Case Study Of Misdirection Attack Computer Science Essay

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Wireless sensor network build with large number of small sized, low- cost and computable sensors, which are having limited battery power, memory, and computation power. The large numbers of small sensors are deployed to monitor any physical phenomena (i.e. temperature), to collect and process the sensed data and to send the data back to the base station. Some applications of WSN are environmental monitoring, personal healthcare, enemy monitoring, etc. But there are some issues in WSNs i.e. battery backup, security etc. Security is also a biggest concern in Wireless Sensor Networks (WSNs) especially those are deployed for military applications and monitoring. They are prone to various attacks and some of them (i.e. passive attacks) are very hazardous they are difficult to detect and defend. In this paper we have discussed the various issues and challenges in WSN followed by different attacks happen at different layer of wireless sensor network (WSN) stack with available solutions. In last we have done the case study of misdirection attack, with its impact measurement the performance of WSN.

I. Introduction

Wireless sensor nodes are low power electronic devices, deployed in remote areas, where power resources are limited. The demand of wireless sensor networks (WSN) has extended many real world applications such as environment monitoring, military applications and monitoring etc. There are some issues in WSN like limited battery power, security etc. Sometimes confidential information is being exchanged through insecure medium of WSN. The confidential information can be leaked or altered because many attacks are possible. Therefore, securing the links is important in designing a sensor network. Here we have discussed various issues and challenges in WSN. Then we have explained the various attacks happen at different layer of wireless sensor network with available solutions. A complete case study of misdirection attack is also done in with its impact measurement on the performance of WSN. Rest of the paper is organized as: section II contains literature survey having the brief discussion of related work done by various authors. The problem definition and novelty of proposed idea is discussed in section III. Various issues and challenges in WSN are discussed in section IV. Applications of WSN are discussed in section V. Different attacks corresponding to different WSN layers are discussed in section VI. Section VII contains the case study of misdirection attack followed by the conclusion in section IX.

