journal of Pure and Applied MathematicsVolume 118 No. 9 2018, 45-64ISSN: 1311-8080 (printed version); ISSN: 1314-3395 (on-line version)url: http://www.ijpam.euSpecial Issue ijpam.eu

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Figure 1. Internet of Things and It’s Popular Application

Continue with our discussion, device communication and

routing is a critical part of it due to the need of maintaining

consistency while data or packet is transmitted between IoT

nodes across various network topologies. The processes of

making secure communication and maintaining a QoS even

more tedious (Gubbi et al., 2010). In it, various Sensor nodes

have different-different computation capabilities, and it is

running on battery power. Consider via the above factor‘s;

there is an essential need of a real-time security model so that

system can assign the different level of security techniques

according to node characteristics like- energy, computation

power, etc. for securing the data and routing process across

IoT nodes.

Figure 2. A forecast of more than 50 billion interconnected devices

by 2020. (Adapted from [CISCO, 2011]).

The IoT architecture (indicated in figure 3) is being

organized into three layers: perception, network, and

application layer (Zhao et al., 2013). The support layer (such

as cloud computing, intelligent computing) is also included in

some system architecture for the support of the application

layer (Suo, Wan, Zou, & Liu, 2012). In this survey, we have

considered three-layer architectures, which have been reported

frequently by other researcher. In this article, we explore the

IoT protocol, which works on network and application layer

and their vulnerability of being attacked during

communication.

The Rest of the article is organized into three sections. In

the first section we cover, the various definitions related to IoT

and their history followed by IoT application, in the very next

section, we provide the various IoT related challenges and

their issues: Security, Energy, and Quality of Service (QoS).

In the next section, we give the protocol stack corresponding

IoT layers and provide a comparison between them. In the last

section we analyze various IoT related security work which is

isolated from the standard protocols and categorize them

according to their key cryptographic techniques, we

summarize all these techniques and provide a comparison

table between them by considering their provide solution

against security threats.

II. DEFIN ITIONS, HISTORY & TRENDS

A. Definitions

Atzori et al. (2010) defined, IoT can be combined into three parts—internet (middleware), things (sensors) and semantic (knowledge/data analysis). Although this type paradigm is required due to the subject nature, the IoT requirement can be expanded only in the service domain.

Figure 3. Security Architecture (Suo, Wan, Zou, & Liu, 2011 ; Zhao & Ge, 2013)

According to the RFID group, the definition of IoT is: The worldwide-interconnected network of different objects uniquely identified based on an address scheme through standard protocols.

The Clusters of European research projects on IoT (Sundmaeker, Guillemin, Friess, & Woelfflé, 2010): "Things" can participate actively in social and business process where they able to interact and communicate with each other by transmitting the data and sensed value about the physical world, while responding autonomously without any human interaction to real/ physical world events and trigger some actions and offer the service.

International Journal of Pure and Applied Mathematics Special Issue

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By Forrester, Smart environment (Bélissent, 2010): Uses of information, communication technologies, and protocols for developing an infrastructure to serve the society, cities administrates transportation, health care and education more efficient, interactive and better.

In our definition, we believe in the theory that a common static architecture cannot be a blueprint for all applications, so we should make it more flexible to support scalability and do not restrict to any standard protocol. Our definition of IoT is Interconnection of devices in IoT networks is achieved through some standards or protocols. Day by day new devices are introduced into a market, for instance, some couple of years ago no one wonders about a mobile phone. Now, these days the mobile phone is smarter as computer and cheaper too. Therefore, we are suggesting here, Standards or protocols, which are used for developing the IoT network, should be open. When new devices are introduced in a network, standards can be modified according to their need.

B. IoT History

The term IoT is around 17 years old, but the real idea about connecting devices had been longer, around since 1970. At that time, the idea was often called "pervasive computing" or "embedded internet". The term, IoT was actually invented by Kevin Ashton at Procter & Gamble during his work. In 1999 "internet" was a hot topic and Kevin Ashton was working in supply chain optimization, wanted to collaborate two technologies: internet and RFID so that he can attract the senior management team. He called his presentation "Internet of Things". Even he got successes, but then it was remained untouched for next 10 years.

In the table 1, we give the brief history about IoT and cover the important events year by year, which can help to know that how IoT came into existence from other areas and what is the required technology, which can help in shaping the IoT world.

C. Trends

IoT is known as one of the emerging technology in research and it‘s industry. People's interest about different paradigms varied with respect to time. According to Google search (2017) trends, the web search popularity during the last 13 years for the terms IoT, wireless sensor network and ubiquitous computing is given in figure 4. It can be clearly observed that the popularity of it is increasing day by day with the downtrend of the wireless sensor network.

Figure 4. Google search trends (2004-2016) for terms Internet of Things, Wireless Sensor Networks, Ubiquitous Computing.

Table 1. Events Which Helped Shaping The IoT World. (Adapted from [POSTSCAPES])

Year Event

1967 Remotely Monitored Battlefield Sensor System (REMBASS)

1978 Aircraft Detection through Distributed Sensor Networks at Lincoln Labs

1993-1996 DARPA ISAT studies - Many Wireless Sensor Network ideas and its possible applications discussed. Deborah Estrin leads

one of the studies.

1994 Low Power Wireless Integrated Micro sensors (LWIM) - Bill Kaiser

1999 1999: The term Internet of Things (IoT) is introduced by K. Ashton, Executive Director of the Auto-ID Center in MIT (Massa chute Institute of Technology).

First time N. Gershenfeld share his ideas about IoT in his book entitled ―When Things Start to Think‖.

