Key Management in IP-based Ubiquitous Sensor Networks: Issues, Challenges and Solutions Mustafa Hasan, Ali Hammad Akbar, Rabia Riaz*, Subir Biswas, Ki-Hyung Kim1 Seung W. Yoo, and Byeong-hee Roh Graduate School of Information and Communication, Ajou University, Suwon, 443-749, South Korea {hasan, hammad, subir, kkim86,swyoo,bhroh}@ajou ac kr, *rabiaiqbal18@gmail com

Abstract. As wireless sensor networks continue to grow, so does the need for effective security mechanisms. Because sensor networks may interact with sensitive data and/or operate in hostile unattended environments, it is imperative that these security concerns be addressed from the beginning of the system design. However, due to inherent resource and computing constraints, security in sensor networks poses different challenges than traditional network/computer security. In this paper, we focus on the key management issues in IP-based ubiquitous sensor networks. 6LoWPAN (IPv6 over Low Power Personal Area Network) is analyzed for its vulnerability to security threats and suitable security mechanisms. Our analysis ascertains that the preassigned key-based security is prone to failures. Such networks need a dynamic key management mechanism to establish a secure communication. For the sake of analysis, we select one of the possible key management solutions in 6LoWPANs—the Public Key Infrastructure (PKI) based Elliptic Curve Cryptography (ECC). We deliberate on its efficacy by mapping it onto an application scenario. We compare ECC in 6LoWPANs against the classical implementation of PKI based ECC in sensor networks and put forth our analysis.

1

Introduction

Ubiquitous sensor networks are quickly gaining popularity due to the fact that they are potentially low cost solutions to a variety of real-world challenges [1]. It becomes more and more important in various application areas, and several application scenarios require connectivity between sensor networks and the Internet. Such scenarios lead to the evolution of IP-based ubiquitous sensor networks (or equivalently IP-USN). Especially interesting point in ubiquitous sensor networks is their integration with IPv6 networks, giving advantages such as a) huge address space suitable to adapt to a large sensor nodes, b) providing built-in auto-configuration via IPv6 neighbor discovery mechanism and c) IPv6 stateless address auto-configuration. The resulting envisioned growth in the utilization of sensor networks pledges a wide 1

Corresponding author

variety of crucial applications ranging from healthcare to warfare, which in turn stimulate numerous efforts to secure these networks. For such applications, there is a burgeoning need to enforce proper security mechanisms. Whether IP-USNs are being deployed in hostile situations or commercial environments, security becomes exceedingly important. These networks are prone to unprecedented, malicious attacks. For example, an adversary can easily eavesdrop to the radio transmissions, impersonate to be one of the network nodes, or intentionally provide misleading information to other wireless nodes. In order to provide security, the communication should be encrypted and authenticated as much as possible. Therefore, an open research problem is “how to bootstrap secure communication among sensor nodes?” More technically speaking, how the secret keys are set up among communicating nodes? This key agreement problem is a part of the key management issue, which has been widely studied in both wired and wireless network environments. As we summarize later, the research and development are still in infancy for USN. In this paper, an attempt is made to define the requirements for a “close-to-utopian” solution for key management in the IP-USN. In this paper we first define the scope of this paper. Second, we discuss our choice of 6LoWPAN as a standardized IP-USN with respect to its security analysis. Third, the possible security threats to 6LoWPAN are presented. Fourth, we critique the possible key management mechanisms for ensuring an acceptable level of security in 6LoWPANs. Some of the significant works in the popular Public Key Infrastructure (PKI) is analyzed for code size-complexity vs. performance feasibility for 6LoWPAN.

2

Scope

The main motivation of this paper is to determine a viable security solution for the IPUSN. The link layer specifications for 6LoWPAN are based on the IEEE 802.15.4 specification, which already provides four basic security services; access control, message integrity, message confidentiality, and replay protection [3]. However, in order to use these security services, the need to have a secret key between the sender and receiver is not undermined. In other word, to use cryptography, both communicating endpoints need to agree on a key or a pool of keys to communicate securely. In this paper, we have presented a key management solution for 6LoWPANs in the presence of resource constraints.