II. literature survey

In paper [1] a topological analysis of WSN in the presence of misdirection attack is done. Authors have proposed an algorithm for the prediction of delay and throughput under the influence of misdirection attack. In paper [2] a comprehensive security model is presented for tailoring the needs of sensor networks. The authors outline the security properties that must be considered when designing a secure sensor networks. The various challenges for sensor networks are also discussed. In paper [3] various types of attacks and countermeasures related to trust schemes in WSNs are categorized. The authors present the development of trust mechanisms along with short summarization of classical trust methodologies emphasizing the challenges of trust scheme in WSNs. In paper [4] a novel approach is proposed for detecting Denial of Service (DoS) attacks in cluster-based sensor networks. This method is based on the election of controller nodes called cNodes which observe and report DoS attack activities. The role of a cNode is to analyze traffic and to send back a warning to the cluster head if any abnormal traffic is detected. In paper [5] an approach for detecting physical layer DoS jamming attack is proposed and analyzed. Authors have proposed a method called physical layer jamming identification based on residual energy where few nodes are taken as monitor nodes. They monitor the jamming attack by checking the receiver signal strength indicator and packet delivery ratio. The system performance improves in the presence of proposed method. In paper [6] an efficient technique that uses multiple base stations deployed in the network to counter the impact of black holes on data transmission is proposed in this paper. The simulation results demonstrate that this technique can achieve more than 99% packet delivery success and can identify 100% of the black hole nodes suffering from very little false positives. In Paper [7] two modifications to the Lightweight Medium Access Control (LMAC) protocol are proposed and evaluated. The first is Data Packet Separation Slot Size Randomization (DSSSR); the second is Round Robin (RR) slot size assignment. The paper shows that (DS-SSR) can increase the WSN resistance against the Energy efficient denial of service link layer jamming attacks. The paper also shows that employing RR slightly eliminates the negative impact on the network throughput when using countermeasures against energy efficient jamming. In paper [8] a survey on recent advances in WSN research area. It summarizes the special features of sensor data collection in WSNs, by comparing with both wired sensor data collection network and other WSN applications. The issues and prior solutions on the utilizations of WSNs for sensor data collection are also given. In paper [9] authors focus on security of Wireless Sensor Network. The appearance of sensor networks as one of the main technology in the future has posed various challenges to researchers. Wireless sensor networks are composed of large number of tiny sensor nodes, running separately, and in various cases, with none access to renewable energy resources. In addition, security being fundamental to the acceptance and employ of sensor networks for numerous applications, also different set of challenges in sensor networks are existed. In paper [10] authors discussed various challenges in WSN and then proposed an integrated security mechanism. It will provide security to all services of WSN. In paper [11] a novel power-efficient data fusion assurance scheme has been proposed. It uses silent negative voting mechanism. It is compared with the direct voting based fusion assurance scheme. The proposed scheme shows very good results with better power efficiency and lower network overhead. Sensor security and challenges such as wireless medium, ad hoc network deployment etc are also discussed. In paper [12] it is discussed that the security architectures used in wireless networks are not feasible due to limited resources and wireless nature. Some security threats and challenges faced by WSNs are also explained here. This paper [13] reviews the design and implementation of a novel defense strategy designed to work alongside existing DoS counter measures. The previous approaches were generic and were not capable of filtering out all attack traffic, instead a small amount of attack traffic reached the attackers intended victim. This small level of attack traffic posed a significant threat to the limited resources of WSN. Paper [14] discusses various attacks in WSN with available security mechanism along with various challenges faced. In paper [15] a survey of denial-of-service threats and counter measures is done considering wireless sensor platform resource constraints as well as the denial-of-sleep attack, which targets a battery-powered device's energy supply. The survey of denial-of-service threats is updated with current threats and countermeasures. In paper [16] the problem for some security trends over wireless sensor networks (WSNs) is investigated. A survey of recent trends in general security requirements, key distribution schemes and target localization is presented. In order to facilitate applications that require packet delivery from one or more senders to multiple receivers, provisioning security in group communications is pointed out as a critical and challenging issue. In paper [17] various anomaly detection techniques for wireless sensor networks are discussed. Some of the open issues for research related to WSN are also added. In paper [18] the security related issues and challenges in wireless sensor networks are investigated. They concluded that most of the attacks against security in wireless sensor networks are caused by the insertion of false information by the compromised nodes within the network. For defending the inclusion of false reports by compromised nodes, a means is required for detecting false reports. The development of such a detection mechanism and making it efficient is a great research challenge. In paper [19] the authors have discussed threat models and security issues faced by WSN. On the basis of the survey they motivate the need of a security framework to provide counter measures against attacks in wireless sensor networks. In paper [20] a novel algorithm for detecting a sinkhole attacker is proposed. The proposed algorithm first finds a list of suspected nodes, and then identifies the attackers in the list through a network flow graph method. Authors have also evaluated the performance of the proposed algorithm through both numerical analysis and simulations.

III. PROBLEM DEFINITION AND NOVELTY

The various issues, challenges and application of WSN are discussed. The different attacks happens at various layers of WSN stack with their available solution are discussed in detail. All these aspects of WSN we have put in a single paper and then we have done the complete study of misdirection attack along with its impact measurement on the performance of sensor network.

IV. ISSUES AND CHALLENGES IN WSN

The ad hoc nature presents significant challenges in the deployment and maintenance of wireless sensor network (WSN). A WSN has many constraint compared to other traditional networks. Some of them as discussed in [3] are:

Medium

The nodes communicating in WSN through a wireless medium are inherently less secure. In WSN eavesdropping is very simple because of its broadcast nature. Any transmitted data can easily be intercepted, altered, or replayed. The wireless medium allows an adversary to easily intercept valid packets and easily inject malicious ones.

B. Ad-Hoc Deployment

The ad-hoc nature of sensor networks means no structure can be statically defined. Due to node failure and high mobility topology changes frequently in WSN. Node deployment can be random because of dropping of node from the air.

C. Hostile Environment

Hostile environment is also a challenging factor in the functioning of sensor nodes. Sensor node can be destructed captured by enemies (attacker). Attackers can easily gain access to a sensor node due to their deployment in hostile environment. Attackers can extract confidential information (e.g. cryptographic keys) from a sensor node. This highly hostile environment represents a serious challenge for security experts and researchers.