MIT Auto-ID Lab, originally founded by K. Ashton, D. Brock and S. Sharma .They introduced the Electronic Product Code (EPC), a global RFID-based item identification system intended to replace the UPC bar code.

2000 LG shared his idea and plans on internet refrigerator.

2002 The Ambient Orb created by David Rose and others in a spin-off from the MIT Media Lab is released into wild with NY

Times Magazine naming it as one of the Ideas of Year. The Orb monitors the Dow Jones, personal portfolios, weather and

other data sources and changes its color based on the dynamic parameters.

2003-2004 RFID is deployed on large number by the Department of Defense (US) in their Savi program and Wal-Mart in the

commercial world.

2005 The UN‘s International Telecommunications Union (ITU) published its first report on the IoT‘s topic. 2008 Identified by the EU and the First IoT European conference is held.

Group of companies launched the IPSO Alliance to encourage the use of IP in ―Smart Objects‖ networks and to enable the

IoT.


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2008-2009

The FCC voted to approve and launching the ‗white space‘ spectrum.

IoT was listed as one of the 6 ―Disruptive Civil Technologies‖ by US Intelligence Council, with Potential impacts on US

interests out to 2025.

According to Cisco‘s Business Solutions Group in 2008-2009, IoT was born.

2010 Chinese Premier Wen Jiabao calls IoT as a key for China industry and has plans to major investments in IoT industry.

2011 IPv6 public launch-The new protocol allows approximately for 2128 addresses to support IoT.

III. APPLICATION

IoT has the ability and can take the society to another level, where things can be very systematic and easy to operate from anytime or anywhere. IoT allows the device for making smart decisions and appropriate action without any human interaction. IoT concepts have been revealed in various domains ranging from transport, logistics, object tracking, agriculture, smart environment (home, office, city) to energy and defense.

According to Fleisch (2010), IoT is appropriate in every phase and everywhere. He considered 100 existence and emerging application that leveraging the IoT concept. He identified seven primary value drivers. Starting four applications are based on machine-to- machine communication (M2M) and rest of three based on user

participation.

1. Simplified manual proximity trigger: IoT nodes can

transmit their name or identity when they are in reach of

sensor range. As soon as the node is close, enough into

sensing space, a particular activity or transaction will be

triggered automatically.

2. Automatic proximity trigger: It triggered an automatic

action when the physical distance between two nodes

under below to some particular value (threshold).

3. Automatic sensor triggering: A smart device can collect

data through various types of sensors, including

brightness, temperature, smell, acceleration, vibration,

noise, chemical composition, humidity, and vision and

life signals. Devices sense these data and communicate

with the server and action will trigger based on pre-

program rules.

4. Automatic product security: A IoT nodes can provide

security based on the QR code, and its cyber

representation (Bind a specific URL corresponding to

every QR code).

5. Simple and direct user feedback: IoT nodes contain

simple mechanism and can give feedback to an

authenticate person present in the domain either in audio

format (small beep) or visual signal (flashlight).

6. Extensive user feedback: IoT nodes can offer a service to

the user (node is linked to a service through some

gateway device). Augmented service is an appropriate

example of this kind of application.

7. Mind changing feedback: The combination of virtual

world and the real world might be a reason of new levels

of change in the human behavior.

Fleisch's seven drivers can be suitable for real IoT

applications.

By integrating subsystem (smart home, smart city, and

transportation system) will form a smart environment that is

shown in Table 2 and their specification on technical

perspective is listed there. We identified some IoT application

and grouped them according to their domain in Table 3.

Table 2. Specification of IoT Applications

Smart office /

Home (Kidd et al., 1999)

Smart city (Murty et al., 2008)

Smart Forest/ Agriculture (Aun , 2000)

Smart Parking / Transportation (Lin et al.,

2005)

Network size Small Medium/Large Medium Small/Large

Users Very few Many/Policy maker/General Public

Few/Landowner General Public/ Many

Energy source Rechargeable battery Energy harvesting Energy harvesting Rechargeable battery/Energy harvesting

Communication Wi-Fi/3G/4G LTE Wi-Fi/3G/4G LTE Wi-Fi/ Satellite Wi-Fi/ Satellite

Data storage Local Server Shared Server Local Server/Shared Server

Shared Server

IoT device RFID/ WSN RFID/ WSN WSN RFID/WSN

Bandwidth Small Large Medium Medium/ Large


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Table 3. IoT Application Domains - Description and Examples.

Domain Description Examples

Industry Application on automation industry and commercial or financial transactions between companies and various organizations.

Publicsector, water infrastructure, manufacturing, logistic, transport, etc.

Enviorment Applications for monitoring, protection and efficient utilization of all natural resources.

Agriculture, forest, energy managment, enviormental managment servvices, recycling etc.

Society Activities regarding the development and serve better societies, nation, and peoples.

Government services towards society and citizens (e.g.,- Smart traffic control system, health monitoring system, smart city).

IV. CHALLENGES AND ISSUES

The heterogeneous nature in its network is rising different challenges with respect of security, resource availability and functionality. A safe IoT system must overcome to all challenges given in table 4.

A. Security and Privacy

In IoT, two major issues are the privacy (user related information) and security about the sensed data and business processes. The heterogeneity in IoT nodes, large scale of deployment, resource constraints, and their mobility make it harder to secure the network. There are a large number of techniques for ensuring the confidentiality. However, the primary task is to execute this algorithm faster to match the constraint of real time and should be less energy consuming. In addition, for making encryption technique secure, an efficient key distribution should be used. In the small-scale system, key distribution can be possible at the time of deployment, but at a large level, only novel key distribution schemes can be used for ensuring the privacy. Data anonymity can be a solution for privacy, but it is supported by equipment like high computation power and large bandwidth which is just contradict to IoT requirements (Miorandi, Sicari, De Pellegrini & Chlamtac 2012).

