SlideShare a Scribd company logo
IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308
__________________________________________________________________________________________
Volume: 02 Issue: 12 | Dec-2013, Available @ http://www.ijret.org 36
MAS BASED FRAMEWORK TO PROTECT CLOUD COMPUTING
AGAINST DDOS ATTACK
Rohit Srivastava1
, Rohit Sharma2
, Avinash Verma3
1
Research Scholar, Computer Science Department, B.B.D. University, Lucknow, Uttar Pradesh, India
2
Assistant Professor, Computer Science Department, SITM, Barabanki, Uttar Pradesh, India
3
Senior Lecturer, Information Technology Department, B.B.D.N.I.T.M., Uttar Pradesh, India
rohitcss710@gmail.com, rohitsharma2412@gmail.com, avinash.verma93@yahoo.com
Abstract
In the today’s world cloud computing has become a very prominent technology in field of research and business. It can be realized as
assimilated technology of parallel computing, network storage technology, grid computing, distributed computing and other modern
existing technologies. According to our comprehensive approach we know that cloud computing provides resources and services to
their clients on behalf of their demands. These cloud services are sometimes abjured due to receiving a huge amount of requests. This
type of retraction in service providence of cloud environment is also considered as Denial of service attack in cloud environment.
DDoS attack is the enhanced form of DOS attack. In this paper the author is going to represent a framework for recognizing and
analyzing this attack with the help of multi agent system. Here the author describes the integration of the results achieved by the
Intrusion detection agents (IDA), existing inside virtual machine of cloud system with a method of data fusion in front- end. At the time
of attack the IDA generates alert signals which will be stored inside the My sql database residing in Cloud synthesizing unit (CSU).
The author propose a quantitative approach to explore the alerts yielded by IDA using Dempester Shapher Theory operation having
three valued logic and Fault tree Analysis described for various flooding attacks. Finally we combine the results achieved by various
IDAs.
----------------------------------------------------------------------***---------------------------------------------------------------------
1. INTRODUCTION
In the modern era cloud computing [4] [5] is playing a vital
role in various areas such as scientific, medicals, research and
academics. It is a well known service to the end user known as
pay on demand service. It has reduced various IT overheads. It
may be defined as a secured, cost effective and flexible service
for the end user. The most important feature of this technology
is accessibility and availability. As it provides virtualized
services and resources to the client via internet. So there is a
major issue of security for both ends, client side as well as
server side.
DDOS attack [9] [10] is one of the most important issues in
cloud environment. This attack neither tends to change or
modify the data nor focuses to illegal or unauthorized access.
It basically blocks the server or the network in order to
intercept the services provided to end user. It can be
implemented through various techniques such as IP spoofing,
bandwidth attack, smurfing, flooding etc.[11]. In DOS attack,
generally it takes sufficient amount time to identify a single
invalid request and response against it. When there are
multiple attacks taking place , the server becomes busy to
respond against these attacks and does not capable for
providing services to the client during that period. Then it is
considered as DDOS attack in the cloud environment.
A multi agent system [1] [2] [3] is used for packet monitoring
and intrusion detection which will work in communicating and
co-coordinating manner with their proactive and reactive
features. Since there is a lot of workload on the server in
order to handle each nonsense request therefore here the
author has proposed a framework with combination of packet
monitoring approach implemented through packet monitoring
agent and Intrusion detection system implemented through
Intrusion detection agent.
IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308
__________________________________________________________________________________________
Volume: 02 Issue: 12 | Dec-2013, Available @ http://www.ijret.org 37
DDoS attack
Fig 1: DOS attack
2. LITERATURE REVIEW
[1]. Alina Madalina Lonea Daniela Elena Popescu and
Huaglory Tianfield [4], have described a concept for detecting
DDoS attack in cloud computing by using IDS deployed in
VMs of cloud system with a a data fusion methodology in
front end. That generates alerts which is stored into the data
base placed within cloud fusion unit of front end server. The
basic concept is used to implement the task is Dampestar
Shapher theory, fault tolerance analysis (for mentioned
flooding attacks) and Dempestar’s combination rule.
[2]. Vikas Chouhan & Sateesh Kumar Peddoju [6] have
suggested a new way for protection of DDOS in cloud
environment using packet monitoring approach which is also
simulated in cloudsim toolkit. Here the author has given a
concept of HOP count and filtering that provides a
ungrudgingly available solution to protect cloud against
DDOS attack. The algorithm requires regular monitoring of
packets travelling in network and extracted the SYN flag, TTL
value and IP information from the TCP/IP packets and checks
that if SYN flag and TTL both values are not set then it
provides the output that the packet is spoofed.
[3].J.J.Shah and Dr. L.G.Malik [7] have efficiently described
the impact of DDOS attack in cloud computing and different
types of DDOS attack at the different layers of OSI model
with increasing complexity in performing attack and focuses
more on prevention and detection of DDOS at different layer
of OSI and effect of DDOS in cloud computing environment.
3. PROPOSED SOLUTION
As MAS is an emerging technology where complex problems
are solved with collaboration, coordination and
communication between agents where Agent can be simply
viewed as self described autonomous software component or
piece of codes. Here agent’s capability and its characteristics
like reactivity, pro-activeness, social ability etc are used to
facilitate applications in cloud computing. Multi-Agent
System will be beneficial for the construction of powerful,
flexible, scalable and extensible system. It is helpful to detect
and protect the cloud environment from DDOS attack and
fault occurrence rate as it is now a challenging issue for
researchers to protect cloud against this attack.
