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Network security analysis of Internet Of Things using Quantum Key Distribution

Sayantan Gupta

 University of Engineering & Management

Kolkata, India

[email protected]

Sucheta Nag

University of Engineering & Management

Kolkata, India

[email protected]

Abstract' The paper defines the various problems in Internet of Things and the analytical solutions have been proposed using Quantum Key Distribution and other methods.

Keywords'Internet Of Things; Network analysis; Quantum Key Distribution; IoT network architechture )

I. INTRODUCTION

Internet Of Things have been the most advanced and chronological evolution in mankind. Basically IoT is a network of a good number of devices rather physical devices connected together. These devices are embedded with electronic circuits, Sensors and software. The IoT has its own network architecture which allows the device to connect to a network of devices and transmit, collect or exchange data over the network architecture. According to a survey conducted recently 40% of the people say that the issue with security is a major concern in our technology.  

Quantum key distribution architecture uses quantum mechanics to ensure secure communication in the network.

Why QKD in IoT?

The best feature in Quantum Key Distribution is the ability of the body to detect and response the presence of any third party or Eve in the arch. Of the  system. The consideration and management of key or variable that uses quantum key distribution depends upon the layers of quantum theory, in deep difference to old public key cryptography, which depends upon the transfer of key by mathematical functions and complex formulas, and cannot provide any indication or detection  of eavesdropping at any point in the entire referral process.

The problem with Internet Of Things is that the network architecture can be easily cracked with. For example- Artificially-controlled devices in cars such as brakes, horn have been very much available to attackers who have access to the various system architecture and in some cases, the vehicle systems are inter-connected, which allows them to be exploited externally by the attackers trying to enter the system.

Likewise to solve the detected issues we will use Quantum Key Distribution over the IoT networks.

In this paper we will propose protocols of QKD to be implemented over Internet of Things and we will suggest other effective measures to overcome the security challenges of IoT.

II. MAJOR CHALLENGES

When the devices are reverse engineered and vulnerabilities are discovered and exploited, the vulnerabilities will need to be patched as quickly as possible. Code obfuscation and code encryption can considerably slow down the reverse engineering process, and deter the majority of attackers, but not entirely prevent reverse engineering. Attackers with nation-state levels of resources, or the resources of sophisticated transnational malicious organizations, may still be able to reverse engineer programs including programs protected through obfuscation and encryption, particularly since code must be decrypted to run.

IoT devices face many threats, including malicious data that can be sent over authenticated connections, exploiting vulnerabilities and/or misconfigurations. Such attacks frequently exploit many weaknesses, including but not limited to (a) failure to use code signature verification and secure boot, and (b) poorly implemented verification models which can be bypassed. Attackers often use those weaknesses to install backdoors, sniffers, data collection software, file transfer capabilities to extract sensitive information from the system, and sometimes even command & control (C&C) infrastructure to manipulate system behaviour. Even more disturbingly, some malicious data attacks can exploit vulnerabilities to install malicious software directly into the running memory of 'already running' IoT systems in ways that the malware disappears on re-boot, but does tremendous damage between reboots. This is particularly scary as some IoT systems, and many industrial systems, are almost never rebooted. Sometimes such attacks come through an IT network connected to an industrial or IoT network. Other times, the attack comes over the Internet, or through direct physical access to the device. Of course, regardless of the initial infection vector, if not detected, the first compromised device remains trusted and then becomes the avenue for infecting the rest of the network, regardless of whether the target is the 'in car' network of a vehicle, or a plant-wide operational network of a manufacturing plant. For such reasons, IoT security must be comprehensive. Closing a window but leaving a door open, 'isn't adequate.' All of the infection vectors must be mitigated.

A. Mutual Authentication

Mutual Authentication is an important and critical aspect to ensure the identification of communicating devices involved in communication or the exchange of data. If the authentication network not strong to encrypt or decrypt data securely then a big loophole is created threatening the entire system. Most systems which bind IoT sensors and actuators rely on some proxy concept, i.e. sensors communicate to some more powerful entity (e.g. from the processing and storage point of view) which then authenticates the sensors on their behalf. However, the last mile effectively remains unprotected which is a barrier to guaranteeing important security properties such as non-repudiation.

B. Maintaining the Integrity of the Network

In powering up, each device boots and runs some code. In that context, it is crucial that we ensure devices only do what we programmed them to do, and ensure that others cannot reprogram them to behave maliciously. In other words, the first step in protecting a device is to protect the code to be sure the device only boots and runs code that you want it running. Integrity is the debit to make sure that the data is protected from unauthenticated and unwanted change and the information is available to the valuable and valid party when it requires.