Security is a critical component for adopting the IoT at a global level, and without any guarantee, regarding authenticity, confidentiality, integrity and non-repudiation the related party is unlikely to adopt on a large scale. We will explore these key points in this section.

1. Availability

Availability is the consistency of every layer services of a network to the devices and makes sure the survivability of

network service even in the presence of attacks. IoT services will apply to commercial and real-time applications, so security in respect of availability should be on top.

2. Authenticity

A Process, where a user or node needs to prove their identity to use some services. Authentication is required to protect the system from impersonating nodes, which can breach the safety of the entire network. In IoT, many node support heterogeneous communication in a network, authentication is necessary to avoid illegal accesses.

3. Confidentiality

Data confidentiality is relevant to the business application, where an only authorized person can access or modify the data. In the context of IoT, data confidentiality addressing two important aspects: first is about the data access mechanism and a second are about object authentication processes. While data is transmitted, routing and encryption are precious to provide safety during communication.

4. Integrity

It provides an assurance that received data to the destination node should be original as sender sent, it should not be damaged or modified either from collision or through a third party (hacker).

5. Non-repudiation

Non-repudiation is an assurance that someone cannot deny to anything; as like source node send their data to the destination and should acknowledge the same. Non-repudiation is important to identify and some untrusted node can send the wrong information to some other nodes in a network and can deny, they never posted such information.

Table 4. IoT Challenges.

Interoperability Incorporate of security techniques in IoT network should not obstruct the functionality of the heterogeneous devices.

Fault tolerance The system should avoid even a single failure in the network, so infected node will not affect the entire system. Apart from that network must also avoid resource exhaustion attack against limited resource device.

Limitation of resource

Most of the IoT devices are restricted with respect to computation power, energy resources (battery operated), memory and bandwidth (linked to each other on low bandwidth). Therefore, it is tough to apply on internet security protocols directly in the context of IoT network. Hence, the standard security techniques need to redesign to full fill


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the requirement of IoT security with more efficient performance.

Availability The IoT devices must be functionally available when it is required. It is specifically vulnerable the Dos attacks such as message flooding to various nodes forced them to be unavailable in the network.

Scalability On internet million of devices existing and increasing continuously (Ericsson, 2011). The security, addressing protocols and required memory to store the generated information for each IoT device and s should able to scale when new devices introduce in the network.

Privacy protection

The popularity of sensors and RFID has increased the privacy concern because when the data are sensed and communicated, anyone can track these data and breach the identity or person (e.g., wearable device). In future, humans can connect their bodies to the internet by microchip implant in human bodies. Hence, health records must not be traceable and remain secure.

B. Energy

Many of IoT node runs on battery operated power and energy efficiency is most crucial for availability and proper functionality of the network. Energy efficiency in IoT sensor nodes is an active research area (Yoo, Wu, & Qiao, 2015; He, Chen, Yau & Sun, 2012). Most of it nodes are running on non-chargeable energy source and communication between heterogeneous nodes is more energy consuming. Deployment of complex security protocols in an IoT network can consume more energy, so it is advisable that in its network, we need a mechanism where a level of security can assign while considering the parameters like energy and probability of actual threads at a particular node.

C. Quality of Services (QoS)

While developing an IoT network, various challenges exist for a developer, one of them a quality of service (QoS) in respect of sensing data quality, resource consumption, data drop and so on. The QoS deal with all the parameters, which can directly or indirectly affect the reliability, performance and availability of the network. Considering some of the points (European Commission, 2014) under this category are:

Bandwidth, Capacity and Throughput

Trustworthiness

Latency

Resource Optimization and Cost Efficiency

Scalability

V. Related Work About IoT Protocols

In this section, we will discuss about various IoT protocols

and try to identify their benefits as well as limitations. The

discussion includes perception layer, network layer and

application layer protocols. Network layer functionality is

further divided into two parts.

A. IoT perception layer protocol

In this section, we will discuss different communication

protocols for IoT device. In IoT, all types of sensors, actuator

devices and communication technology or protocols between

them will reside in this category only. ZigBee and Bluetooth

are most commonly used in IoT network. In this layer, we will

discuss various protocol standards. On the other hand, IEEE

801.11ah can be used easily due to the existing and globally

spread infrastructure of IEEE 802.11 in a wireless application.

In some application, reliability is preferable hence; they use

Home Plug for LAN connectivity.

1. IEEE 802.15.4

IEEE 802.15.4 is most used standard in IoT for medium

access control. It includes device communication, a header

with source and destination address and frame format. The

traditional network frame format does not use in IoT network

due to their overhead so, in 2008 IEEE 802.15.4e was

introduced to upgrade IEEE 802.15.4 to support less power

energy. It is highly reliable because it uses channel hopping

and time synchronization method.

2. IEEE 802.11ah

IEEE 802.11ah runs on low energy and apart from that, it is

same as IEEE 802.11. IEEE 802.11 standard are not

appropriate for IoT due to high power requirements and frame

overhead, so it is a redesigned version of IEEE 802.11 to meet

IoT requirements with less overhead and less power

communication for motes and sensors. IEEE 802.11 (known

as Wi-Fi) is very popular wireless standard and mostly used in

Laptops, mobile phones, etc (Park, 2015).