D. Inadequate Resources

Limited resources to a sensor node pose considerable challenges to resource-hungry security mechanisms. The hardware constraints necessitate extremely efficient security algorithms in terms of bandwidth, computational complexity and memory. This is no trivial task. Energy is the most precious resource for sensor networks. Communication is especially expensive in terms of power. Clearly, security mechanisms must give some special effort to be communication-efficient in order to be energy-efficient.

E. Unattended Operation

Based on the function of the particular sensor network, the sensor nodes may be left unattended for long periods of time.

V. APPLICATIONS OF WSN

Environmental monitoring

Habitat monitoring is an important tool for assessing the threat and conservation status of species and protected areas. This can be used to get the information about the breeding pattern of birds where human cannot go because it can disturb them. This can be done at global and regional scales, where data are available.

Military surveillance

In the battle field some sensor nodes include surveillance and monitoring, guiding systems of intelligent missiles and detection of attack by weapons of mass destruction i.e. chemical or biological weapons detection.

Smart home/office

Sensors controlling appliances and electrical devices in the house are very popular these days. Better lighting and heating in office buildings.

Radiation Monitoring

Sensor helps authorities and security forces to measure the level of radiation of the affected zones without compromising the life of the workers.

Medical monitoring

Patients can wear small sensor devices that monitor their physiological data such as cancer detection, glucose, heart rate, diagnosis and monitoring. Sensor can be extremely useful for medical field.

Infrastructure protection

It includes power grid monitoring, water distribution monitoring.

Traffic Monitoring

Calculate the average speed of the vehicles which transit over a roadway by taking the time mark at two different points and reduce journey times, reduce emissions and save energy.

Miscellaneous Applications

Smart sensor node can be built into appliances at home, such as ovens, refrigerators and vacuum cleaners, which enable them to interact with each other and be remote-controlled.

VI. SECURITY REQUIREMENT FOR WSN

The following are the security requirements of a wireless sensor network [5].

A. Data Confidentiality

Confidentiality is the ability to hide messages from a passive attacker so that any message communicated via the sensor network remains confidential. Confidentiality remains the most important issue in network security. A sensor node should not reveal its data to the neighbors.

B. Data Authentication

Authentication ensures the reliability of the message by identifying its origin. Data authentication verifies the identity of the sender and receiver. Data authentication is achieved through symmetric or asymmetric mechanisms where sending and receiving nodes share secret keys. Due to the wireless nature of the media and the unattended nature of sensor networks, it is extremely challenging to ensure authentication in WSN.

C. Data Integrity

Data integrity in sensor networks is needed to ensure the reliability of the data. It refers to the ability to confirm that a message has not been tampered with, altered or changed. Even if the network has confidentiality measures, there is still a possibility that the data integrity has been compromised by alterations.

D. Data Availability

Availability depicts whether a node has the ability to use the network resources. However, failure of the base station or cluster leader's availability will eventually threaten the entire sensor network.

E. Data Freshness

Even if confidentiality and data integrity are assured, there is also a need to ensure the freshness of each message. Informally, data freshness suggests that the data is recent, and it ensures that no old messages have been replayed. To solve this problem a nonce, or another time related counter, can be added into the packet to ensure data freshness.

F. Organization of Network

For network management purpose there is no fixed infrastructure available to WSN, feature further brings a great challenge to WSN security. The absence of self organization may results a damage done by an attacker.

VII. LAYER WISE ATTACK IN WSN

There are five different layers in the layered architecture of wireless sensor network i.e. physical layer, data link layer, network layer, transport layer and application layer. The following attacks are identified at the different layers of WSN stack:

A. Attacks at Physical Layer

Following attacks are identified at physical layer:

1) Jamming: This is one of the Denial of Service Attacks in which the adversary attempts to disrupt the operation of the network by broadcasting a high-energy signal. Jamming attacks in WSNs, classifying them as constant (corrupts packets as they are transmitted), deceptive (sends a constant stream of bytes into the network to make it look like legitimate traffic), random (randomly alternates between sleep and jamming to save energy), and reactive (transmits a jam signal when it senses traffic). To defense against this type of attack, use spread spectrum techniques for radio communication. Handling jamming over the MAC layer requires Admission Control Mechanisms. Network layer deals with it, by mapping the jammed area in the network and routing around the area. Algorithms that combine statistically analyzing the received signal strength indicator (RSSI) values, the average time required to sense an idle channel (carrier sense time), and the packet delivery ratio (PDR) techniques can reliably identify all four types of jamming.