C. Confidentiality

 Confidentiality is the major concerns from

the evolution of smart objects in the architecture network of IoT system and there is no visible path line to transmit or receive the data, so it uses the medium interface. Therefore, we have to make sure that the information which gets transmitted is hidden from unauthenticated access and so it is very important to perfect guide the security system to help in our use.

D. Attacks on the system

Various attacks like false routing, message tampering, unauthorized usage, eavesdropping, DOS attack are common to any network system like Internet. But there are some issues which may be a vital concern in IOT but not in current Internet system architecture. Like take the example, nowadays the devices are easier to access physically or remotely in IOT, then physical abruption, secret extraction. tampering of nodes are very much serious as we are unaware in this subject.

III. SOLUTIONS USING COW PROTOCOL

The performance of a QKD system can be found by the  formula Q= Xv, here in this formula X is the surfed or changed bit rate and v stands for the denoted  key fraction. Now if we look at certain conditions, X is directly proportional to the certain rate of the source  and the  number of photons per second (c). Now if we increase  the rate (or c) we will find that X also increases simultaneously. Pulse rates greater than 1.23GHz and up to 11GHz, though only over a fraction of a milli second or even seconds. However, v depends on the available information of an eave trying to get access to the system and in the case of district laser systems, which are vulnerable and easily open tom(PNS) attacks, depends on c. The implementation of district laser schemes, like 'Differential Phase Shift' (DPS)6 or SARG7, or decoy states, which are immune to various kind of attacks like that of PNS, which allows one to increase c and thus, the max covered distance and secret bit rate. Finally, the quantum bit error rate (QBER) is dependent on the difference between the machine noise and data transfer loss. So, the system noise limits the max transferred distance, hence the focus is in low noise creating detectors.

So we assume a QKD prototype which is relied on a PNS proof algorithm known as coherent 1-way (COW) that has usage of very high increasing pulse variants with non-stopping operations occurred with little-running, less noise detectors. In this type of algorithm, the represented bits are encoded and as well as decoded in space-time variation. A detailed line of very weak, distorted and abused coherent pulsed radiation is put forward by a F-laser gun with a variable intensity checker.

The following are the dimensions of the research protocol application:

    SECURITY ANALYSIS

The COW system algorithm does not apply instruction by instruction or symbol by symbol type of structure  unlike the other QKD algorithms & the available security solutions system can't be applied any way. The protocol thus inscribed is also known as distributed-phase-reference algorithm, just like DPS, which basically depends upon the coherence between proper non-valid pulses to entrust  the security analysis of the system.

Now since the process of starting the operation of the initial system, the main key K is located and relied only in the Key Dist. and location system, thus it becomes very difficult for a system or Eve to generate or recopy the right private key which is used by the developer, considering the fact that the Eve could trace all the correct information from the system for its use. The data and the info gained in this purpose cannot be disrupted. This holds the integrity of the data. Hence it is not possible to detect or evaluate secret information from the algorithm without accessing the system's secret hidden key K. It preserves the privacy and security at the user end. In the time of mutual authentication, the various devices and systems are validated mutually among themselves and creates a brand new key Ks which ensures the mutual transmissivity of the system. Since the encrypted message-signals are transferred to the algorithm in raw form confidentiality is thus not a concern for this cause.

A. ADVANTAGES USING THE COW PROTOCOL IN IoT

' By using this algorithm the main advantage is that the  ending of the different cryptographic proceedings that are assumed and proved to be impossible by implementing the use of only primitive ways (that is- non-quantum)processes. Let us consider the fact that, non-Newtonian mechanics ensures us that calculation of such data disrupts that secret data which is prevailed; which is to be utilized to detect the presense of any dropping in the system network and can thus stabilize/handle the system.

' The integrity of the raw information is maintained. The information and data is only and only access able to valid users for communication.

' The COW network will allow us to gain more security to open IoT networks which will act as a major advantage.

IV. SOLUTION USING ECC PROTOCOL

 In 19th century Neil Kobiltz and Victor Miller developed public key cryptosystem elliptic curve cryptography. It is like RSA public key cryptography. The difficulty of Elliptic Curve Discrete Logarithm Problem (ECDLP) determines the strength of security provided by ECC. ECC requires scalar multiplication, which incorporates point doubling and adding operation which is computationally more efficient than RSA exponentiation. ECC being complex makes it difficult for the hacker to understand ECC and hence to decipher the security key. The security level given by RSA with 1024 bit key can be achieved with 160 bit key by ECC. Hence it is well suited for devices like smart cards, mobile devices.