Table 5. Protocol Stack for IoT Layer.

Application Layer

(MQTT, SMQT, DDS, XMPP, AMQP CoRE, CoAP )

Network Layer

Encapsulation

( 6LowPAN,

6TiSCH,6Lo, Thread...)

Routing

(RPL, CORPL, CARP…)

Perception Layer

(WiFi, Bluetooth, Zigbee smart, DECT/ ULE,

Weightless, Z-wave, DASH7, 3G/LTE, Home Plug GP,

LoRaWAN, LTE-A, G.9959, 802.11ah, 802.15.4e…)

3. Wireless HART

Wireless HART acquires time division multiple access

(TDMA) to accesses medium and operate on the top of IEEE

802.15.4 PHY. It uses advanced encryption techniques to


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encrypt data and maintain integrity, so it is a secure and

reliable protocol. This protocol ensures security source to

destination (End to End security mechanism) and peer-to peer

as well (Raza, & Voigt, 2010; Kim, Hekland, Petersen &

Doyle, 2008).

4. Z-Wave

This protocol comes under MAC protocol and very

popular for home automation. Its range up to 30-meter,

appropriate for a small message and low power protocol and

used for communication in smart home or office. Z-Wave

follows master-slave architecture and master control the entire

network and instructs the slaves through commands. It

acknowledges the message to ensure reliability and uses

CSMA/CA for collision detection (He, Chen, Yau, & Sun,

2012).

5. Bluetooth Low Energy

Bluetooth is used for short distance communication and

consume ten times less energy with 15 times more latency

than classical Bluetooth. It works on master-slave architecture

and uses two types of frame: data frame and adverting. Slaves

send the adverting frame on one or more dedicated link. The

master continues to sense these links, find them and connect

with slaves. Nodes are mostly in an inactive state to make an

efficient source of resource and awake only when they

communicate with each other (Decuir, 2010; Hasan, Hossain,

& Niyato, 2013).

6. Zigbee Smart Energy

Zigbee supports a large range of communication and can

be used in a healthcare system, remote controls or in smart

office. It supports different network topologies like peer to

peer, star, tree soon. ZigBee standards divide in two profiles:

ZigBee and ZigBee Pro. ZigBee. These protocols work with

different applications and support implementation with low

computational power and memory. ZigBee Pro includes more

features like efficiency through many to one routing

techniques, security through symmetric key exchange and

scalability (ZigBee Standards Organization, 2008).

7. DASH7

It is wireless communication protocol and for RFID and

employ globally on ISM Band (Industrial, scientific and

medical) and appropriate for IoT applications. It supports high

range, scalable and offers higher data rate than ZigBee. It is

designed to support lightweight, low cost to support

encryption and follow IPv6 addressing (LoRa Alliance, 2015).

8. HomePlug

Homeplug is a MAC protocol and used in a home

automation system. It comes in three versions: Home plug-

AV, HomePlug AV2, and HomePlugGP. HomePlugGp is a

redesigned version of HomePlugAv for ensuring low power

and cost; it is specially designed for its applications (smart

home). HomePlugGp uses Orthogonal Frequency Division

coding Multiplexing (OFDM) coding for reliable

communication. HomePlugGP use CDMA and TDMA

techniques for medium accesses while HomePlugAV used

only CSMA as a MAC protocol. HomePlugGP synchronizes

the sleeping time and wakes up only when in requires, so it

operates on less power than HomePlug9) G.9959 (HomePlug

Alliance, 2012).

9. Long Term Evolution-Advances (LTE-A)

Long Term Evolution Advances (LTE-A) is a set of

standards, introduced for communication between M2M

(machine to machine) or IoT devices in a cellular network.

Compared to other cellular protocols, LTE supports scalability

and low power. LTE-A divide the frequency into independent

band and can them separately (Orthogonal Frequency Division

Multiple Access). LTE-A architecture consists of a Core

network- responsible for to track IPs and to control the mobile

nodes; 2nd one is Radio accesses network to deal with access

control, wireless connectivity, and data plan and the last one is

mobile nodes (Hasan, Hossain, & Niyato, 2013).

10. LoRaWAN

LoRaWAN is a new and emerging wireless technology,

with low energy, low cost, secures and supports full duplex

communication. It is designed to support large or scalable with

million numbers of devices. It supports the future needs of IoT

like energy harvesting, mobility, operated at low power and

redundant operation (LoRa Alliance, 2015).

11. Weightless

It is a wireless area network technology and designed by

Special Interest Group (SIG) -Nonprofit organization. It

supports two standards Weightless-N and Weightless-w.

Weightless introduced earlier, support low cost and consumed

less energy and communicating between machine to machine

using TDM access. Weightless- W offers above features too,

but uses only television band frequencies (Poole, 2014).

12. Digital Enhanced Cordless Telecommunications (DECT)

/ Ultra Low Energy (ULE)

It is the European standard for cordless phones. Digital

Enhanced Cordless Telecommunications (DECT) / Ultra Low

Energy (ULE) is an improved version of DECT. It operates on

low power and less cost air interface technique so it can be use


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Table 6. Perception Layer Protocols Comparison

in IoT applications. It communicates through the dedicated

channel, so it is free from congestion. DECT/ULE uses

FDMA and TDMA, which were not supported by DECT

(Bush, 2015).

B. IoT Network layer protocol

We divide the network layer functionality into two parts:

Routing and Encapsulation. In this section, we will discuss

various routing and encapsulation protocols.