2) Tampering or destruction: Given physical access to a node, an attacker can extract sensitive information such as cryptographic keys or other private data on the node. One defense to this attack involves tamper-proofing the node's physical package. Self Destruction (tamper-proofing packages) - whenever somebody accesses the sensor nodes physically the nodes vaporize their memory contents and this prevents any leakage of information. Second - Fault Tolerant Protocols - the protocols designed for a WSN should be resilient to this type of attacks.

3) Radio interference: In which the adversary either produces large amounts of interference intermittently or persistently. To handle this issue, use of symmetric key algorithms in which the disclosure of the keys is delayed by some time interval.

B. Attacks at Data Link Layer

Following attacks are identified at data link layer:

1) Continuous Channel Access (Exhaustion): An attacker node can disrupt the MAC protocol by continuously requesting over the channel. This leads to starvation for other nodes because they are not able to access the channel during this time.

2) Collision: This is very much similar to the continuous channel attack. A collision occurs when two nodes attempt to transmit simultaneously on the same frequency. When packets collide, a change will likely occur in the data portion, causing a checksum mismatch at the receiving end. The packet will then be discarded as invalid. A typical defense against collisions is the use of error-correcting codes.

3) Unfairness: Repeated application of these exhaustion or collision based MAC layer attacks or an abusive use of cooperative MAC layer priority mechanisms, can lead into unfairness. Such an attack is a partial DOS attack, but results in marginal performance degradation. One major defensive measure against this type of attacks is the usage of small frames, so that any individual node seizes the channel for a smaller duration only.

4) Interrogation: Exploits the two-way request-to send/ clear to send (RTS/CTS) handshake that many MAC protocols use to mitigate the hidden-node problem. An attacker can exhaust a node's resources by repeatedly sending RTS messages to elicit CTS responses from a targeted neighbor node. To put a defense against such type of attacks a node can limit itself in accepting connections from same identity or use Anti replay protection and strong link-layer authentication.

5) Sybil Attack: This type of attack is very much prominent in Link Layer. First type of link layer Sybil Attack is Data Aggregation in which single malicious node is act as different Sybil Nodes and then this may many negative reinforcements to make the aggregate message a false one. Second type is voting. Many MAC protocols may go for voting for finding the better link for transmission from a pool of available links. Here the Sybil Attack could be used to stuff the ballot box. An attacker may be able to determine the outcome of any voting and off course it also depends on the number of identities the attacker owns.

C. Attacks at Network Layer

1) Sinkhole: In sinkhole attack and adversary tries to lure almost all the traffic toward the compromised node, creating a metaphorical sinkhole with the attacker at the center. Geo-routing protocols are known as one of the routing protocol classes that are resistant to sinkhole attacks, because that topology is constructed using only localized information, and traffic is naturally routed through the physical location of the sink node, which makes it difficult to lure it elsewhere to create a sinkhole.

2) Hello Flood: This attack exploits Hello packets that are required in many protocols to announce nodes to their neighbors. A node receiving such packets may assume that it is in radio range of the sender. A laptop class adversary can send this kind of packet to all sensor nodes in the network so that they believe the compromised node belongs to their neighbors. This causes a large number of nodes sending packets to this imaginary neighbor and thus into oblivion. Authentication is the key solution to such attacks and can be avoided easily by verifying bi-directionality of a link before taking action based on the information received over that link.

3) Node Capture: It is observed and analyzed that even a single node capture is sufficient for an attacker to take over the entire network. Good solution to this problem would definitely constitute a groundbreaking work in WSN.

