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An Approach Used In Wireless
Network to Detect Denial of Service
Attack
Ms. Rashi Dhagat, Mr. Pankaj Jagtap
School Of Computer Science & Information Technology
DAVV, Indore
21-Mar-16ACM-WIR 2016
CONTENT
 Introduction
 Problem Definition
 Issue Of Existing Methods
 Detection Criteria
 Proposed Work
 Research Design
 Conclusion
21-Mar-16ACM-WIR 2016
DENIAL OF SERVICE ATTACK
Denial of service (DoS) usually refers to an attack that attempts to make a
computer resource unavailable to its intended users by flooding a network or
server with requests and data.
 It is known to network community since 1980s.
 R. T. Morris first describe concept of DoS in his paper in 1985.
 Attacker exploit this weakness by sending large vol. of data to victim system.
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ACM-WIR 2016
WHY WIRELESS?
 Wireless solutions are in great demand as organizations seek to
become more flexible and productive.
 It maintain a cost effective and competitive advantage.
 It offers mobility.
 It is also much harder to physically secure wireless network.
21-Mar-16
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ACM-WIR 2016

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security in wireless sensor networks
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This document discusses security issues and proposed solutions for wireless sensor networks. It begins by defining wireless sensor networks and describing common applications. It then outlines several security threats like denial of service attacks, wormhole attacks, sybil attacks, and traffic analysis attacks. It also discusses proposed cryptography and authentication schemes to provide data confidentiality, integrity, and freshness. Finally, it advocates for a holistic security approach that considers all network layers rather than focusing on single layers.

Overview on security and privacy issues in wireless sensor networks-2014
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Lecture Outlines Why Security is Important for WSN WSNs have many applications e.g.: military, homeland security assessing disaster zones Others. This means that such sensor networks have mission-critical tasks. Security is crucial for such WSNs deployed in these hostile environments. Why Security is Important for WSN Moreover, wireless communication employed by WSN facilitates eavesdropping and packet injection by an adversary. These mentioned factors require security for WSN during the design stage to ensure operation safety, secrecy of sensitive data, and privacy for people in sensor environments. Algorithms to achieve security services Symmetric Encryption Asymmetric Encryption Hash Function/Algorithm Digital Signature Why Security is Complex in WSN Because of WSNs Characteristics: Anti-jamming and physical temper proofing are impossible greater design complexity and energy consumption Denial-of-service (DoS) attack is difficult Sensor node constraints Sensor nodes are susceptible to physical capture Deploying in hostile environment. eavesdropping and injecting malicious message are easy Using wireless communication Why Security is Complex in WSN Because of WSNs Characteristics: maximization of security level is challenging Resource consumption asymmetric cryptography is often too expensive Node constraints centralized security solutions are big issue no central control and constraints, e.g. small memory capacity. Cost Issues Overall cost of WSN should be as low as possible. Typical Attacks to WSN Physical Attacks Environmental Permanently destroy the node, e.g., crashing or stealing a node. Attacks at the Physical Layer Jamming: transmission of a radio signal to interfere with WSN radio frequencies. Constant jamming: No message are able to be sent or received. Intermittent jamming: Nodes are able to exchange messages periodically Jamming Attack Countermeasure Physical Attacks Node Capture Attacks routing functionalities Countermeasure tamper-proof features Expensive solution Self-Protection disable device when attack detected Attacks on Routing Sinkhole attack attacker tries to attract the traffic from a particular region through it Solution: Watchdog Nodes can start to trace the source of false routing information Attacks on Routing Sybil attack (Identity Spoofing) attacker claims to have multiple identities or locations provide wrong information for routing to launch false routing attacks Solutions: Misbehavior Detection. Identity Protection Privacy Attacks Attempts to obtain sensitive information collected and communicated in WSNs Eavesdropping made easy by broadcast nature of wireless networks Traffic analysis used to identify sensor nodes of interest (data of interest), WSN Privacy Issues Cont. WSN Privacy Issues Attack Trust and reputation in WSN WSN Traditional Security Techniques Cryptographic primitive

encryption algorithmssinkhole attackprivacy
A Security Overview of Wireless Sensor Network
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This document summarizes security schemes for wireless sensor networks, including TinySec, IEEE 802.15.4, and others. It discusses the challenges of WSNs like power constraints and limited resources. It also outlines common security threats to WSNs such as denial of service attacks, attacks on information in transit, Sybil attacks, black hole/sinkhole attacks, and hello flood attacks. The document evaluates the feasibility of applying basic security schemes like cryptography and steganography to WSNs given their unique constraints and requirements.