3

6LoWPAN

6LoWPAN is a standardization work of IETF (Internet Engineering Task Force) for IP-USN technologies. It deals with the problem statements, packet format, routing protocols, etc. for low power wireless devices. It comprises devices that conform to the IEEE 802.15.4-2003 standard. IEEE 802.15.4 compliant devices are characterized by short range, low bit rate, low power and low cost. 6LoWPAN has some of the characteristics that conflict with those of existing IP networks such as

small packet size versus the 1,500-bytes Maximum Transmission Unit (MTU) for IPv6, an availability of low bandwidth and a very large number of devices with limited operating space and lifetime. The gateway-based architecture of 6LoWPAN is poised to realize a seamless IPv6 connectivity to IEEE 802.15.4 devices as shown in the Figure 1.

Fig. 1. Connectivity paradigm of 6LoWPAN devices. 3.1

6LoWPAN Security Analysis

The security aspect, in 6LoWPAN is a costly proposition, both in terms of code size and number of transmissions of security primitives. For instance, while placing IPv6 on top of IEEE 802.15.4, it may seem that one could use a more thorough IPv6 security doing away with the security of WPAN since the security architecture defined by IEEE 802.15.4 offers duplication. Below, we elaborate upon the possible security solutions available in and out of the 6LoWPAN suite that we may opt to use. 3.1.1 IP Security Analysis IPSec (IP security protocol) provides per-packet authenticity and confidentiality; guarantees between peers communicate using IPSec [4]. It is available for both IPv4 and IPv6. Basically, IPSec is designed for generalized IP nodes that operate over Ethernet. It means that each node has enough buffers at its disposal, an undeterred bandwidth and no battery limitations like 6LoWPAN. So, IPsec per se is not suitable for the 6LoWPAN network. Obviously other issues such as different operating modes of 6LoWPAN devices such as Full Function Device (FFD) or Reduced Function Device (RFD), and routing peculiarities such as coordinator assisted hierarchical routing makes the adoption of IPsec less desirable. 3.1.2 IEEE 802.15.4 Security Analysis The Medium Access Control (MAC) sublayer of IEEE 802.15.4 provides security services through the MAC PAN Information Base (PIB) which maintains an Access Control List (ACL). IEEE 802.15.4 MAC provides the frame security with a set of optional services, as and when the application requires. Due to the diversity of applications envisioned by IEEE 802.15.4, the processes of authentication and key

exchange are left to the implementor’s discretion. Thus we can say that IEEE 802.15.4 takes a rather open-ended approach to define the security suite and settings.

4.

Security Threats and Vulnerabilities of 6LoWPAN

Most of the attacks and threats against user and data security in IP based USN are almost similar to their counterparts in the wired domain, while some are exacerbated with the inclusion of vulnerabilities in wireless connectivity. Wireless networks are usually more vulnerable to various security threats as the unguided transmission medium is more susceptible to security attacks. In fact, we consider all the wireless and ad hoc wireless attacks as applicable equally for IP based USN plus some critical attacks especially targeted at them. Broadly categorizing, two different perspectives can be assigned to attacks. One is the attack against the security mechanisms and another is against the basic mechanisms (like routing mechanism). Some of the major attack can be depicted as follows. 4.1

Denial of Service

Denial of Service (DoS) [7,8] attack initiates to fail the nodes to perform their primary job, unbeknownst. The simplest DoS attack tries to exhaust the resources that are available to the victim node, by sending fake request packets to prevent the legitimate users from accessing services they are entitled to. In wireless environment, several types of DoS attacks can be triggered in different layers. At the Physical Layer, the DoS attacks could be tempering and jamming electromagnetic (EM) signals. At the Link Layer, it could be collision and contention. At the Network Layer, it could be the swarming of packets for network traffic during homing and at the Transport Layer this attack could be performed by half open and half close attacks. Especially, for the IP based USN, there are possibilities of DoS attacks through the internet connectivity at the Network Layer. There is also susceptibility to the Physical Layer DoS attacks because of unattended deployment and limited communication/computation resources. For example, one laptop can easily disrupt the communication of several sensor nodes by swarming their transceivers. 4.2

Physical Attacks

Sensor networks typically operate in vast outdoor environments. In those kinds of environments, the small sensors, with the unattended and distributed nature makes those highly susceptible to physical attacks, i.e., threats due to physical node destruction relocation and masking [9]. By the Physical attacks, sensors nodes can be condemned permanently, so the losses are irreversible. For instance, attackers can extract cryptographic secrets from the associated circuitry, modify programming in the sensors, and the malicious node can take control over them [10]. Some of the works have shown that standard sensor nodes, such as the MICA2 motes, can be compromised in less than one minute [11]. These compromises can result into code

modification inside the sensor node to change the mission-oriented roles of full fledged networks, let alone sensors. 4.3