1. IoT Network layer Routing protocol

In this section, we will discuss IoT routing protocol, which

is responsible for delivering the packets from source to target

device.

a. Routing Protocol (RPL)

RPL (Routing Protocol) is a distance vector routing

protocol that can support various communication protocols,

which we discuss in an upper section of perception layer. It

constructs Destination-oriented direct acyclic graph (DODAG)

that has one and unique route from the root to all leaf nodes.

Firstly, each node advertises him as a root node by sending an

advertisement message. This message will spread in a

network, and the entire DODAG will slowly build. When

communicating, root sends a DAO (Destination

Advertisement Object) to its parents, like this it's will

propagate to root, and root will decide according to the

destination address that's where it has to send. When any new

node wants to join a network, it will request, through the

DODAG Information Solicitation (DIS), and root gives

acknowledge through DAO Acknowledgment (DAO-ACK).

RPL node can be stateless and stateful, the stateful node used

commonly and node keeps track of parents only. Root has

complete knowledge of entire DODAG so communication will

go through root only. Stateful node keeps information about

the parents as well as children where communication will go

through it does not need to go through the root (Winter, 2012).

b. Cognitive RPL (CORPL)

CORPL (Cognitive RPL) is an extension of RPL protocol,

used DODAG topology and designed for the cognitive

network. CORPL comes with two modifications of RPL that is

it forwards the packet to best hope by choosing multiple

forwarders from forwarder set. Each node maintains their

forwarder set in place of its parent and use DIO message to

update their neighbors when there is any change. Each node

changes neighbor‘s priorities corresponding these updates to

create forwarder set (Aijaz, & Aghvami, 2015).

c. Content-aware routing protocol (CARP)

CARP (Content-aware routing protocol) is used in underwater

communication, and it considers link reliability based on the

successful communication by neighbor sensor history. It is a

distributed routing protocol and uses a lightweight packet

mechanism so that we can use in IoT application. It works

based on two scenarios: network initialization and data

forwarding. In first scenario: hello message will broadcast

from the source to each available node in a network. In second

scenario: packet will be routed in the network hop by hop.

Each hop identifies independently. The main drawbacks with

the CARP protocol are that it does not maintain the previously

sensed data means if there is significant change is sensor data

and if an application requires the previous one, in this kind of

situation CARP is not applicable. E-CARP is an extended

version of CARP with allowing to node save the previous data

(Zhou, Yao, Xing, Shu, & Bu, 2015).

Protocol Energy Efficient

Reliability Remark: Techniques for ensuring the reliability

IEEE 802.15.4 High High Channel hopping, time synchronization

IEEE 802.11 AH

High Less

Wireless HART

Less High Advance encryption

Z-Wave High High Acknowledge system, CSMA/CD

Bluetooth Low Energy

Very High High Encryption

Zigbee Smart Energy

High High Symmetric key

DASH7 High Average Encryption

HomePlug High High OFDM

LTE-A High Less

LoRaWAN Very High High Acknowledgement, time-synchronization mechanisms at regular fixed intervals

Weightless High Less

DECT/ULE High High Congestion free


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2. Network Layer Encapsulation Protocols

Ericsson (2011) estimated that up to 2020 there will be 50

billion devices on the Internet, so to support the unique

addressing mechanism IPV6 protocol is used on its network.

Now one problem is that, IoT data link frame format relatively

small to store IPV6 addresses. Therefore, to handle this kind

of situation IETF (Internet Engineering Task Force) working

on a set of standards to enclose the IPV6 datagram‘s into IoT

data link layer frames. In this section, we will discuss this

mechanism in brief.

Table 7. Network Layer Routing Protocols Comparison.

Protocols Energy Efficient

Security

RPL

CORPL

CARP

a. 6LoWPAN

IPv6 over low power wireless area network (6LoWPAN) is

most popular protocol under this category. It encapsulates long

header of IPv6 protocol in IEEE 802.15.4 packets which

maximum size is 128 bytes. This standard introduces

compression techniques to decrease transmission overhead,

support multi hop delivery and fragmentation support to

maintain maximum frame size of 128 bytes. Four types of

header supported by 6LoWPAN frame: 6LoWPAN, mess,

fragment and dispatcher header. If any frame does not follow

specialization of 6LoWPAN network, then it will reject. Mess

is used for broadcasting, the fragment is used to break the

large IPv6 header to fit into 128-byte size and dispatcher is

used for multicast and compression over IPv6 header (Jain,

2015).

b. 6TiSCH

It is a working group of Internet Engineering Task Force

(IETF) developing a mechanism to distribute channel in

TSCH (Time-Slotted Channel Hopping) mode. It consists a

matrix where column represents the available frequencies and

rows available time slots for network scheduling and the

channel will be distributed according to this matrix. The

matrix is partitioned into many chunks and known to all nodes

in a network. There is a possibility that some nodes can have

the same parameters, so to avoid this kind of situation node

will negotiate so that each node will get a chance. This

standard will not specify the scheduling techniques, so

according to application requirements allow maximum

flexibility to IoT application. The scheduling can be

distributed or centralized depending on topology or

application (Dujovne, Watteyne, Vilajosana, & Thubert,

2014).

c. IPv6 over G.9959

G.9959 supports a frame format, where 32 bits reserved for

the network identifier (home network) that is given by a

controller and 8 bit for node identifier that is assigned to each

node. RFC 7428 introduce a frame format to transmit IPv6

packet over G.9959 packet, and support a level of security

through shared key mechanism for encryption, but some

applications required end-to-end encryption mechanism for

maintaining the high level of security.

d. IPv6 over Bluetooth Low Energy

The Bluetooth Special Interest Group (BSIG) in Bluetooth

v4.0 and an enhanced version in v4.1 introduced Bluetooth

low energy. It is a radio technology, which is run on low

power, such as battery power and it, attracts IoT applications

such as environmental sensing, health monitoring, etc.