In this paper the author has focused to detect and remove basic
two different intrusions as IP spoofing and flooding attacks
with the help of multi agent system. In this approach the
author has used multiple agents in order to detect and remove
mention above DDoS attacks. Here the author has proposed an
architecture in which packet monitoring agent is used to
identify unauthorized packets travelling inside the network on
the other hand an intrusion detection agent is used to detect
and resolve various flooding attacks using TCP, UDP or
ICMP packets. The complete working of the architecture is
mentioned below-
Attacke
User
Attacker
ISP
Target
Server
User
Attacke
User
ISP
User
IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308
__________________________________________________________________________________________
Volume: 02 Issue: 12 | Dec-2013, Available @ http://www.ijret.org 38
PMA Private switch
Public Switch
Cloud Synthesizing Unit
Fig 2: Implementation of MAS in cloud Intrusion Detection methodology
Packet Monitoring Agent: The basic aim of the packet
monitoring agent is to regularly monitor the packets travelling
in the cloud in order to determine spoofed packets. This can be
implemented with the help of packet monitoring algorithm
where various comparisons are performed with respect to
SYN and TTL(Time to live) value. It is considered that each
packet is associated with a SYN flag and TTL value whose
value is stored in IP2HC table. The packet monitoring agent
uses the approach of this packet monitoring algorithm in
which at any instant of time if it is found that the SYN flag= 0
and Source IP value =0 and hop count is calculated by TTL, if
the calculated hop is not equal to the stored hop in IP2HC
table, it means that there are no any entries in the IP2HC table
for that particular packet and that is not considered as an
authentic packet and declared as a spoofed packet, because
every authentic IP address having a TCP connection must
have its entry in IP2HC table and it is blocked for further
movement in the network.
Intrusion Detection Agent: There are multiple IDAs are used
with each virtual machine in order to reduce the workload of
single IDA. In large network access it is very difficult to
analyze and resolve the attack by a single agent. Hence the
network traffic is now splitted into the IDAs and each agent
will work in communicating and collaborative manner. The
packets forwarded through the PMA are further analyzed by
the IDAs in order to check the mentioned flooding attacks.
These IDAs generates alerts by ID sensors deployed with
IDAs and these alerts are further stored in MY SQL data base
deployed in Cloud synthesizing unit. The Cloud synthesizing
unit having the capability to analyze the results using the
Dempester Shapher Theory of proof containing 3 valued logic
and an analysis of fault tree for IDAs for every virtual
machines. At the end of the analysis the whole result
transmitted by sensors are now integrated by using Dempester
combination rule. The major objective of this paper is get a
collaborating effort by each IDA. Whenever any IDA is out of
work at any instant of time then it will request for work to
another IDA, if the another IDA needs the help of requesting
IDA then it will provide an acknowledgement signal to the
requesting one, then the requesting IDA will also work in a
collaborative manner in order to remove the attack from the
specific node, due to this feature the multi agent system will
be more helpful to get rid of problem of agent overloading and
slow handling against each nonsense request.
In our proposed solution we have implemented a private cloud
containing three nodes and after completing the detection
phase by IDAs implemented within the virtual machines the
attack assessment process is executed by the Attack
Assessment Agent. This agent basically requires the
probability assignment of each packet .Which can be done by
using Probability Assignment Agent.
Probability Assignment Agent: The basic work of this agent
is to assign the probability to each packet for possible flooding
as TCP, UDP, and ICMP. Here we use an state space K and
three valued DST operations (YES, NO, (YES, NO)) for
possible flooding attacks as TCP, UDP, and ICMP for every
virtual machine based IDAs. Then some imitation code is
provided in order to convert the alert accessed from IDAs. The
Internet
p.s
My sql DB
PAA
AAA
IDA XEN O.S.
IDA XEN O.S.
IDA XEN O.S.
IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308
__________________________________________________________________________________________
Volume: 02 Issue: 12 | Dec-2013, Available @ http://www.ijret.org 39
basic aim of this code is to obtain mentioned below
probabilities of alerts received from IDAs.
Suppose that:
Mass of UDP=A
Mass of TCP=B
Mass of ICMP=C
Then we can write it as
(mA(y),mA(N),mA(Y,N))
(mB(y),mB(N),mB(Y,N))
(mC(y),mC(N),mC(Y,N))
Fig 3 Computation for probability assignment
Conversion of Alerts into Probability Assignments using code:
For every node
Start
For all E (TCP, ICMP, UDP)
1) Query for alerts from My-Sql when any attack E
takes place for specified host name.
2) Query the possible alerts against attack E for each
for all hostname.
3) If the attack E is unknown then make a query from
My Sql Database.
4) Compute “Yes” for E such as :
Yes (E) = result obtained from first
step/ result obtained from Second step
5) Compute ” (Yes, NO)” for attack E such as :
Yes, No (E) = result obtained from
Third step/ result obtained from Second step
6) Compute “No” for E such as:
No (E) = 1- (yes (E) + yes, No (E))
End
After computing the probabilities for each attack packet , the
probability for each IDA should be calculated mentioned
below the fault tree as described in figure 3 which contains
the total calculated probability of attack on the first IDA
represented by T. It can be represented as:
mT1(y), mT1(N),mT1 (y,N).
