• No results found

RESEARCH STUDY ON FOG COMPUTING FOR SECURE DATA SECURITY

N/A
N/A
Protected

Academic year: 2022

Share "RESEARCH STUDY ON FOG COMPUTING FOR SECURE DATA SECURITY"

Copied!
8
0
0

Loading.... (view fulltext now)

Full text

(1)

RESEARCH STUDY ON FOG COMPUTING FOR SECURE DATA SECURITY

Niranjanamurthy M

1

, Kavitha P B

2

, Priyanka Kasana

3

, Vishnu S N

4

1,2,3,4

M, Department of Computer Applications, MSRIT, Bangalore, (India)

ABSTRACT

Fog computing which is also commonly called as fogging is a distributed computing infrastructure in which some application services are handled at the network in smart devices and some applications are handled in cloud. The term “fog computing” or “edge computing” means that other than hosting and working entirely from a centralized cloud, fog systems operate on network ends. It is a term for processing some small applications and resources at the edge of the cloud, rather than processing applications entirely in the cloud.

fog computing facilitates the operation of compute, storage and other services between end devices mostly IoT devices and cloud computing data centers. Fog Computing can never replace cloud it is just extending the cloud computing by giving security in the cloud atmosphere. With Fog services we are able to increase the cloud experience by separating users data that need to live on the edge. The main objective of fog computing is to process the data close to the end user. In this paper we did survey on fog computing, why we need fog, Challenges in fog computing, Comparing Fog computing with Cloud Computing, key advantages, Fog Computing Services.

Keywords: fog computing, why we need fog, Challenges in fog computing, Comparing Fog computing with Cloud Computing, key advantages, Fog Computing Services

I. INTRODUCTION

Fog computing or fog networking, is an architecture that uses one or a collaborative multitude of end-user clients or near-user edge devices to carry out a substantial amount of storage (instead of storing primarily in cloud data centers), communication (rather than routed over the internet). Fog model provides benefits in advertising, computing, entertainment and other applications, well suited for data analytics and distributed data collection points. End services can be easily done on set-up-boxes and access points . It improves QoS and reduces response time. The main objective of fogging is placing the information close to the user at the edge of the network. Fogging Advantages: -There is lot of reduction in data movement across the network resulting in reduced data traffic, cost and latency, elimination of overhead of centralized computing systems, increased security of data as it stays closer to the end user. 1.Eliminates the core computing environment, thereby reducing a major block and a point of failure. 2.Improves the security, as data are encoded as it is moved towards the network edge. 3. Edge Computing, in addition to providing sub-second response to end users, it also provides high levels of scalability, reliability and fault tolerance. 4. Consumes less amount of band width mainly in case like oil and gas where lot of bandwidth is required.

(2)

Cost: The bandwidth essential for regularly transmitting the huge amount of data (which could originate from anywhere in the country or in the world) to the cloud is very expensive and can create bottlenecks as various enterprise use cases contend for those same resources. Fog Computing requires relatively less movement of data, which makes the network traffic less for other uses.

Expedience: By processing data closer to its source where it was originated, Fog Computing can significantly expedite computations and processes—enabling organizations to go from ‗near real-time‘ processing speeds to true real-time processing. Again, the proliferation of mobile devices and demands projected for the IoT make time a essential component of service delivery and customer satisfaction. IoT applications such as vehicle to vehicle communication require the least amount of response time as possible.

Security and Governance: The lesser the frequency and the lesser the distance of the data travel, the more safe it tends to be. Additionally, there are strict regulatory requirements about where data is stored and accessed (which vary by industry and country) to which local Fog Computing at the extremities of the Cloud can innately conform.