A. Why use Elliptic curve cryptography?

The advancement of IoT has led to technical advantages and business opportunities but it equally threatened by attackers. Because the information is not encoded and the privacy of the information is not guaranteed and also the senders and the receivers are not authenticated via secure connections. The advantages of ECC protocol are:

1) Elliptic curve cryptography is a newer and better method based on algebraic structure of elliptic curves over finite fields and considered as an efficient technique which requires lower key size for the user. The attacker has an exponential time challenge to break into the system. In ECC a 160 bit key gives the same security as RSA with 1024 bit key. It requires only less memory space and lower computation. The advantage of the ECC is the absence of the sub exponential time algorithms and uses minimum key size and provides more security.

2) ECC is used in devices which has less storage memory especially in smart cards such as  bank cards, electronic tickets, personal identification cards, etc. Most of the manufacturing companies are producing smart card that make use of elliptic curve digital signature algorithms.

3) Wireless communication uses ECC and it is used in devices with less computing power and resources as well. The most suitable platform to implement ECC are constrained devices. With smaller key size the execution is favourable to systems where real time performance is an important factor.

B. Security Analysis

The security of ECC depends on the difficulty of Elliptic Curve Discrete Logarithm Problem (ECDLP). In the notation A=kB, A and B belong to Ez(a.b) and k is less than z i.e. k<z. In this if k and B are given, then it is easy to calculate.But if A and B are given it is relatively hard to determine k, if k is sufficiently large. k is the discrete logarithm of A to the base B. This is the discrete logarithm problem for ECC. Due to the complexity of  DLP ECC is hard to break. The main operation involved in ECC is point multiplication.

An elliptic curve E is described as y2=x3+ax+b. The degree of this equation is 3. In order to perform higher order encryption and decryption the equation should satisfy the standards proposed by NIST. In the proposed model ECC encrypts the plain text (M) into cipher text (C) and vice versa by using the finite set of points in the elliptic curve over GF(z). The Weier Strass equation y2=x3+ax+b is used with modulo p to generate the points on the elliptic curve. The elliptic curve domain parameters are p, a, b, G, N, h, r where 'p' is a prime number, 'a' and 'b' are coefficients, 'G' is a generator point, 'N' is the cryptographic prime factor, 'h' is the cofactor and 'r' is the random integer less than 'N'. According to NIST the prime p should be greater than 2160. For illustration, the proposed system uses the finite field elliptic curve with modulo 307. The coefficients 'a' and 'b' are assigned '1'. Hence the equation is y2=x3+x+1 mod 307.

To do this cryptography point addition, point doubling and point multiplication are employed. To make encryption and decryption more feasible both sender and the receiver should know and agree upon the table defined with the chosen elliptic curve. Since the ECC is based on discrete logarithm, for an intruder to crack or steal the message is impossible. They should know the random integer generated 'r' by the sender and the private key of the receiver. The cracker should find the multiplier that creates the cipher text 'C' from the generator point 'G'. It is rather difficult when 'r' and 'z' in GF(z) are large.

C. Algorithm for ECC points

Algorithm to generate points

{

Select a EC with modulo z (y2=x3+ax+b% z)

Assign values to the coefficients a and b

Compute the equation y=x3+ax+b % z.

{

For x=0 to (p-1)

s=x3+ax+b % z

For d=0 to (z+1)/2

{

t = d2 %z

If t=s

y1 = d and y2 = z-d

else d = d+1

}

x=x+1

}

(x, y1), (x, y2)

}

N=301 where when N is multiplied by the point generator it should produce zero and the generator point is capable of reproducing all the points generated with the defined curve. The chosen point generator is (7,257). The total number of points generated are 296.

The plain text (M) is encoded into a point P(M) from the finite set of points generated in the elliptic curve Ep (a, b). When the points are generated, selecting a generator point 'G' is the important factor, where G ' Ep (a, b). The generator point and the Ep(a, b) will be made public. The generator point chosen is (7, 257). Sender and receiver can select a private key (Pr) and calculate the public key Pu = Pr x G.

The simple method of encryption and decryption is given below.