Hence using this approach we can can also compute the Belief
and Possibility of attack for all IDA as :
Belief= mT1(y) and
Possibility= mT1(y)+ mT1(y,N)
Attack Assessment Agent:The basic work of this agent is to
assess the attack by analyzing the combination of result
provided by various IDAs . This can be easily achieved by
using Dempester’s combination rule. Which is helpful to
increase the “TRUE DDoS positive rates” and decrease the”
False DDoS positive rates.”
IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308
__________________________________________________________________________________________
Volume: 02 Issue: 12 | Dec-2013, Available @ http://www.ijret.org 40
CONCLUSIONS
As it is very clear to us that here Dempester Shapher Theory is
used to analyze and detect the DDoS in Cloud implemented
with Intrusion Detection Agent. But here the author has used
various factors which are helpful to detect and avoid DDoS
from cloud. The use of multiagent system makes the proposed
methodology more efficient with reference to extra workload
and speed up factors.
Besides this the communicating and collaborative property of
the agents are used in which at any instant of time if one agent
is busy enough in order to handle with nonsense request and
not capable to provide services to authentic users then the free
agent communicates with the busy one in order to share the
workload of busy agent this also makes the processing faster
comparatively previous solutions.
REFERENCES
[1] M. Wooldridge, “Intelligent agents,” in Multi-Agent
Systems, M. Wooldridge and G. Weiss, Eds., pp. 3–51,
MIT Press, Cambridge, Mass, USA, 1999.
[2] S.M. Wooldridge and N. R. Jennings, “Intelligent
agents: theory and practice,” The Knowledge
Engineering Review, vol. 10, no. 2, pp. 115–152, 1995.
[3] M. Wooldridge, An Introduction to Multi-agent
Systems, John Willey & Sons, New York, NY, USA,
2003.
[4] A.M. Lonea, D.E. Popescu, H. Tianfield, Detecting
DDoS Attacks in Cloud Computing Environment, INT
J COMPUT COMMUN, ISSN 1841-9836, 8(1):70-78,
February, 2013.
[5] Muhammad Zakarya, DDoS Verification and Attack
Packet Dropping Algorithm in Cloud Computing,
World Applied Sciences Journal 23 (11): 1418-1424,
2013,ISSN 1818-4952,© IDOSI Publications,
2013,DOI: 10.5829/idosi.wasj.2013.23.11.950.
[6] Vikas Chouhan & Sateesh Kumar Peddoju, Packet
Monitoring Approach to Prevent DDoS Attack in
Cloud Computing, International Journal of Computer
Science and Electrical Engineering (IJCSEE) ISSN No.
2315-4209, Vol-1 Iss-1, 2012
[7] J.J.Shah Dr. L.G.Malik, Impact of DDOS Attacks on
Cloud Environment, International Journal of Research
in Computer and Communication Technology, Vol 2,
Issue 7, July-2013,ISSN(Online) 2278-5841,ISSN
(Print) 2320-5156.
[8] Priyanka Negi, Anupama Mishra and B. B. Gupta
Enhanced CBF Packet Filtering Method to Detect
DDoS Attack in Cloud Computing Environment.
[9] Nisha H. Bhandari, Survey on DDoS Attacks and its
Detection & Defence Approaches, International Journal
of Science and Modern Engineering (IJISME) ISSN:
2319-6386, Volume-1, Issue-3, February 2013.
[10] Amit Khajuria, Roshan Srivastava, Analysis of the
DDoS Defence Stratigies in Cloud Computing,
INTERNATIONAL JOURNAL OF ENHANCED
RESEARCH IN MANAGEMENT & COMPUTER
APPLICATIONS,VOL. 2, ISSUE 2, FEB.-2013 ISSN
NO: 2319-7471.
[11] Upma Goyal, Gayatri Bhatti and Sandeep Mehmi ,A
Dual mechanism for defeating DDoS in cloud
computing Model, International Journal of Application
or Innovation in Engineering & Management
(IJAIEM), ISSN 2319 – 4847, Volume 2, Issue 3,
March 2013.
BIOGRAPHIES
Rohit Srivastav is pursuing M.Tech. from
B.B.D. University and completed his B.Tech.
in Computer science. He has also published
papers in international journal.
Dr. Rohit Sharma received his Ph.D. degree
in computer science and guided number of
M.Tech. thesis. He has also published
research papers in international journal and
also a reviewer of few international journals.
Avinash Verma received his M.Tech. degree
in Computer Science and also pursuing
Ph.D. in Computer Science. He has guided
various M.Tech. thesis.

More Related Content

PDF
A combined approach to search for evasion techniques in network intrusion det...
PDF
DIVISION AND REPLICATION OF DATA IN GRID FOR OPTIMAL PERFORMANCE AND SECURITY
PDF
A Collaborative Intrusion Detection System for Cloud Computing
PDF
06558266
PDF
IRJET- Storage Security in Cloud Computing
PDF
A novel approach for a secured intrusion detection system in manet
PDF
Review of Detection DDOS Attack Detection Using Naive Bayes Classifier for Ne...
PDF
G0262042047
A combined approach to search for evasion techniques in network intrusion det...