II. RELATED WORK

WHY DO WE NEED FOG? As Fog computing is implemented at the edge of the network, it provides low response time for applications like traffic congestion system, location knowledge of the data , and increases quality-of-services (QoS) for streaming and real time applications where actions has to be taken in less amount of time. Typical examples include robotics, transportation, and networks of sensors and actuators. Moreover, this new infrastructure supports heterogeneity as Fog devices include end-user devices, access points, edge routers and switches. The Fog paradigm is well suited for real time big data analytics, supports mobility, and provides advantages in entertainment, personal computing and mainly in making IoT happen.

Fig-1: Fog computing in smart Grid.

(3)

Fig.2: Architecture of Fog computing

Fog computing is well suited for the geographical distribution of resources instead of having a centralized one, meaning Fog computing is the extension of Cloud computing. The difference is Fog provides proximity to its end users through dense geographical distribution and it also supports mobility. Access points or set-up boxes are used as end devices to host services at the network. In Fog computing platform multi-tier architecture is used. In first tier there is machine to machine communication and the higher tiers deals with visualization and reporting.[10]

WHAT CAN WE DO WITH FOG? Smart Grid: Energy load balancing applications may run on network edge devices, such as smart meters and micro-grids [15]. Based on energy demand, availability and the lowest price, these devices automatically switch to alternative energies like solar and wind. As shown in Figure 2, Fog collectors at the edge process the data generated by grid sensors and devices, and issue control commands to the actuators [14]. They also filter the data to be consumed locally, and send the rest to the higher tiers for visualization, real-time reports and transactional analytics. Fog supports ephemeral storage at the lowest tier to semi-permanent storage at the highest tier. Global coverage is provided by the Cloud with business intelligence analytics.Fig.2. Fog computing in smart traffic lights and connected vehicles. Smart Traffic Lights and Connected Vehicles: Video camera that senses an ambulance flashing lights can automatically change street lights to open lanes for the vehicle to pass through traffic. Smart street lights interact locally with sensors and detect presence of pedestrian and bikers, and measure the distance and speed of approaching vehicles. As shown in Figure 3, intelligent lighting turns on once a sensor identifies movement and switches off as traffic passes.

Neighboring smart lights serving as Fog devices coordinate to create green traffic wave and send warning signals to approaching vehicles [14]. Wireless access points like WiFi, 3G, road-side units and smart traffic lights are deployed along the roads. Vehicles-to Vehicle, vehicle to access points, and access points to access points interactions enrich the application of this scenario.[1]

Fog computing is a term for an alternative to cloud computing that puts some kinds of transactions and resources at the edge of a network, rather than establishing channels for cloud storage and utilization.

Proponents of fog computing argue that it can reduce the need for bandwidth by not sending every bit of information over cloud channels, and instead aggregating it at certain access points, such as routers. This allows for a more strategic

(4)

compilation of data that may not be needed in cloud storage right away, if at all. By using this kind of distributed strategy, project managers can lower costs and improve efficiencies. We propose a different approach for securing data in the cloud using technology of offensive decoy. We monitor data access in the cloud and detect abnormal data access patterns. When there is unauthorized access and then verified using challenge questions, we launch a disinformation attack by sending large amounts of decoy information to the attacker. [2]

With the increase of data theft attacks the security of user data has become a serious issue for cloud service providers for which Fog Computing is a paradigm which monitors the behavior of the user and provides security to the user data. Other techniques discussed in this paper use Fog computing for optimizing the website performance. We hope that by continuing this work using Fog Computing platforms can lead to improved defensive techniques and would contribute in increasing the level of security if user data on the cloud.[3]

With the increase of data theft attacks the security of user data security has become a serious issue for cloud serviceproviders for that Fog Computing is a paradigm which monitors the behavior of the user and provides security to the user data. Fog Computing presents a new approach to solve the problem of insider data theft attacks in a cloud using decoy files and also to save storage required for maintaining decoy files in the cloud.

So by using decoy files in Fog can minimize insider attacks in cloud.[5].