tiny secieee 802.15.4twists
PROBLEM DEFINITION
Attack can result in abnormal conditions in network by blocking
communication in network. Since network parameter can be
changed such as
 Increase in collision rate
 Bad frame rate
 Received Signal strength
 Hardware / software fault
21-Mar-16
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ACM-WIR 2016
ISSUE OF EXISTING METHODS
 Boundary nodes cannot detect the attack.
 Does not Support threshold Technique to find parameters.
 Additional requirement Of hardware in the system profile.
 Used only for three nodes like transmitter, receiver,
attacker(xu et. al.)
 Does not differentiate the attack and fault occur at network
level.
21-Mar-16
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ACM-WIR 2016
DETECTION CRITERIA
We define the following metrics to measure the effectiveness of a
attacker:
 Packet Delivery Ratio (PDR)
 Bad Packet Ratio (BPR)
 Energy Consumption Amount (ECA)
 Signals-to-Noise Ratio (SNR)
21-Mar-16
5
ACM-WIR 2016
PROPOSED WORK
System behaviors are classified in order to create an initial
system profile and abnormalities in the network can be
identified by comparing later profiles.
 The sampled and recorded threshold levels are used later to
detect the existence of any jammer.
 The 6-Sigma method, which is a simple yet an efficient
calculation technique, has been used to determine the
threshold levels.
21-Mar-16
6
ACM-WIR 2016

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different security techniques and challenges of wireless sensor network including IEEE 802.15.4 and Zig-bee security.

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 In this method, the UCL (Upper Control Limit) and
the LCL (Lower Control Limit) is calculates to detect
initial parameters (PDR, BPR, ECA).
 PDR & BPR are used to separate these from natural
condition at network. Since BPR value is higher in
case of attack then natural condition at network.
 Energy consumed by jammer for attacking is much
higher than natural condition.
21-Mar-167ACM-WIR 2016
RESEARCH DESIGN
A detection method is developed by the help of the
parameters used in the basic attack detection method
and additional network packets.
 The detection method not only depends on the
relationship of sampled parameters in a node, but also
inquires the parameters of neighbor nodes.
21-Mar-16
8
ACM-WIR 2016
 It is based on exchanging packets between neighbor
nodes when abnormal network parameters ((PDR<
PDRThe &&ECA> ECAThe) ||(PDR< PDRThe&&
BPR> BPRThe)) are sampled.
 Node determine attack if:
 No Reply packets.
 No. of received packet is lower than no. of
neighbor.
 No. of received packet is lower than or equal to
no. of neighbor and alarm flag is detect from next
hop neighbor.
21-Mar-169ACM-WIR 2016
CONCLUSION
DOS Attack in wireless are very serious of risk for wireless
nodes that can operate in environment with limited sources.
To overcome these problems, the nodes should apply efficient
and successful policies for reliable and yet adaptive detection
mechanisms.
In this paper, we have proposed detection mechanism for
many types of attacker. The proposed algorithms can separate
network conditions caused by various types of jammers or
caused by natural sources from each other along with high
detection rate and low false positive rate.
Another advantage is that no additional hardware is required
to implement the algorithms on existing wireless nodes.
21-Mar-16
10
ACM-WIR 2016

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While wireless sensor networks face security challenges, addressing issues like confidentiality, integrity, and availability is critical for successful deployment. The document discusses these security requirements and explains how attacks can target different network layers. It provides examples of physical layer attacks like jamming and tampering. At higher layers, attacks include collisions and resource exhaustion in the data link layer, and spoofing, selective forwarding, sinkholes, Sybil attacks and wormholes in the network layer. Transport layer attacks involve flooding and desynchronization. Confidentiality, integrity, and cryptography are also discussed as important security concepts for wireless sensor networks.

security in wireless sensor network
security in wireless sensor networksecurity in wireless sensor network
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Wireless sensor networks consist of distributed autonomous devices that can monitor various environmental conditions. Securing these networks is challenging due to constraints on sensors' processing, memory, and battery power. Attacks on wireless sensor networks can target security mechanisms or routing mechanisms. Common attacks include denial of service through jamming, spoofing and altering information in transit, replication attacks, and physical node destruction. Effective security schemes must provide data confidentiality, integrity, and freshness given sensors' limitations. Developing efficient detection of compromised nodes reporting false data while ensuring holistic security in wireless sensor networks remains an important research challenge.