DIVISION AND REPLICATION OF DATA IN GRID FOR OPTIMAL PERFORMANCE AND SECURITY
A Collaborative Intrusion Detection System for Cloud Computing
06558266
IRJET- Storage Security in Cloud Computing
A novel approach for a secured intrusion detection system in manet
Review of Detection DDOS Attack Detection Using Naive Bayes Classifier for Ne...
G0262042047

What's hot (12)

PDF
IJCER (www.ijceronline.com) International Journal of computational Engineerin...
PDF
IRJET- Netreconner: An Innovative Method to Intrusion Detection using Regular...
PDF
DEVELOPING MOBILE AGENT FOR INTRUSION DETECTION
PDF
Investigation of detection & prevention sinkhole attack in manet
PDF
Pe2 a public encryption with two ack approach to
PDF
Network Security Using IDS, IPS & Honeypot
PDF
How to Counter-act Security Threats in Mobile Ad Hoc Networks?
PDF
New Security Threats and Protection Techniques in Mobile Ad Hoc Networks
PDF
Public encryption with two ack approach to mitigate wormhole attack in wsn
PDF
Behavioral Malware Detection in Dtn Using Intrusion Detection System
PDF
A45010107
PDF
1850 1854
IJCER (www.ijceronline.com) International Journal of computational Engineerin...
IRJET- Netreconner: An Innovative Method to Intrusion Detection using Regular...
DEVELOPING MOBILE AGENT FOR INTRUSION DETECTION
Investigation of detection & prevention sinkhole attack in manet
Pe2 a public encryption with two ack approach to
Network Security Using IDS, IPS & Honeypot
How to Counter-act Security Threats in Mobile Ad Hoc Networks?
New Security Threats and Protection Techniques in Mobile Ad Hoc Networks
Public encryption with two ack approach to mitigate wormhole attack in wsn
Behavioral Malware Detection in Dtn Using Intrusion Detection System
A45010107
1850 1854
Ad

Viewers also liked (20)

PDF
Shear strength of rc deep beam panels – a review
PDF
3 d video streaming for virtual exploration of planet surface
PDF
Transmission of image using sms technique
PDF
Ontology based clustering in research project
PDF
Invalidating vulnerable broadcaster nodes using
PDF
Robotic arm controlled in missile launchers using plc and image authenticatio...
PDF
Development of strain prediction models for concrete roads
PDF
Copyright protection for images on android phones
PDF
Review on redundancy removal of rules for optimizing firewall
PDF
Effect of dyeing parameters on dyeing of cotton fabrics with fluoro chloro py...
PDF
Experimental study of behaviour of poultry feather fiber a reinforcing mate...
PDF
Fractals for complexity analysis of diabetic retinopathy in retinal vasculatu...
PDF
An octo coding technique to reduce energy transition
PDF
A distinct approach for xmotif application gui test automation
PDF
Influence of land use land cover in simulating the thunderstorm event using ...
PDF
Real time voting system using face recognition for different expressions and ...
PDF
Evaluation of the impact of oil spillage on izombe community and their produc...
PDF
Effect and optimization of machining parameters on
PDF
A comprehensive survey on data mining
PDF
Characteristic orthogonal polynimial application to galerkin indirect variati...
Shear strength of rc deep beam panels – a review
3 d video streaming for virtual exploration of planet surface
Transmission of image using sms technique
Ontology based clustering in research project
Invalidating vulnerable broadcaster nodes using
Robotic arm controlled in missile launchers using plc and image authenticatio...
Development of strain prediction models for concrete roads
Copyright protection for images on android phones
Review on redundancy removal of rules for optimizing firewall
Effect of dyeing parameters on dyeing of cotton fabrics with fluoro chloro py...
Experimental study of behaviour of poultry feather fiber a reinforcing mate...
Fractals for complexity analysis of diabetic retinopathy in retinal vasculatu...
An octo coding technique to reduce energy transition
A distinct approach for xmotif application gui test automation
Influence of land use land cover in simulating the thunderstorm event using ...
Real time voting system using face recognition for different expressions and ...
Evaluation of the impact of oil spillage on izombe community and their produc...
Effect and optimization of machining parameters on
A comprehensive survey on data mining
Characteristic orthogonal polynimial application to galerkin indirect variati...
Ad

Similar to Mas based framework to protect cloud computing (20)

PDF
Secure intrusion detection and countermeasure selection in virtual system usi...
PDF
1426742816
PDF
A novel distributed intrusion detection framework for network analysis
PDF
An Improved Intrusion Prevention Sytem for WLAN
PDF
An Improved Intrusion Prevention Sytem for WLAN
PDF
An intelligent system to detect slow denial of service attacks in software-de...
PDF
IRJET- Software Defined Network: DDOS Attack Detection
PDF
Secure data dissemination protocol in wireless sensor networks using xor netw...
PDF
DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODEL
PDF
Deep Learning for Smart Grid Intrusion Detection: A Hybrid CNN-LSTM-Based Model
PDF
DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODEL
PDF
EFFICIENT IDENTIFICATION AND REDUCTION OF MULTIPLE ATTACKS ADD VICTIMISATION ...
PDF
Ak03402100217
PDF
Ijmet 10 02_045
PDF
An approach for ids by combining svm and ant colony algorithm
PDF
An approach for ids by combining svm and ant colony algorithm
PDF
Crypto Mark Scheme for Fast Pollution Detection and Resistance over Networking
PDF
A honeynet framework to promote enterprise network security
PDF
Cloud computing challenges and solutions
PDF
International Journal of Fuzzy Logic Systems (IJFLS)
Secure intrusion detection and countermeasure selection in virtual system usi...