Decoy data, such as decoy documents, honey pots and other bogus files can be generated on demand and used to detect unauthorized access to information and to spoil the thief‘s ex-filtrated information. Serving decoys will make the attacker to believe that they have ex-filtrated useful data, when they have not. This technology is integrated with user behavior profiling technology to secure users data in the Cloud. . Whenever there is abnormal and unauthorized access to a cloud service, decoy information may be returned by the Cloud and delivered that it appears to be completely normal and legitimate. The legitimate user, would readily identify when decoy file is being returned by the Cloud, and hence could alter the Clouds responses through a variety of means, such as challenge questions, informing the Cloud security system that it has not correctly detected an unauthorized access. In the case where the access has been correctly detected as an unauthorized access, the Cloud security system would provide unbounded amounts of bogus files to the attacker, thus securing the users true data from can be implemented by two additional security features: (1) validating whether the access to the data is authorized when abnormal information access is identified, and (2) confusing the attacker with bogus data that is by providing decoy documents.[6]

Fog Computing is an extension of Cloud Computing. Fog computing also provides data, compute, storage, and application services to users. The only difference is Fog computing gives proximity to its end users through large geographical distribution and it also supports the mobility feature. Access points or set-up boxes are used as end devices to host services at the network and these devices are also referred as edge network. Fog computing improves the Quality of service. According to Cisco, due to its large geographical distribution the Fog computing is well suited in for areas such as real time analytics and big data. While Fog nodes allow localization, therefore allowing low latency and context awareness, the Cloud provides global centralization [7].

(5)

III. CHALLENGES IN FOG COMPUTING

There are many problems that will have to be addressed to make the fog a reality [7]. It is necessary to clearly identify these problems so that research works can focus on them. The set of open challenges for the fog is: 1) Discovery/Sync: Applications running on devices may require either some agreed, centralized point (e.g. to establish an ―upstream‖ backup if there are too few peers in our storage application); 2) Compute/Storage limitation: Current trends are improving this fact with smaller, more energy-efficient and more powerful devices (e.g. one of today‘s phones is more powerful than many high end desktops from 15 years ago). Still new improvements are granted for non consumer devices;

3) Management : In addition to setting up the communication routes across end nodes, IoT/ubiquitous computing nodes and applications running on top need to be properly setup and configured to operate as desired.

Having potentially billions of small devices to be configured, the fog will heavily rely on decentralized (scalable) management mechanisms that are yet to be tested at this unprecedented scale. One thing that can be predicted with certain degree of confidence is that there will be no full control of the whole fog and asymptotic declarative configuration techniques will become more common; 4) Security: The same security concerns that apply to current virtualized environments can be foreseen to affect fog devices hosting applications. The presence of secure sandboxes for the execution of droplet applications poses new interesting challenges: Trust and Privacy. Before using other devices or mini-clouds in the network to run some software, isolation and sandboxing mechanisms must be in place to ensure bidirectional trust among cooperating parties. The fog will allow applications to process user‘s data in third party‘s hardware/software. This of course introduces strong concerns about data privacy and its visibility to those third parties; 5) Standardization: Today no standardized mechanisms are available so each member of the network (terminal, edge point...) can announce its availability to host others software components, and for others to send it their software to be run;6) Accountability/Monetization: Enabling users to share they spare resources to host applications is very important to enable new business models around the concept of the fog. A proper system of incentives needs to be created.

The incentives can be financial or otherwise (e.g. unlimited free data rates). On the other hand the lack of central controlling entity in the fog makes it difficult to assert if a given device is indeed hosting a component (droplet) or not; 7) Programmability: Controlling application lifecycle is already a challenge in cloud environments [8].

The presence of small functional units (droplets) in more locations (devices) calls for the right abstractions to be in place, so that programmers do not need to deal with these difficult issues [9]. Easy to use APIs for programmers will heavily rely on simple Management mechanisms that provide them with the right abstractions to hide the massive complexity of the fog. Some vendors like Microsoft have already taken some steps in positioning themselves in this space9. Table 2 discusses which of these challenges are inherently new and which ones have been inherited by the fog from one of its ―parent‖ technologies.[1]

(6)

Comparing Fog computing with Cloud Computing

[Ref: http://www.healthit.myindustryt racker.com/ en/article/92751 /iot-from-cloud-to-fog]

The key advantages of Fog Computing are related to:

Data is placed closer to the End user – the Drops allow keeping the data close to a user instead of storing them in a datacenter which is far, and possible delays in data transfer can be eliminated.