To encrypt the message:

1. The sender chooses a random integer 'r'.

2. Calculates cipher text point using receiver's Public Key.

3. C= [(r.G), (M+r. Pur)].

To decrypt the message:

1. Receiver multiplies the first point (r.G) with the private key (Prr).

2. Add this result to the second point of the cipher text pair.

3. M = (M+rPur)-(Prr(r.G))=(M+rPrrG) - (Prr(r.G))

V. OTHER SOLUTIONS

The security must be addressed throughout the device lifecycle, from the initial design to the operational environment:

1. Secure booting: When a device is first switched on, the authenticity and integrity of the software installed is verified using digital signatures generated cryptographically. The same way when a legal document is checked, the digital signature is verified by the device before loading it. Hence there is an establishment of trust. But the device still needs protection from various run-time threats and malicious intentions.

2. Access control:  The different forms of resource and access control are applied. Some access controls are built into the operating system which limit the privileges of device components and applications so they access only the resources they need to do perform their task. If any component is compromised, access control makes sure that the intruder has as minimal access to other parts of the system as possible. Device-based access control mechanisms and network-based access control systems are analogous such as Microsoft'' Active Directory''. Even if someone manages to steal corporate information to gain access to a network, compromised information would be limited to only those areas of the network authorized by those particular credentials. The principle of least privilege dictates that only the minimal access required to perform a function should be authorized in order to minimize the effectiveness of any breach of security.

3. Firewalling and IPS:  The traffic that is destined to end at the device should be controlled a firewall or deep packet inspection capability. Deeply embedded devices have unique protocols, different from enterprise IT protocols. For instance, the smart energy grid has its own set of steps governing how devices talk to each other. That is why industry-specific protocol filtering and deep packet inspection capabilities are needed to identify dangerous payloads hiding in non-IT protocols. Common higher-level internet traffic should not be the concern of the device'the network appliances should take care of that'but what it needs, is to filter the specific data destined to end on that device in a way that makes full use of the limited computational resources available.

4. Updates and patches:  Once the device is working, it will start receiving hot patches and software updates. Operators need to roll out patches, and devices need to verify them, in a way that does not consume bandwidth or interfere with the functional safety of the device. It's one thing when Microsoft sends updates to Windows'' users and ties up their devices for 15 minutes. It is quite another when thousands of devices in the field are performing important functions or services and are dependent on security patches to protect it against the inevitable vulnerability that escapes into the wild. Software updates and security patches must be delivered in a way that conserves the limited bandwidth and discontinuous connectivity of an embedded device and eliminates the possibility of compromising functional safety.

5. End to End security solutions:  Security at both the device and network levels is important to the operation of IoT.The same intelligence that makes devices perform their tasks must also enable them to recognize and coun''teract threats. Fortunately, this does not require a revolutionary approach, but rather an evolution of measures that have proven successful in IT networks, adapted to the challenges of IoT and to the constraints of connected devices

VI. CONCLUSION

Security is critical to IoT and needs to be taken care of at every stage because we are not just dealing with financial transactions which can be tackled through penalties in case there is a data breach. Here we are talking of systems whose interference could lead to loss of lives or cause massive disruption to the society.

IoT is a worthwhile amalgamation of business agility and technology. IoT takes a holistic risk based approach not only aligned to business objectives but also take into account the probable impact it may have on human lives. Within this, security is an enabler for a business to be conducted in a secure manner which is transparent and works behind the scenes. Security in a solution provides reasonable assurance to the business that the end customer's as well as their interests are safeguarded from potential threats.

Hence, the IoT shall use well-defined standards for security which talk with safety standards catering to diverse industries and enables businesses to think and act in a pragmatic way.

VII. REFERENCES

[1] Internet of Things (IoT): A vision, architectural elements, and future directions . Jayavardhana Gubbia, Rajkumar Buyyab,', Slaven Marusic a, Marimuthu Palaniswami a

[2] Recent Machine Learning Applications to Internet of Things (IoT)

Yue Xu (A paper written under the guidance of Prof. Raj Jain)  

[3] A Secure and Efficient ID-Based Aggregate Signature Scheme for Wireless Sensor Networks

Limin Shen ; Jianfeng Ma ; Ximeng Liu ; Fushan Wei ; Meixia Miao

[4] Secure Data Obfuscation Scheme to Enable Privacy-Preserving State Estimation in Smart Grid AMI Networks

Samet Tonyali ; Ozan Cakmak ; Kemal Akkaya ; Mohamed M. E. A. Mahmoud ; Ismail Guvenc

[5] Dynamic Resource Discovery Based on Preference and Movement Pattern Similarity for Large-Scale Social Internet of Things

Zhiyuan Li ; Rulong Chen ; Lu Liu ; Geyong Min

[6] Secure Object Tracking Protocol for the Internet of Things

Biplob R. Ray ; Morshed U. Chowdhury ; Jemal H. Abawajy

         

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