1426742816
A novel distributed intrusion detection framework for network analysis
An Improved Intrusion Prevention Sytem for WLAN
An Improved Intrusion Prevention Sytem for WLAN
An intelligent system to detect slow denial of service attacks in software-de...
IRJET- Software Defined Network: DDOS Attack Detection
Secure data dissemination protocol in wireless sensor networks using xor netw...
DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODEL
Deep Learning for Smart Grid Intrusion Detection: A Hybrid CNN-LSTM-Based Model
DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODEL
EFFICIENT IDENTIFICATION AND REDUCTION OF MULTIPLE ATTACKS ADD VICTIMISATION ...
Ak03402100217
Ijmet 10 02_045
An approach for ids by combining svm and ant colony algorithm
An approach for ids by combining svm and ant colony algorithm
Crypto Mark Scheme for Fast Pollution Detection and Resistance over Networking
A honeynet framework to promote enterprise network security
Cloud computing challenges and solutions
International Journal of Fuzzy Logic Systems (IJFLS)

More from eSAT Publishing House (20)

PDF
Likely impacts of hudhud on the environment of visakhapatnam
PDF
Impact of flood disaster in a drought prone area – case study of alampur vill...
PDF
Hudhud cyclone – a severe disaster in visakhapatnam
PDF
Groundwater investigation using geophysical methods a case study of pydibhim...
PDF
Flood related disasters concerned to urban flooding in bangalore, india
PDF
Enhancing post disaster recovery by optimal infrastructure capacity building
PDF
Effect of lintel and lintel band on the global performance of reinforced conc...
PDF
Wind damage to trees in the gitam university campus at visakhapatnam by cyclo...
PDF
Wind damage to buildings, infrastrucuture and landscape elements along the be...
PDF
Role of voluntary teams of professional engineers in dissater management – ex...
PDF
Risk analysis and environmental hazard management
PDF
Review study on performance of seismically tested repaired shear walls
PDF
Monitoring and assessment of air quality with reference to dust particles (pm...
PDF
Low cost wireless sensor networks and smartphone applications for disaster ma...
PDF
Coastal zones – seismic vulnerability an analysis from east coast of india
PDF
Can fracture mechanics predict damage due disaster of structures
PDF
Assessment of seismic susceptibility of rc buildings
PDF
A geophysical insight of earthquake occurred on 21 st may 2014 off paradip, b...
PDF
Effect of hudhud cyclone on the development of visakhapatnam as smart and gre...
PDF
Disaster recovery sustainable housing
Likely impacts of hudhud on the environment of visakhapatnam
Impact of flood disaster in a drought prone area – case study of alampur vill...
Hudhud cyclone – a severe disaster in visakhapatnam
Groundwater investigation using geophysical methods a case study of pydibhim...
Flood related disasters concerned to urban flooding in bangalore, india
Enhancing post disaster recovery by optimal infrastructure capacity building
Effect of lintel and lintel band on the global performance of reinforced conc...
Wind damage to trees in the gitam university campus at visakhapatnam by cyclo...
Wind damage to buildings, infrastrucuture and landscape elements along the be...
Role of voluntary teams of professional engineers in dissater management – ex...
Risk analysis and environmental hazard management
Review study on performance of seismically tested repaired shear walls
Monitoring and assessment of air quality with reference to dust particles (pm...
Low cost wireless sensor networks and smartphone applications for disaster ma...
Coastal zones – seismic vulnerability an analysis from east coast of india
Can fracture mechanics predict damage due disaster of structures
Assessment of seismic susceptibility of rc buildings
A geophysical insight of earthquake occurred on 21 st may 2014 off paradip, b...
Effect of hudhud cyclone on the development of visakhapatnam as smart and gre...
Disaster recovery sustainable housing

Recently uploaded (20)

PDF
Automation-in-Manufacturing-Chapter-Introduction.pdf
PPTX
OOP with Java - Java Introduction (Basics)
PPTX
CH1 Production IntroductoryConcepts.pptx
PPTX
Engineering Ethics, Safety and Environment [Autosaved] (1).pptx
PPTX
M Tech Sem 1 Civil Engineering Environmental Sciences.pptx
PPTX
Recipes for Real Time Voice AI WebRTC, SLMs and Open Source Software.pptx
PDF
keyrequirementskkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkk
PDF
Mohammad Mahdi Farshadian CV - Prospective PhD Student 2026
PPTX
MCN 401 KTU-2019-PPE KITS-MODULE 2.pptx
PPTX
CARTOGRAPHY AND GEOINFORMATION VISUALIZATION chapter1 NPTE (2).pptx
PPTX
Lecture Notes Electrical Wiring System Components
PPTX
Internet of Things (IOT) - A guide to understanding
PDF
Model Code of Practice - Construction Work - 21102022 .pdf
PDF
PPT on Performance Review to get promotions
DOCX
573137875-Attendance-Management-System-original
PPT
CRASH COURSE IN ALTERNATIVE PLUMBING CLASS
PPTX
IOT PPTs Week 10 Lecture Material.pptx of NPTEL Smart Cities contd
PPTX
bas. eng. economics group 4 presentation 1.pptx
PDF
The CXO Playbook 2025 – Future-Ready Strategies for C-Suite Leaders Cerebrai...