Bluetooth LE using the same compression method as

6LowPAN and fragmentation feature is different from a

6LowPAN standard. It is achieved through sub layer L2CAP

(Logical Link Control and Adaptation Protocol) which

reassemble the large payload packet into 27 bytes. Bluetooth

LE can use over small messages with low power (Nieminen,

Savolainen, Isomaki, Patil, Shelby & Gomez, 2015).

Table 8. Network Layer Encapsulation Protocols Comparison

Protocol Energy Efficient Security

6LoWPAN

6TiSCH

IPv6 over G.9959

IPv6 over Bluetooth

Low Energy

C. IoT application Layer Protocols

In this section, we briefly highlighted many standard

application protocols. Application layer protocols are

dependent on application type and specifications. In Table-6

we summarize comparison points between these application

layer protocols.

1. Message Queue Telemetry Transport (MQTT)

Message Queue Telemetry Transport (MQTT) was

constructed by IBM in 1999 and standardized in 2013 by

OASIS (Locke, 2010; Karagiannis, Chatzimisios, Vazquez-

Gallego, & Alonso-Zarate, 2015). The architecture of MQTT

organized into three components: publisher, broker (queue)

and subscriber. The publisher is lightweight sensors from IoT

point of view that connects to a broker; broker is a queue

system where publisher sends their sensed data and go back to

sleep. Subscribers are IoT applications; they are interested in

sensed data, so they in contact with a broker when new data

are received. Brokers categorized the data in topics and

delivered to the subscriber according to interesting topics.

2. Secure-MQTT (SMQTT)

An improved version of MQTT is Secure-MQTT (SMQTT),

which used an encryption technique based on a light attribute.

The main advantage of SMQTT is broadcast encryption

feature where one encrypts a message to send to multiple

destinations, so it is a required function for IoT application.

The algorithm work in four stages: setup, encryption, publish

and decryption. The publisher and subscriber registered them


53

self to broker in the setup phase and get a key from the

developer of an application according to required security

level. When new data are formed, it is encrypted, published

and send them to a subscriber by a broker. The encryption

algorithm and set of keys are not standardized; SMQTT is

introduced just to add the security feature in MQTT (Singh,

Rajan, Shivraj, & Balamuralidhar, 2015).

3. Advance Message Queue Protocol (AMQP)

The Advance Message Queue Protocol (AMQP) is a session

layer protocol, which in introduced for financial applications.

It follows the same architecture (Publisher/subscriber) as

MQTT and runs over TCP/IP protocol. In AMQP, broker

functionality is divided into two parts: exchange and queue.

The exchange processes the publisher message and organizes

them into a queue according to roles and condition, which is

predefined into the queue. Queues corresponding to the

subscriber and the topics, whenever the data available in the

queue then will get (OASIS, 2012).

4. Constrained Application Protocol (CoAP)

The Constrained Application Protocol (CoAP) is developed by

the IETF working group to provide a lightweight interface. It

is an application-layer protocol. REST (representational state

transfer protocol) is a standard interface work between HTTP

client and interface. As compared to light it application

requirements, REST consumes more power and significantly

overhead. The CoAP is introduced to match the IoT

requirements such as low power overhead to operate sensors.

CoAP architecture, functionality divided into two layers:

messaging and request/response. The first sub layer is ensured

the reliability and deal with the duplicity of the packet and

request/response sub layer for communication. CoAP has four

messaging nodes - conformable, non-confirmable, piggyback

and separate. Reliable and unreliable transmission represent

by confirmable and unconformable modes respectively, while

piggyback used in the client / server model, where the server

get a message sends the response directly with acknowledged

the message. On the other side, the separate mode will use

when server response within the message separate from the

acknowledgment (Karagiannis, Chatzimisios, Vazquez-

Gallego & Alonso-Zarate 2015; Shelby, Hartke, & Bormann,

2014).

5. Extensible Messaging and Presence Protocol (XMPP)

XMPP was introduced for chatting and message exchange

purpose and standardized by IETF many years ago. It is a

standard and efficient protocol over the internet. Now, it is

reusing the same standards because of its use XML, which

make it easily extensible. It is a very efficient protocol over

the internet and has been raised over the IoT application.

XMPP can work on request/response, or publisher/subscriber

architecture and developer can choose according to the

development application. It is developed for near real-time

application and provides efficient support for a small message.

It does not provide any support for QoS. Therefore, it does not

take place in M2M communication. Furthermore, XML

involves a lot of tag format and headers, which cause for more

power consumption. So, it is rarely used in IoT applications

(Karagiannis, Chatzimisios, Vazquez-Gallego & Alonso-

Zarate, 2015; Saint-Andre, 2011).

Table 9. Application Layer Protocols Comparison.

Protocols Security QoS

MQTT

AMQP

CoAP

XMPP

DDS

V. COMPAIRSION AND CLASSIFICATION OF IOT RELATED

SECURITY ATTACKS

In this section, existing IoT related security work analyzed

and categorized into two types: techniques that work on

asymmetric key schemes and symmetric pre-distribution

schemes. These techniques are isolated from standard IoT

protocols, which are covered in the above section. In figure 5

taxonomy of security techniques according to cryptography

schemes.

In table 10, we compare all these security techniques by

considering the various attributes: energy, latency, complexity

and bandwidth utilization. We use simple notations to

compare the security techniques: ‗‘– supported, ‗blank

means‘ – not applicable or not comparable and ‗’ not

supported.