It Creates a dense geographical distribution – Fog computing extends direct cloud services by creating an edge network which is located at numerous points. This, dense, geographically dispersed infrastructure helps in numerous ways: big data and analytics will be done faster, administrators are able to support location-based mobility demands and not have to traverse the entire WAN, and finally, these edge network (Fog) systems would be created in such a way that real-time data analytics become a reality on a truly massive scale.

True support for mobility and the Internet of Everything – there is a direct increase in the amount of devices and data that we use. Administrators will be able to leverage the Fog and control where users are coming in and how they access this information. As more services are created for the benefit of end-user, edge and Fog networks will become more prevalent.

Many verticals are ready to adopt – The term ―fog computing‖ has been embraced by Cisco Systems as a new paradigm to support wireless data transfer to support distributed Systems in the ―Internet of Things.‖ A number of distributed computing and storage start-up companies are also adopting the phrase. It builds upon earlier concepts in distributed computing, like content delivery networks, but allows the delivery of more complex services using cloud technologies.

Seamless integration with the cloud and other services – With Fog services is possible to enhance the cloud experience by isolating the user data that needs to live on the edge. From there, administrators are able to tie-in

(7)

analytics, security, or other services that are directly into their cloud model. This infrastructure still maintains the concept of the cloud while incorporating the power of Fog Computing at the edge.

Fog Computing Services cover:

 Applications that require very low and predictable latency.

 Geographically distributed applications

 Fast mobile applications

 Large-scale distributed control systems

Advantages of Fog computing

 Gets the data close to the user. Instead of housing information at data center sites far from the

end-point, the Fog aims to place the data close to the end-user.

 Creates dense geographical distribution. First of all, big data and analytics can be done faster with

better results. Second, administrators will be able to support location-based mobility demands and not have to traverse the entire network. Third, these edge (Fog) systems would be created in simplest way that real-time data analytics become a reality on a truly massive scale.

 True support for mobility and the Internet of Everything. By controlling data at various edge

points, Fog computing integrates core cloud services with those of a really distributed data center platform. As more services are created to benefit the end-user, edge and Fog networks will become more prevalent.

 Many verticals are ready to adopt. Many organizations are already adopting the concept of the

Fog. Many different kinds of services aim to deliver rich content to the end-user. This spans IT shops, vendors, and entertainment companies as well.

 Seamless integration with the cloud and other services. With Fog services, we‘re able to enhance

the cloud experience by isolating user data that needs to live on the edge. From there, administrators are able to tie-in analytics, security, or other services directly into their cloud model. [Ref: https://www.linkedin. com/pul se/2014052 0183722-246665791-fog-computing]

IV. CONCLUSION

Fog Computing is not a replacement for Cloud Computing. Fog Computing is a big step to a distributed cloud – by controlling data in all node points, fog computing allows turning datacenter into a distributed cloud platform for users. Fog is an addition which develops the concept of cloud services. Thanks to the ―drops‖ it is possible to isolate data in the cloud systems and keep them close to users. Fog computing is proposed to enable computing directly at

the edge of the network, which can deliver new applications and services especially for the future of Internet. Fog Computing extends the Cloud Computing paradigm to the edge of the network, thus enabling a new breed of applications and services. Defining characteristics of the Fog are: low latency and location awareness; wide-spread geographical distribution; mobility; very large number of nodes, predominant role of wireless access, strong presence of streaming and real time applications, heterogeneity. In this paper, the authors

(8)

argue that the above characteristics make the Fog the appropriate platform for a number of critical Internet of Things (IoT) services and applications, namely, Connected Vehicle, Smart Grid, Smart Cities, and, in general, Wireless Sensors and Actuators Networks (WSANs).