PPTX
Sustainable Sites - Green Building Construction
Automation-in-Manufacturing-Chapter-Introduction.pdf
OOP with Java - Java Introduction (Basics)
CH1 Production IntroductoryConcepts.pptx
Engineering Ethics, Safety and Environment [Autosaved] (1).pptx
M Tech Sem 1 Civil Engineering Environmental Sciences.pptx
Recipes for Real Time Voice AI WebRTC, SLMs and Open Source Software.pptx
keyrequirementskkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkk
Mohammad Mahdi Farshadian CV - Prospective PhD Student 2026
MCN 401 KTU-2019-PPE KITS-MODULE 2.pptx
CARTOGRAPHY AND GEOINFORMATION VISUALIZATION chapter1 NPTE (2).pptx
Lecture Notes Electrical Wiring System Components
Internet of Things (IOT) - A guide to understanding
Model Code of Practice - Construction Work - 21102022 .pdf
PPT on Performance Review to get promotions
573137875-Attendance-Management-System-original
CRASH COURSE IN ALTERNATIVE PLUMBING CLASS
IOT PPTs Week 10 Lecture Material.pptx of NPTEL Smart Cities contd
bas. eng. economics group 4 presentation 1.pptx
The CXO Playbook 2025 – Future-Ready Strategies for C-Suite Leaders Cerebrai...
Sustainable Sites - Green Building Construction

Mas based framework to protect cloud computing

  • 1. IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308 __________________________________________________________________________________________ Volume: 02 Issue: 12 | Dec-2013, Available @ http://www.ijret.org 36 MAS BASED FRAMEWORK TO PROTECT CLOUD COMPUTING AGAINST DDOS ATTACK Rohit Srivastava1 , Rohit Sharma2 , Avinash Verma3 1 Research Scholar, Computer Science Department, B.B.D. University, Lucknow, Uttar Pradesh, India 2 Assistant Professor, Computer Science Department, SITM, Barabanki, Uttar Pradesh, India 3 Senior Lecturer, Information Technology Department, B.B.D.N.I.T.M., Uttar Pradesh, India rohitcss710@gmail.com, rohitsharma2412@gmail.com, avinash.verma93@yahoo.com Abstract In the today’s world cloud computing has become a very prominent technology in field of research and business. It can be realized as assimilated technology of parallel computing, network storage technology, grid computing, distributed computing and other modern existing technologies. According to our comprehensive approach we know that cloud computing provides resources and services to their clients on behalf of their demands. These cloud services are sometimes abjured due to receiving a huge amount of requests. This type of retraction in service providence of cloud environment is also considered as Denial of service attack in cloud environment. DDoS attack is the enhanced form of DOS attack. In this paper the author is going to represent a framework for recognizing and analyzing this attack with the help of multi agent system. Here the author describes the integration of the results achieved by the Intrusion detection agents (IDA), existing inside virtual machine of cloud system with a method of data fusion in front- end. At the time of attack the IDA generates alert signals which will be stored inside the My sql database residing in Cloud synthesizing unit (CSU). The author propose a quantitative approach to explore the alerts yielded by IDA using Dempester Shapher Theory operation having three valued logic and Fault tree Analysis described for various flooding attacks. Finally we combine the results achieved by various IDAs. ----------------------------------------------------------------------***--------------------------------------------------------------------- 1. INTRODUCTION In the modern era cloud computing [4] [5] is playing a vital role in various areas such as scientific, medicals, research and academics. It is a well known service to the end user known as pay on demand service. It has reduced various IT overheads. It may be defined as a secured, cost effective and flexible service for the end user. The most important feature of this technology is accessibility and availability. As it provides virtualized services and resources to the client via internet. So there is a major issue of security for both ends, client side as well as server side. DDOS attack [9] [10] is one of the most important issues in cloud environment. This attack neither tends to change or modify the data nor focuses to illegal or unauthorized access. It basically blocks the server or the network in order to intercept the services provided to end user. It can be implemented through various techniques such as IP spoofing, bandwidth attack, smurfing, flooding etc.[11]. In DOS attack, generally it takes sufficient amount time to identify a single invalid request and response against it. When there are multiple attacks taking place , the server becomes busy to respond against these attacks and does not capable for providing services to the client during that period. Then it is considered as DDOS attack in the cloud environment. A multi agent system [1] [2] [3] is used for packet monitoring and intrusion detection which will work in communicating and co-coordinating manner with their proactive and reactive features. Since there is a lot of workload on the server in order to handle each nonsense request therefore here the author has proposed a framework with combination of packet monitoring approach implemented through packet monitoring agent and Intrusion detection system implemented through Intrusion detection agent.