4) Selective Forwarding/ Black Hole Attack (Neglect and Greed): WSNs are usually multi-hop networks and hence based on the assumption that the participating nodes will forward the messages faithfully. Malicious or attacking nodes can however refuse to route certain messages and drop them. If they drop all the packets through them, then it is called a Black Hole Attack. However if they selectively forward the packets, then it is called selective forwarding. To overcome this, Multi path routing can be used in combination with random selection of paths to destination, or braided paths can be used which represent paths which have no common link or which do not have two consecutive common nodes, or use implicit acknowledgments, which ensure that packets are forwarded as they were sent.

5) Sybil Attack: In this attack, a single node presents multiple identities to all other nodes in the WSN. This may mislead other nodes, and hence routes believed to be disjoint with respect to node can have the same adversary node. A countermeasure to Sybil Attack is by using a unique shared symmetric key for each node with the base station.

6) Wormhole Attacks: An adversary can tunnel messages received in one part of the network over a low latency link and replay them in another part of the network. This is usually done with the coordination of two adversary nodes, where the nodes try to understate their distance from each other, by broadcasting packets along an out-of-bound channel available only to the attacker. To overcome this, the traffic is routed to the base station along a path, which is always geographically shortest or use very tight time synchronization among the nodes, which is infeasible in practical environments.

7) Spoofed, Altered, or Replayed Routing Information: The most direct attack against a routing protocol in any network is to target the routing information itself while it is being exchanged between nodes. An attacker may spoof, alter, or replay routing information in order to disrupt traffic in the network. These disruptions include the creation of routing loops, attracting or repelling network traffic from select nodes, extending and shortening source routes, generating fake error messages, partitioning the network, and increasing end-to-end latency. A countermeasure against spoofing and alteration attacks is to append a message authentication code (MAC) after the message. Efficient encryption and authentication techniques can defend spoofing attacks.

8) Acknowledgment Spoofing: Routing algorithms used in sensor networks sometimes require Acknowledgments to be used. An attacking node can spoof the Acknowledgments of overheard packets destined for neighboring nodes in order to provide false information to those neighboring nodes. The most obvious solution to this problem would be authentication-via-encryption of all sent packets and also packet headers.

9) Misdirection: This is a more active attack in which a malicious node present in the routing path can send the packets in wrong direction through which the destination is unreachable. In place of sending the packets in correct direction the attacker misdirects those and that too towards one node and thus this node may be victimized. If it gets observed that a node's network link is getting flooded without any useful information then the victim node can be scheduled into sleep mode for some time to overcome this.

10) Internet Smurf Attack: In this type of attack the adversary can flood the victim node's network link. The attacker forges the victim's address and broadcasts echoes in the network and also routes all the replies to the victim node. This way the attacker can flood the network link of the victim. If it gets observed that a node's network link is getting flooded without any useful information then the victim node can be scheduled into sleep mode for some time to overcome this.

11) Homing: uses traffic pattern analysis to identify and target nodes that have special responsibilities, such as cluster heads or cryptographic- key managers. An attacker then achieves DoS by jamming or destroying these key network nodes. Header encryption is a common prevention technique. Using "dummy packets" throughout the network to equalize traffic volume and thus prevent traffic analysis. Unfortunately, this wastes significant sensor node energy, so use it only when preventing traffic analysis is of utmost importance.

D. Attacks at Transport layer

Following attacks are identified at transport layer:

1) Flooding: This attacker may repeatedly make new connection requests until the resources required by each connection are exhausted or reach a maximum limit. It produces severe resource constraints for legitimate nodes. One proposed solution to this problem is to require that each connecting client demonstrate its commitment to the connection by solving a puzzle. As a defense against this class of attack, a limit can be put on the number of connections from a particular node.

2) De-synchronization Attacks: An attacker repeatedly duplicates messages to the end points request transmission of missing frames. Hence, these messages are transmitted again and again. If the attacker knows the proper timing, it can prevent the end points from exchanging any information. So lots of battery power wastes. The possible solution to this attack is requiring authentication of all packets including control fields communicated between hosts. Header or full packet authentication can defeat such an attack.