Sybil Attack

Some sensor nodes might need to work together to execute a complete task, hence there is a burgeoning need to distribute subtasks and ensure redundancy of information. In this kind of situation, a node can pretend to be more than one node, using the identities of other sensors. Sybil attack can be performed for attacking the distributed storage, routing mechanism, data aggregation, voting, fair resource allocation and misbehavior detection, etc [12]. It’s not very easy to be aware of a Sybil attack in place, but measuring the usage of radio resources, the Sybil attacks may be detected, though with very little probability. 4.4

Black hole / Sinkhole Attack

In the Black Hole attack, a malicious node acts as a black hole [13] to attract all the traffic in the sensor network. Especially in a flooding based protocol, the attacker listens to requests for routes then replies to the requesting nodes that it contains the high quality or shortest path to the base station. Once the malicious device is able to insert itself between the communication nodes, it is able to do anything with the packets passing through it. In fact, this attack can affect even the nodes those are spatially farther from the malicious node. 4.5

Hello Flood Attack

Hello Flood attack as introduced in [14], uses HELLO packets as a mechanism to redraw the attention of the sensors in USN. In this sort of attack, an attacker with a high radio transmission range and processing power sends HELLO packets to a number of sensor nodes which are dispersed in a large area within a USN. The sensors are thus persuaded that the adversary is their neighbor. As a consequence, while sending the information to the base station, the victim nodes try to send their data through the attacker as they know that it is their neighbor and are ultimately spoofed by the attacker. 4.6

Wormhole Attack

In the Wormhole attack [15] the attacker records the packets (or bits) at one location in the network and tunnels those to another location. Such attacks can be fatal to the working for the USN, since, this sort of attack does not require compromising a sensor in the network; rather it could be performed even at the initial phase when the sensors start to discover the neighboring information.

5.

Purported Keying Models for the 6LoWPAN

The characteristics of sensors, communicating devices and resulting sensor networks, such as limited resources at the node and network level, lack of physical protection, unattended operation, and a close interaction with the physical environment, all make it infeasible to implement some of the most popular key exchange techniques in their literal forms for 6LoWPANs. In this section, we visit the three widely known schemes such as trusted-server scheme, pre-distribution scheme and public key cryptography schemes in order to reach to a pragmatic key management mechanism for 6LoWPANs. 5.1

Trusted-Server Scheme

The trusted-server scheme relies solely on the server for key agreement between nodes, e.g., Kerberos [16]. If the server is compromised, the trust amongst sensor nodes is severed. Such a scheme is not suitable for sensor networks because there is usually no guarantee of communicating seamlessly with a trusted server at all the times in sensor networks. 5.2

Key Pre-Distribution

The key agreement scheme is key pre-distribution, where key information is distributed among all sensor nodes prior to deployment. If the network deployers were to know which nodes were more likely to stay in the same neighborhood before deployment, keys may be decided a priori. However, because of the randomness of the deployment, knowing the set of neighbors deterministically might not be feasible. Furthermore, the presence of intruder nodes right from the network deployment and initiation time cannot be rejected outright as implausible. Some schemes like network shared keying, pair-wise keying, and group keying, have been defined as variants of key distribution. On-site key management mechanisms, while warranting the same level of security as key pre-distribution schemes have an obvious edge to cope up with network dynamics. 5.3

Public Key Cryptography Scheme

This class of key management scheme depends on asymmetric cryptography, such as public key certificates that are irreversible singularly. This irreversibility comes at a price—often staked by the limited computation and energy resources of sensor nodes. Some of the most popular examples include, but are not limited to Diffie-Hellman key agreement [17] or RSA [18], and [19]. However, the cryptanalysis of public key schemes reveals that they are uncontested cryptographic champions.