  • 2. IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308 __________________________________________________________________________________________ Volume: 02 Issue: 12 | Dec-2013, Available @ http://www.ijret.org 37 DDoS attack Fig 1: DOS attack 2. LITERATURE REVIEW [1]. Alina Madalina Lonea Daniela Elena Popescu and Huaglory Tianfield [4], have described a concept for detecting DDoS attack in cloud computing by using IDS deployed in VMs of cloud system with a a data fusion methodology in front end. That generates alerts which is stored into the data base placed within cloud fusion unit of front end server. The basic concept is used to implement the task is Dampestar Shapher theory, fault tolerance analysis (for mentioned flooding attacks) and Dempestar’s combination rule. [2]. Vikas Chouhan & Sateesh Kumar Peddoju [6] have suggested a new way for protection of DDOS in cloud environment using packet monitoring approach which is also simulated in cloudsim toolkit. Here the author has given a concept of HOP count and filtering that provides a ungrudgingly available solution to protect cloud against DDOS attack. The algorithm requires regular monitoring of packets travelling in network and extracted the SYN flag, TTL value and IP information from the TCP/IP packets and checks that if SYN flag and TTL both values are not set then it provides the output that the packet is spoofed. [3].J.J.Shah and Dr. L.G.Malik [7] have efficiently described the impact of DDOS attack in cloud computing and different types of DDOS attack at the different layers of OSI model with increasing complexity in performing attack and focuses more on prevention and detection of DDOS at different layer of OSI and effect of DDOS in cloud computing environment. 3. PROPOSED SOLUTION As MAS is an emerging technology where complex problems are solved with collaboration, coordination and communication between agents where Agent can be simply viewed as self described autonomous software component or piece of codes. Here agent’s capability and its characteristics like reactivity, pro-activeness, social ability etc are used to facilitate applications in cloud computing. Multi-Agent System will be beneficial for the construction of powerful, flexible, scalable and extensible system. It is helpful to detect and protect the cloud environment from DDOS attack and fault occurrence rate as it is now a challenging issue for researchers to protect cloud against this attack. In this paper the author has focused to detect and remove basic two different intrusions as IP spoofing and flooding attacks with the help of multi agent system. In this approach the author has used multiple agents in order to detect and remove mention above DDoS attacks. Here the author has proposed an architecture in which packet monitoring agent is used to identify unauthorized packets travelling inside the network on the other hand an intrusion detection agent is used to detect and resolve various flooding attacks using TCP, UDP or ICMP packets. The complete working of the architecture is mentioned below- Attacke User Attacker ISP Target Server User Attacke User ISP User
  • 3. IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308 __________________________________________________________________________________________ Volume: 02 Issue: 12 | Dec-2013, Available @ http://www.ijret.org 38 PMA Private switch Public Switch Cloud Synthesizing Unit Fig 2: Implementation of MAS in cloud Intrusion Detection methodology Packet Monitoring Agent: The basic aim of the packet monitoring agent is to regularly monitor the packets travelling in the cloud in order to determine spoofed packets. This can be implemented with the help of packet monitoring algorithm where various comparisons are performed with respect to SYN and TTL(Time to live) value. It is considered that each packet is associated with a SYN flag and TTL value whose value is stored in IP2HC table. The packet monitoring agent uses the approach of this packet monitoring algorithm in which at any instant of time if it is found that the SYN flag= 0 and Source IP value =0 and hop count is calculated by TTL, if the calculated hop is not equal to the stored hop in IP2HC table, it means that there are no any entries in the IP2HC table for that particular packet and that is not considered as an authentic packet and declared as a spoofed packet, because every authentic IP address having a TCP connection must have its entry in IP2HC table and it is blocked for further movement in the network. Intrusion Detection Agent: There are multiple IDAs are used with each virtual machine in order to reduce the workload of single IDA. In large network access it is very difficult to analyze and resolve the attack by a single agent. Hence the network traffic is now splitted into the IDAs and each agent will work in communicating and collaborative manner. The packets forwarded through the PMA are further analyzed by the IDAs in order to check the mentioned flooding attacks. These IDAs generates alerts by ID sensors deployed with IDAs and these alerts are further stored in MY SQL data base deployed in Cloud synthesizing unit. The Cloud synthesizing unit having the capability to analyze the results using the Dempester Shapher Theory of proof containing 3 valued logic and an analysis of fault tree for IDAs for every virtual machines. At the end of the analysis the whole result transmitted by sensors are now integrated by using Dempester combination rule. The major objective of this paper is get a collaborating effort by each IDA. Whenever any IDA is out of work at any instant of time then it will request for work to another IDA, if the another IDA needs the help of requesting IDA then it will provide an acknowledgement signal to the requesting one, then the requesting IDA will also work in a collaborative manner in order to remove the attack from the specific node, due to this feature the multi agent system will be more helpful to get rid of problem of agent overloading and slow handling against each nonsense request. In our proposed solution we have implemented a private cloud containing three nodes and after completing the detection phase by IDAs implemented within the virtual machines the attack assessment process is executed by the Attack Assessment Agent. This agent basically requires the probability assignment of each packet .Which can be done by using Probability Assignment Agent. Probability Assignment Agent: The basic work of this agent is to assign the probability to each packet for possible flooding as TCP, UDP, and ICMP. Here we use an state space K and three valued DST operations (YES, NO, (YES, NO)) for possible flooding attacks as TCP, UDP, and ICMP for every virtual machine based IDAs. Then some imitation code is provided in order to convert the alert accessed from IDAs. The Internet p.s My sql DB PAA AAA IDA XEN O.S. IDA XEN O.S. IDA XEN O.S.