11011 a0449 secure routing wsn
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1) The document discusses security issues in wireless sensor networks, specifically focusing on attacks against routing protocols and potential countermeasures. It outlines common attacks like spoofing, selective forwarding, sinkhole attacks, Sybil attacks, wormholes, and HELLO flood attacks. 2) The document then provides an overview of potential countermeasures like link layer security, identity verification protocols, verification of link bidirectionality, and multipath routing. 3) Finally, the document emphasizes the importance of secure routing protocol design and highlights the need for protocols to incorporate security features to defend against insider and outsider attacks.

REFERENCE
1. W. Xu, W. Trappe, Y. Zhang, and T. Wood. “The feasibility of
launching and detecting jamming attacks in wireless networks”, In
ACM MobiHoc ’05, page to appear. ACM Press, 2005.
2. Yee Wei, L. Lodewijk, V. Hoesel, J. Doumen, P. Hartel, P.Havinga,
“Energy-Efficient Link-Layer Jamming Attacks against Wireless
ensor Network MAC Protocols”, SANS’05, November 7, 2005,
Virginia, USA.
3. Y. Law, P. Hartel, J. den Hartog, and P. Havinga. “Linklayer
jamming attacks on S-MAC,” In 2nd European Workshop on
Wireless Sensor Networks (EWSN 2005), pages 217–225. IEEE,
2005.
4. Wood, J. Stankovic, and S. Son., “JAM: A jammed-area mapping
service for sensor networks,” In 24th IEEE Real Time Systems
Symposium, pages 286- 297, 2003.
5. J. G. Proakis. Digital Communications. McGraw-Hill, 4th edition,
2000.
21-Mar-16
11
ACM-WIR 2016
6. Schleher. Electronic Warfare in the Information Age. MArtech House,
1999.
7. CrossBow Corporation, MICA2 Data Sheet [Online],
http://www.xbow.com.MICA2 data sheet.
8. S. Chebrolu, A. Abraham, J.P. Thomas, “Feature deduction and
ensemble design of intrusion detection systems”, Computers &
Security, Vol. 24, pp. 295-307, 2005.
9. P. Garcia-Teodoro, J. Diaz-Verdejo, G. Macia-Fernandez, E. Vazquez,
“Anomaly-based network intrusion detection: Techniques, systems
and challenges”, Computers & Security, Vol. 28, pp. 18-28, 2008.
10. A.D.Wood and J.A.Stankovic, “Denial of service in sensor Networks”,
IEEE Computer, 35(10):54–62, Oct.2002.
11. M. Vamsikrishna, R. Sudhakrishna ”Network Jamming Detection
Prevention Using Hidding Method ”IJCTT 2011.
21-Mar-1612ACM-WIR 2016
THANK YOU
21-Mar-16ACM-WIR 2016