In table 11 we consider six metrics to evaluate the

solutions: Privacy, Authentication, Confidentiality, Denial-of-

service (DOS), Integrity and end-to-end (E2E) Security. We

define simple notations to evaluate the security services: ‗ ‗–

supported, ‗blank means‘ – not supported.

VI. RESEARCH CHALLENGES

The concept of IoT has been extended to various domains of real life in order to solve various problems. It can be viewed as a combination of heterogeneous devices, sensor, actuator, etc. communicating with each other without very less human intervention and providing meaningful information to control and monitor situation for example: Patient monitoring, energy management , and traffic monitoring System. The applications of IoT can be constrained by resource limitation such as less computation power, limited energy, limited bandwidth, limited memory etc. Apart from above, challenges the applications developed using IoT concept are prone to security and privacy attack. The computing nodes/sensors are deployed in open environment and their communication is limited but vulnerable to attack. Further, the sensed data is collected at one key node and forwarded for analysis and monitoring purpose. This involves use of Internet quite often. So, in view of above scenarios a security framework or model for IoT application is desirable, where it has to be ensured that privacy and security of data cannot be compromised.


54

As mostly IoT applications are Real time and Energy constrained, the challenge to provide security to applications needs a balancing approach. The strategy for providing security should be adaptive in nature which changes according to the applications parameter such as energy, Timeliness, attack level, security level, Load in the system etc.

In IoT, standard is an important part. The standard development process and protocol should be open accesses to all, so that when new devices will introduce in network, existing standard can be modified to support new object and application. In today‗s network paradigm, global standards are typically more applicable than any local agreements.

Therefore, it becomes an open and viable area of research and effort is required to develop a comprehensive security aware framework where the security level can be flexible and it is decided only after analyzing the network nodes parameters: Energy, Computation power, Attack level, Security level such that QoS feature of things and node-integrated network can be ensured.

VII. CONCLUSIONS

The objective of this survey is to present an explicit analysis of the traditional IoT security protocols, modified techniques, their approach and possible challenges over various attacks. There are numerous issues in IoT, such as user privacy, authentication, data confidentiality, DOS, integrity and end-to-end (E2E) security across network that must be resolve by IoT security techniques. Still, there are multiple security threats, which will be place in the Future IoT. Additionally, In IoT networks most of the devices are resource restricted and it is not only recommended to assure the security in network, but also to implement efficient techniques which balancing the requirements like computation power, energy, and QoS features of things and network, so that these techniques can be applicable to the real world scenarios.

This survey paper also provides a classification of existing security techniques and protocols relying on their key-based cryptography approach for assuring reliability in the IoT network. These techniques and protocols are examine for identify their advantages and limitation over energy and QoS features. Apart from that, this article also identify some research challenges for Future IoT so that organizations and researchers should tackle these problem and further research can be carried out in this direction.


55

Figure 5 Taxonomy of cryptography key classification.

Classification of cryptographic keys

Asymmetric key

schemes

Symmetric key

predistribution scheme

Raw public key

encryption

Server assist

key distribution Certification

based encryption

Offline key

distribution Identity based

encryption

External

assisted

server

Deterministic key

distribution Probabilistic key

distribution

Key agreement

based on asymmetric

techniques

Key transport based on public

key encryption

(Sarikaya

et al.,

2012)

Proxy-

based assisted

server

IoT (Raza

et al.,

2013) (Hummen

et al.,

2013)

(Szczechow

iak et al.,

2009) (Yang et al.,

2013)

(Nicanfar et

al., 2011)

(Yang et al.,

2013)

(Meulenaer

et al., 2008) (Moskowitz

,2012)(Gos

wami et al.,

2014)

(Du et al.,

2006; Blom

et al., 1984)

(Raza et al.,

2011)

(Saied et

al., 2012)

(Hussen et

al., 2013) (Vucinic

et al.,

2015)

(Bhattacha

ryya et al.,

2015)

(Eschen

auer et

al.,

2012)


56

Table 10. Summary of Proposed Security work and their key Techniques for IoT.

Protocol/References Briefdescription Energy Efficient

Latency

Complexity

B.W. utilization

Security Bootstrapping Solutions for Resource-Constrained Devices( Sarikaya et al., 2012)

This document give an idea how to securely configure the resource constrained device networks at initial stage and bootstrapping architecture, security methods and communication channel are described.

Less

A lattice based authentication for low-cost RFID (Moustaine et al., 2012)

Author proposes an NTRU based schemefor RFID tag (low-cost), and a lightweight mutual authentication protocol based on this NTRU‘s adaptation. This solution covers the security and privacy related requirements for RFID systems. Less

Lightweight secure CoAPs for the IoT: Lithe (Raza et al., 2013)

Author present Lightweight Secure CoAP for the IoT (Lithe) — a combination of DTLS and CoAP for the IoT. With Lithe, additionally give a novel DTLS header compression scheme that motive to decrease the energy consumption by leveraging the 6LoWPAN standard. DTLS header compression scheme does not compromise the end-to-end security properties. Simultaneously, it greatly reduces the number of data bytes while maintaining DTLS standard compliance.