  • 4. IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308 __________________________________________________________________________________________ Volume: 02 Issue: 12 | Dec-2013, Available @ http://www.ijret.org 39 basic aim of this code is to obtain mentioned below probabilities of alerts received from IDAs. Suppose that: Mass of UDP=A Mass of TCP=B Mass of ICMP=C Then we can write it as (mA(y),mA(N),mA(Y,N)) (mB(y),mB(N),mB(Y,N)) (mC(y),mC(N),mC(Y,N)) Fig 3 Computation for probability assignment Conversion of Alerts into Probability Assignments using code: For every node Start For all E (TCP, ICMP, UDP) 1) Query for alerts from My-Sql when any attack E takes place for specified host name. 2) Query the possible alerts against attack E for each for all hostname. 3) If the attack E is unknown then make a query from My Sql Database. 4) Compute “Yes” for E such as : Yes (E) = result obtained from first step/ result obtained from Second step 5) Compute ” (Yes, NO)” for attack E such as : Yes, No (E) = result obtained from Third step/ result obtained from Second step 6) Compute “No” for E such as: No (E) = 1- (yes (E) + yes, No (E)) End After computing the probabilities for each attack packet , the probability for each IDA should be calculated mentioned below the fault tree as described in figure 3 which contains the total calculated probability of attack on the first IDA represented by T. It can be represented as: mT1(y), mT1(N),mT1 (y,N). Hence using this approach we can can also compute the Belief and Possibility of attack for all IDA as : Belief= mT1(y) and Possibility= mT1(y)+ mT1(y,N) Attack Assessment Agent:The basic work of this agent is to assess the attack by analyzing the combination of result provided by various IDAs . This can be easily achieved by using Dempester’s combination rule. Which is helpful to increase the “TRUE DDoS positive rates” and decrease the” False DDoS positive rates.”
  • 5. IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308 __________________________________________________________________________________________ Volume: 02 Issue: 12 | Dec-2013, Available @ http://www.ijret.org 40 CONCLUSIONS As it is very clear to us that here Dempester Shapher Theory is used to analyze and detect the DDoS in Cloud implemented with Intrusion Detection Agent. But here the author has used various factors which are helpful to detect and avoid DDoS from cloud. The use of multiagent system makes the proposed methodology more efficient with reference to extra workload and speed up factors. Besides this the communicating and collaborative property of the agents are used in which at any instant of time if one agent is busy enough in order to handle with nonsense request and not capable to provide services to authentic users then the free agent communicates with the busy one in order to share the workload of busy agent this also makes the processing faster comparatively previous solutions. REFERENCES [1] M. Wooldridge, “Intelligent agents,” in Multi-Agent Systems, M. Wooldridge and G. Weiss, Eds., pp. 3–51, MIT Press, Cambridge, Mass, USA, 1999. [2] S.M. Wooldridge and N. R. Jennings, “Intelligent agents: theory and practice,” The Knowledge Engineering Review, vol. 10, no. 2, pp. 115–152, 1995. [3] M. Wooldridge, An Introduction to Multi-agent Systems, John Willey & Sons, New York, NY, USA, 2003. [4] A.M. Lonea, D.E. Popescu, H. Tianfield, Detecting DDoS Attacks in Cloud Computing Environment, INT J COMPUT COMMUN, ISSN 1841-9836, 8(1):70-78, February, 2013. [5] Muhammad Zakarya, DDoS Verification and Attack Packet Dropping Algorithm in Cloud Computing, World Applied Sciences Journal 23 (11): 1418-1424, 2013,ISSN 1818-4952,© IDOSI Publications, 2013,DOI: 10.5829/idosi.wasj.2013.23.11.950. [6] Vikas Chouhan & Sateesh Kumar Peddoju, Packet Monitoring Approach to Prevent DDoS Attack in Cloud Computing, International Journal of Computer Science and Electrical Engineering (IJCSEE) ISSN No. 2315-4209, Vol-1 Iss-1, 2012 [7] J.J.Shah Dr. L.G.Malik, Impact of DDOS Attacks on Cloud Environment, International Journal of Research in Computer and Communication Technology, Vol 2, Issue 7, July-2013,ISSN(Online) 2278-5841,ISSN (Print) 2320-5156. [8] Priyanka Negi, Anupama Mishra and B. B. Gupta Enhanced CBF Packet Filtering Method to Detect DDoS Attack in Cloud Computing Environment. [9] Nisha H. Bhandari, Survey on DDoS Attacks and its Detection & Defence Approaches, International Journal of Science and Modern Engineering (IJISME) ISSN: 2319-6386, Volume-1, Issue-3, February 2013. [10] Amit Khajuria, Roshan Srivastava, Analysis of the DDoS Defence Stratigies in Cloud Computing, INTERNATIONAL JOURNAL OF ENHANCED RESEARCH IN MANAGEMENT & COMPUTER APPLICATIONS,VOL. 2, ISSUE 2, FEB.-2013 ISSN NO: 2319-7471. [11] Upma Goyal, Gayatri Bhatti and Sandeep Mehmi ,A Dual mechanism for defeating DDoS in cloud computing Model, International Journal of Application or Innovation in Engineering & Management (IJAIEM), ISSN 2319 – 4847, Volume 2, Issue 3, March 2013. BIOGRAPHIES Rohit Srivastav is pursuing M.Tech. from B.B.D. University and completed his B.Tech. in Computer science. He has also published papers in international journal. Dr. Rohit Sharma received his Ph.D. degree in computer science and guided number of M.Tech. thesis. He has also published research papers in international journal and also a reviewer of few international journals. Avinash Verma received his M.Tech. degree in Computer Science and also pursuing Ph.D. in Computer Science. He has guided various M.Tech. thesis.