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Denial of service attack

  • 1. An Approach Used In Wireless Network to Detect Denial of Service Attack Ms. Rashi Dhagat, Mr. Pankaj Jagtap School Of Computer Science & Information Technology DAVV, Indore 21-Mar-16ACM-WIR 2016
  • 2. CONTENT  Introduction  Problem Definition  Issue Of Existing Methods  Detection Criteria  Proposed Work  Research Design  Conclusion 21-Mar-16ACM-WIR 2016
  • 3. DENIAL OF SERVICE ATTACK Denial of service (DoS) usually refers to an attack that attempts to make a computer resource unavailable to its intended users by flooding a network or server with requests and data.  It is known to network community since 1980s.  R. T. Morris first describe concept of DoS in his paper in 1985.  Attacker exploit this weakness by sending large vol. of data to victim system. 21-Mar-16 1 ACM-WIR 2016
  • 4. WHY WIRELESS?  Wireless solutions are in great demand as organizations seek to become more flexible and productive.  It maintain a cost effective and competitive advantage.  It offers mobility.  It is also much harder to physically secure wireless network. 21-Mar-16 2 ACM-WIR 2016
  • 5. PROBLEM DEFINITION Attack can result in abnormal conditions in network by blocking communication in network. Since network parameter can be changed such as  Increase in collision rate  Bad frame rate  Received Signal strength  Hardware / software fault 21-Mar-16 3 ACM-WIR 2016
  • 6. ISSUE OF EXISTING METHODS  Boundary nodes cannot detect the attack.  Does not Support threshold Technique to find parameters.  Additional requirement Of hardware in the system profile.  Used only for three nodes like transmitter, receiver, attacker(xu et. al.)  Does not differentiate the attack and fault occur at network level. 21-Mar-16 4 ACM-WIR 2016
  • 7. DETECTION CRITERIA We define the following metrics to measure the effectiveness of a attacker:  Packet Delivery Ratio (PDR)  Bad Packet Ratio (BPR)  Energy Consumption Amount (ECA)  Signals-to-Noise Ratio (SNR) 21-Mar-16 5 ACM-WIR 2016
  • 8. PROPOSED WORK System behaviors are classified in order to create an initial system profile and abnormalities in the network can be identified by comparing later profiles.  The sampled and recorded threshold levels are used later to detect the existence of any jammer.  The 6-Sigma method, which is a simple yet an efficient calculation technique, has been used to determine the threshold levels. 21-Mar-16 6 ACM-WIR 2016
  • 9.  In this method, the UCL (Upper Control Limit) and the LCL (Lower Control Limit) is calculates to detect initial parameters (PDR, BPR, ECA).  PDR & BPR are used to separate these from natural condition at network. Since BPR value is higher in case of attack then natural condition at network.  Energy consumed by jammer for attacking is much higher than natural condition. 21-Mar-167ACM-WIR 2016
  • 10. RESEARCH DESIGN A detection method is developed by the help of the parameters used in the basic attack detection method and additional network packets.  The detection method not only depends on the relationship of sampled parameters in a node, but also inquires the parameters of neighbor nodes. 21-Mar-16 8 ACM-WIR 2016
  • 11.  It is based on exchanging packets between neighbor nodes when abnormal network parameters ((PDR< PDRThe &&ECA> ECAThe) ||(PDR< PDRThe&& BPR> BPRThe)) are sampled.  Node determine attack if:  No Reply packets.  No. of received packet is lower than no. of neighbor.  No. of received packet is lower than or equal to no. of neighbor and alarm flag is detect from next hop neighbor. 21-Mar-169ACM-WIR 2016
  • 12. CONCLUSION DOS Attack in wireless are very serious of risk for wireless nodes that can operate in environment with limited sources. To overcome these problems, the nodes should apply efficient and successful policies for reliable and yet adaptive detection mechanisms. In this paper, we have proposed detection mechanism for many types of attacker. The proposed algorithms can separate network conditions caused by various types of jammers or caused by natural sources from each other along with high detection rate and low false positive rate. Another advantage is that no additional hardware is required to implement the algorithms on existing wireless nodes. 21-Mar-16 10 ACM-WIR 2016
  • 13. REFERENCE 1. W. Xu, W. Trappe, Y. Zhang, and T. Wood. “The feasibility of launching and detecting jamming attacks in wireless networks”, In ACM MobiHoc ’05, page to appear. ACM Press, 2005. 2. Yee Wei, L. Lodewijk, V. Hoesel, J. Doumen, P. Hartel, P.Havinga, “Energy-Efficient Link-Layer Jamming Attacks against Wireless ensor Network MAC Protocols”, SANS’05, November 7, 2005, Virginia, USA. 3. Y. Law, P. Hartel, J. den Hartog, and P. Havinga. “Linklayer jamming attacks on S-MAC,” In 2nd European Workshop on Wireless Sensor Networks (EWSN 2005), pages 217–225. IEEE, 2005. 4. Wood, J. Stankovic, and S. Son., “JAM: A jammed-area mapping service for sensor networks,” In 24th IEEE Real Time Systems Symposium, pages 286- 297, 2003. 5. J. G. Proakis. Digital Communications. McGraw-Hill, 4th edition, 2000. 21-Mar-16 11 ACM-WIR 2016
  • 14. 6. Schleher. Electronic Warfare in the Information Age. MArtech House, 1999. 7. CrossBow Corporation, MICA2 Data Sheet [Online], http://www.xbow.com.MICA2 data sheet. 8. S. Chebrolu, A. Abraham, J.P. Thomas, “Feature deduction and ensemble design of intrusion detection systems”, Computers & Security, Vol. 24, pp. 295-307, 2005. 9. P. Garcia-Teodoro, J. Diaz-Verdejo, G. Macia-Fernandez, E. Vazquez, “Anomaly-based network intrusion detection: Techniques, systems and challenges”, Computers & Security, Vol. 28, pp. 18-28, 2008. 10. A.D.Wood and J.A.Stankovic, “Denial of service in sensor Networks”, IEEE Computer, 35(10):54–62, Oct.2002. 11. M. Vamsikrishna, R. Sudhakrishna ”Network Jamming Detection Prevention Using Hidding Method ”IJCTT 2011. 21-Mar-1612ACM-WIR 2016