V. ACKNOWLEDGEMENTS

I thank Dr. T. V. Suresh Kumar, Prof. and Head, Dept. of MCA, MSRIT, Bangalore-54. for his continuous support and encouragement for completing this research paper and also thanks to MSRIT management.

I thank Dr. Jagannatha, Associate Professor. of Dept. of MCA, MSRIT, Bangalore-54, for his valuable guidance and support for completing this paper.

REFERENCES

[1] Divya Shrungar J, Priya M P, Asha S M - "Fog Computing: Security in Cloud Environment", International Journal of Advanced Research in Computer Science and Software Engineering ISSN: 2277 128X Volume 5, Issue 8, August 2015

[2] T.Rajesh Kanna, M. Nagaraju , Ch. Vijay Bhaskar-"Secure Fog Computing: Providing Data Security"

International Journal of Research in Computer and Communication Technology, Vol 4, Issue 1, January - 2015

[3] Manreet kaur, Monika Bharti-"Fog Computing Providing Data Security: A Review" International Journal of Advanced Research in Computer Science and Software Engineering Volume 4, Issue 6, June 2014 [4] Ivan Stojmenovic, Sheng Wen "The Fog Computing Paradigm: Scenarios andSecurity Issues" Federated

Conference on Computer Science and Information Systems pp. 1–8 Proceedings of the 2014

[5] Kshamata Shenoy, Prachi Bhokare, Unnathi Pai "FOG Computing Future of Cloud Computing"International Journal of Science and Research (IJSR) ISSN (Online): 2319-7064 Volume 4 Issue 6, June 2015

[6] Sonali Khairnar, Dhanashree Borkar, "FOG COMPUTING: A NEW CONCEPT TO MINIMIZE THE ATTACKS AND TO PROVIDE SECURITY IN CLOUD COMPUTING ENVIRONMENT"IJRET:

International Journal of Research in Engineering and Technology Volume: 03 Issue: 06 | Jun-2014 [7] Manreet Kaur, Monika Bharti "Securing user data on cloud using Fog computing and Decoy technique"

International Journal of Advance Research in Computer Science and Management Studies Volume 2, Issue 10, October 2014

[8] Bonomi, Flavio, et al. "Fog computing and its role in the internet of things." Proceedings of the first edition of the MCC workshop on Mobile cloud computing. ACM, 2012, pp. 13-16).

[9] F. Bonomi, ―Connected vehicles, the internet of things, and fog computing,‖ in The Eighth ACM International Workshop on Vehicular InterNetworking (VANET), Las Vegas, USA, 2011.

[10] Zhu, Jiang, ―Improving Web Sites Performance Using Edge Servers in Fog Computing Architecture‖, Service Oriented System Engineering (SOSE), IEEE. 2013.

References

Related documents

To best of our knowledge it was the first study to evalu- ate biofilm-forming ability and toxin expression of CRC- extracted Bacteroides fragilis isolates under planktonic

Before doing an aggregation, it is important to examine the available information.. Whereas the first three information are constant parameters of the BESS, the last infor- mation,

Self-hypnosis training has a positive impact on both the psychosocial and immune effects and is found to be useful in stress management with self-hypnosis evidence at

board the container vessel that will transport all the containers to the discharging port in Hamburg, Germany 7 Using the shipping line’s Key Transit. Table, it will take 37 days

The purpose of this quantitative study was to correlate the leadership style (Bass & Riggio, 2006) of supervisors with the OCB (Organ, 1988) of residential care workers

The re- sults of our study show that mean oxidative stress markers levels, both AOPP and MDA and total antioxidant capac- ity in elite athletes included in the study were increased

In the 2000s, the development of internet platforms that facilitated user-generated content transformed internet users from consumers to creators of personal webpages,