Certificate-based authentication for the IoT (Hummen et al., 2013)

Author proposes these methods to decrease the overheads of the DTLS handshake. These methodss are based on pre-validation, handshake delegation and session resumption. High

Establishment of ECC-based initial secrecy usable for IKE implementation (Ray et al., 2012)

Author proposes a new flexible approach for reduce the complexity and security improvement of the IKE implementation. Less

Identity-based encryption for heterogeneous sensor networks: TinyIBE (Szczechowiak et al., 2009)

Author present an efficient security bootstrapping mechanism for heterogeneous Sensor Networks that base on Identity-Based Encryption and exploits the enhanced capabilities of high-end cluster heads. Propose asymmetric security scheme provides authenticated key distribution without using expensive certificates.

Less

Authenticated Pair wise Key using Pairing-based Cryptography (Yang et al., 2013)

This technique stand on the elliptic curve Diffie-Hellman (ECDH). It can effectively protect from various attacks: man-in-the-middle attacks and node-capture attacks through encrypting the exchanged parameters using identity-based encryption.

Less

Elliptic Curve Diffie-Hellman - Elliptic Curve Digital Signature Algorithm (ECDH-ECDSA) (Meulenaeret al., 2008)

Author verify the energy cost of cryptographic protocols, both from a computation point and a communication of view, based on practical measurements on the MICAz and TelosB sensors. Author focus on the cost of two key agreement protocols: Kerberos and the Elliptic Curve Diffie-Hellman key exchange with authentication provided by the Elliptic Curve Digital Signature Algorithm (ECDH-ECDSA).

HIP Diet EXchange (DEX) (Moskowitz, 2012)

HIP is introduced to provide secure authentication of hosts. HIP also explore to limit the exposure of the host to various attacks denial-of-service and man-in-the-middle (MitM).


57

A Key-Management Scheme for Distributed Sensor Networks (Eschenauer et al., 2002)

Author presents a key-management scheme designed to satisfy both operational and security requirements of DSNs. The scheme includes selective distribution and revocation of keys to sensor nodes as well as node re-keying without substantial computation and communication capabilities. It relies on probabilistic key sharing among the nodes of a random graph and uses simple protocols for shared-key discovery and path-key establishment, and for key revocation, re-keying, and incremental addition of nodes.

A key predistribution scheme for sensor networks using deployment knowledge (Du et al., 2006)

Author propose a novel random key pre-distribution scheme that exploits deployment knowledge and avoids unnecessary key assignments and the performance including memory usage, connectivity and network resilience against node capture of sensor networks can be substantially improved with the use of our proposed scheme.

An Optimaal Class of Symmetric Key Generation Systmes

The purpose of this paper is to provide a class of SKGS for which the amount of secret information needed by each user to generate his keys is the least possible while at the same time a certain minimum number of users have to cooperate to resolve the uncertainty of unknown keys.

High

D-HIP: a distributed key exchange scheme for HIP-based IoT (Saied et al., 2012)

Author proposes a distributed lightweight key exchange protocol designed to reduce the requirements of HIP Base Exchange, in order to be supported by resource-constrained nodes.

SAKES: secure authentication and key establishment scheme (Hussen et al., 2013)

Author propose Secure Authentication and Key Establishment (SAKES) scheme for the machine-to-machine (M2M) communication in the 6LoWPAN. SAKES light weight public key during the session establishment processes and pair wise key for node authentication.

Less

BROSK (Lai et al., 2002) BROSK protocol: To make link dependent keys by broadcasting key negotiation messages

An Measurement Transmission Scheme for Privacy Protection (Li et al., 2013)

Author proposed a Ring Communication Architecture (RCA). This technique which assure customers‘ privacy by using the ortho code.

Energy-efficient physical layer packet authenticator (Bartoli et al., 2013)

In this method, verification test will conduct at Physical layer to challenge exhaustion DoS attacks and this technique is able to reject non-intended packets without the need to their total reception.

Lightweight Establishment of Secure Session (Bhattacharyya, et al., 2015)

This is a novel lightweight cross layer approach for session establishment and interchange of application layer message through a secure channel.

Object security architecture (Vucinic et al., 2015)

OSCAR: Architecture provides End-to-End security in IoT network and work on the concept of object security and relates security with the application payload.

Securing communication in 6LoWPAN with compressed IPSec (Raza et al.,

This technique offer secure communication (End-to-End) between the internet and IP enabled sensor network in 6LoWPANs.


58

2011)

Securing Intra-Communication in 6LoWPAN: A PKI Integrated Scheme (Goswami et al., 2014)

A public key infrastructure (PKI) enabled scheme with database system, which contains the required keying information about all the network nodes.

Smart Grid Authentication Scheme (SGAS-I) Authentication and Smart Grid Key Management (SGKM-I) for Unicast and Multicast Communications (Nicanfar et al., 2011)

A novel key management and mutual authentication protocol for establish a link between the utility server and customers smart meters so that communication can take place. This protocol secure from various attacks like Brute-force, DoS and Man-In-The-Middle Replay attacks.

low High

Table 11. Summary of Proposed Security Methods for IoT.

Author Privacy

Authentication Confidentiality DOS

Integrity E2E Security

(Sarikaya et al., 2012)

(Moustaine et al., 2012)

(Hummen et al., 2013)

(Raza et al., 2013)

(Ray et al., 2012)

(Szczechowiak et al., 2012)

(Yang et al., 2013)

(De Meulenaer et al., 2008)

(Moskowitz et al., 2012)

(Eschenauer et al ., 2002)

(Du et al., 2006)

(Du et al., 2006 ; Blom et al., 1984)

(Saied et al., 2012)

(Hussen et al., 2013)

(Lai et al., 2002)

(Li et al., 2013)

(Bartoli et al., 2013)

(Vucinic et al., 2015)

(Raza et al ., 2011)

(Goswami et al., 2014)

(Nicanfar et al. 2011)


59

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