6. An Insight into Resource Utilization of Applications on 6LoWPAN Devices—The First Step Towards Making Security Feasible The implementation of IP-USN (6LoWPAN) security requires the analysis of the allowable resources that can be allocated for the security purpose. This activity shall enable us to determine a key exchange mechanism to establish substantial security in 6LoWPANs. In this section, we analyze some 6LoWPAN applications with respect to their implementation cost and permissible delay bounds. 6.1 6LoWPAN Applications To analyze the resource constraints, we visit applications developed thus far using 6LoWPAN. For the 6LoWPAN applications we used a true single-chip 2.4 GHz IEEE 802.15.4 compliant RF transceiver with base-band modem (commonly the Chipcon® CC2420DB chipset). As an operating system, we use our own implementation of the 6LoWPAN stack. Chipcon CC2420DB devices use 8-bit microcontroller with advance RISC architecture, 128K Bytes of In-System Reprogrammable Flash (ROM), 4K Bytes EEPROM (RAM) and 4K Bytes Internal SRAM (RAM). Our 6LoWPAN working group at Ajou University has developed a weather forecasting system, a location tracking system and a wind sensor management system. These applications are inherently insecure since the clients did not specify any security measures. We analyze some of the resources that are necessary and crucial to the implementation of a viable security system, such as used and available flash memory, RAM, and parameters as local processing time per node, and application-specific maximum allowable refresh time to update the sensed data. Table 2 is the fact sheet. For example, typical usage is around 4 KB of RAM and 100 KB of ROM in general. The trends of application resource usage suggest that resources are never overloaded. We can, therefore dedicate at least 2 KB of RAM and 20 KB of flash memory for the security implementation. Likewise, the variance of transmission delay and processing time for all the applications together allow a tolerance, say 500 ms to the least. After analyzing resource in hand and the popular key exchange methods, we recommend to use the trusted public key cryptography.

6LoWPAN Applications Used RAM Used ROM Processing time Transmission delay Weather Forecasting Location Tracking Wind Sensor Management

2KB 3KB

83KB 91KB

1s 0.7s

80ms 500ms

3 KB

80KB

0.9s

4s

Table 2. Resource and delay fact sheet for some 6LoWPAN applications

6.2 Public-Key Infrastructure for Key Distribution Based on Elliptic Curve Cryptography The public key scheme has been investigated extensively for sensor networks and can fulfill most if not all the security requirements. Public-key cryptography is more flexible and simple in rendering a clean interface for the security component. Against the popular belief that a public key scheme is not practical for sensor network, few working groups argue that this can be a good scheme with simple modification of Elliptic Curve Cryptography (ECC). One working group at Harvard University deployed the PKI by modifying ECC and getting very exciting results in TinyOS [20]. Another working group worked on the TelosB and they showed favorable results too in [21]. Since IEEE 802.15.4 AES security mechanism has no support for group keying or shared keying mechanisms, we assert that PKI may be favorable for 6LoWPAN. 6.3

PKI based ECC Implementation

In this section, we briefly give a background introduction about ECC, and corresponding elliptic curve Diffie-Hellman and Digital Signature Algorithm. 6.3.1

Elliptic Curve Cryptography

In recent years, ECC has attracted much attention as a security solution for wireless networks due to a very small key size and low computational overhead. ECC can use a considerably shorter key and offer the same level of security as other asymmetric algorithms using much larger ones. The gap between ECC and its competitors in terms of key size required for a given level of security becomes dramatically more prominent at higher levels of security, e.g. 160-bit ECC offers the comparable security to 1024-bit RSA and 512 bit ECC provides security of the level of 15,360 bit RSA. 6.4 Summary of Experimental Results on Other OS and Performance Analysis For our analysis, we selected four popular implementation of ECC in sensor networks. 6.4.1

TelosB Based on Hardware Multiplier

TelosB mote (TPR2400) is the latest product in the mote family designed by University of California at Berkeley for experimentation in sensor network research. The experiments based on TelosB mote show that it takes 3.3s and 6.7s to conduct a public key signature and verification respectively. This gives us a positive and feasible result for the sensor network for applications that are delay-tolerant.

6.4.2

TinyOS Based EccM 1.0 and EccM 2.0

EccM1.0 and EccM 2.0 are two versions of Ecc implementation on the MICA2 in the form of TinyOS Module at Harvard University. EccM 1.0 was designed for execution on a single mote. It first selects a random curve in the form of an equation. It next selects from that curve a random point, G. It further selects at random some k, the node's Private Key. Finally, it computes k.G, the node's public key. The running time of these operations is then transmitted to the node's UART. The results obtained for 33-bit keys required a running time of approx. 1.8 s. The delay performance however degrades for key lengths exceeding 63-bits. EccM 2.0 removes the shortcomings in EccM1.0 with index-calculus methods [23]. Table 3 summarizes the implementation details. According to 6LoWPAN’s resource analysis, this comparative result shows that, a modification to ECC may be feasible for the sensor network, especially for the 6LoWPAN. Implementation

TelosB

EccM 1.0

EccM 2.0

TinyEcc

Total Time

Private Key

.0.07s

0.36s

0.229s

0.161s

Public Key

10.19

54.114s

34.161s

24.5s

N/A

0.00549j

0.00549j

ROM

13.8k

18k

34.3k

12.5k

RAM

1.3k

0.8k

1k

1.3k

Total Energy

M emory

N/A

Table 3. Comparison of popular PKI implementations.