E. Attacks at Application layer

Following attacks are identified at application layer:

1) Overwhelm attack: An attacker might attempt to overwhelm network nodes with sensor stimuli, causing the network to forward large volumes of traffic to a base station. This attack consumes network bandwidth and drains node energy. We can mitigate this attack by carefully tuning sensors so that only the specifically desired stimulus, such as vehicular movement, as opposed to any movement, triggers them. Rate limiting and efficient data-aggregation algorithms can also reduce these attacks' effects.

2) Path-based DOS attack: It involves injecting spurious or replayed packets into the network at leaf nodes. This attack can starve the network of legitimate traffic, because it consumes resources on the path to the base station, thus preventing other nodes from sending data to the base station. Combining packet authentication and anti replay protection prevents these attacks.

3) Deluge (reprogram) attack: Network programming system let you remotely reprogram nodes in deployed networks If the reprogramming process isn't secure, an intruder can hijack this process and take control of large portions of a network. It can use authentication streams to secure the reprogramming process.

TABLE I

ATTACKS AT DIFFERENT LAYERS OF WSN STACK

Layer

Attack

Physical Layer

Jamming, Tampering, Sybil Attack, Interceptions

Data Link Layer

Collision, Sybil Attack, Spoofing and Altering Routing Attack, Exhaustion, Unfairness, Replay Attack, Traffic Analysis, Monitoring

Network Layer

Internet Smart Attack, Sybil Attack, Black hole Attack, Spoofing and Altering Routing Attack, Wormhole Attack, Selective Forwarding Attack, Hello flood Attack, Neglect and Greed, Homing, Misdirection Attack, Byzantine

Transport Layer

Flooding Attack, Desynchronization

Application Layer

Spoofing and Altering Routing Attack, False Data Injection

VIII. MISDIRECTION ATTACK: A CASE STUDY

In misdirection attack the attacker routes the packet from its children node to other distant nodes, but not necessarily to its legitimate parent node. This produces long delay in packet delivery and further decreases the throughput of the network [1].

A. Misdirection attack can be performed as

In the presence of misdirection attack packets reach to the destination but not from the original route, from a different route which further produces long delay.

Figure 1. Normal flow of Packets

Figure 1 shows the simulation scenario for normal flow of packets. S1, S2,----- S12 are sensor nodes, sensing any physical phenomenon and send sensed data packets to router R1,R2 and R3. Router R1, R2 and R3 further send this data to the base station (Co).

Figure 2. Flow Packets when R1 becomes Attacker

Figure 2 shows the simulation scenario for flow of packets when router R1 becomes misdirection attacker. Packets are misdirected towards R3 by the malicious node R1. The traffic coming from R3 has the packets of R3 and R1. So packets of R1 are reached to the base station (Co) with some delay. Thus traffic received (bps) at base also reduces.

B. Simulation Design and Results

We have done the simulation of misdirection attack, the both scenario are as shown in figure 1 and 2.

1) Simulation Parameters: We have taken the following simulation parameters:

TABLE II

PARAMETERS USED IN SIMULATION

Parameter

Value

Area

500x500 met (Fix)

Network Size

Normal Flow

12 Sensor Nodes

03 Routers with normal flow

01 Coordinator

Attacking Scenario

12 Sensor Nodes

02 Routers with normal flow

01 Router (R1: misdirection node)

01 Coordinator

Topologies

Tree

Simulation Time

60 Minutes

Packet Inter- Arrival Time (sec)

Constant (1)

Packet Size (bits)

Constant (1024)

CSMA/CA Parameters

Default

Sensing duration (sec)

0.1

2) Results: During the simulation we have compute the effect of misdirection attack on the performance of WSN. The following results are obtained:

TABLE III

TRAFFIC RECEIVED (bps) AT BASE (Co)

 

Normal Flow

Attack

Traffic Received (bps)

2979.84

1989.40

Figure 3. Traffic Received (bps) at base station (Co)

Figure 3 shows the traffic received (bps) at base station under normal flow and misdirection attack.

IX. CONCLUSION

We have discussed the various issues and challenges in WSN. The different attacks corresponding to different layers of WSN stack with available solutions are also discussed. In last we have done the case study of misdirection attack, with its impact measurement the performance of WSN. During the simulations we have observed that the traffic received (bps) at base station reduces to 990.44 bps is a drastic decrement which further degrades the performance of network.

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