7. Conclusion In this paper, we consider 6LoWPAN network as a specific example of IP-USN. Various application scenarios of 6LoWPANs, their likely threats, and possible security solutions are discussed. We short listed solutions for 6LoWPAN security implementation by analyzing the resources in hand after allocating the resources for various applications. In this paper we showed the competitive scenario of the other implementations, and also some guidelines for making security viable for any application. We also considered dynamic shared key approaches in order to analyze the best performance of the system. Such schemes may also be feasible for 6LoWPANs incase a priori information about the topology, mission, and operating conditions of a sensor network is available to the implementors.

Acknowledgement This work was supported through IT Leading R&D Project in part by MIC & IITA of Korea.

Reference [1] Wenliang Du, Jing Deng, Yunghsiang S. Han, Shigang Chen, and Pramod K. Varshney, “A Key Management Scheme for Wireless Sensor Networks Using Deployment Knowledge” 2003. [2] ZigBee Alliance, http://www.zigbee.org/ [3] Naveen Sastry and David Wagner, "Security Considerations for IEEE 802.15.4 Networks” WiSE’04, October 1, 2004, Philadelphia, Pennsylvania, USA. [4] S. Daniel Park, K. Kim, E. Seo, S. Chakrabarti, “IPv6 over Low Power WPAN Security Analysis,” draft-daniel-6lowpan-security-analysis-01.txt, IETF draft, June, 2006 [5] T. Aura, “Cryptographically Generated Addresses (CGA),” IETF RFC3972, March 2005 [6] J. Arkko, J. Kempf, B. Zill, P. Nikander, “ SEcure Neighbor Discovery (SEND), ” IETF RFC3971, March 2005 [7] Blackert, W.J., Gregg, D.M., Castner, A.K., Kyle, E.M., Hom, R.L., and Jokerst, R.M., “Analyzing interaction between distributed denial of service attacks and mitigation technologies”, Proc. DARPA Information Survivability Conference and Exposition, Volume 1, 22-24 April, 2003, pp. 26 – 36. [8] Wang, B-T. and Schulzrinne, H., “An IP traceback mechanism for reflective DoS attacks”, Canadian Conference on Electrical and Computer Engineering, Volume 2, 2-5 May 2004. [9] X. Wang, W. Gu, K. Schosek, S. Chellappan, and D. Xuan. Sensor network configuration under physical attacks. Technical Report Technical Report (OSU-CISRC-7/ 04-TR45), Dept. of Computer Science and Engineering, The Ohio-State University, July 2004. [10] X. Wang, W. Gu, S. Chellappan, Dong Xuan, and Ten H. Laii. Search-based physical attacks in sensor networks: Modeling and defense. Technical report, Dept. of Computer Science and Engineering, The Ohio-State University, February 2005. [11] C. Hartung, J. Balasalle, and R. Han. Node compromise in sensor networks: The need for secure systems. Technical Report Technical Report CU-CS-988- 04, Department of Computer Science, University of Colorado at Boulder, 2004. [12] Newsome, J., Shi, E., Song, D, and Perrig, A, “The sybil attack in sensor networks: analysis & defenses”, Proc. of the third international symposium on Information processing in sensor networks, ACM, 2004, pp. 259 – 268. [13] Culpepper, B.J. and Tseng, H.C., “Sinkhole intrusion indicators in DSR MANETs,” Proc. First International Conference on Broad band Networks, 2004, pp. 681 – 688. [14] Karlof, C. and Wagner, D., “Secure routing in wireless sensor networks: Attacks and ountermeasures”, Elsevier's Ad Hoc Network Journal, Special Issue on Sensor Network Applications and Protocols, September 2003, pp. 293-315. [15] Hu, Y.-C., Perrig, A., and Johnson, D.B., “Packet leashes: a defense against wormhole attacks in wireless networks”, Twenty-Second Annual Joint Conference of the IEEE Computer and Communications Societies. IEEE INFOCOM 2003, Vol. 3, 30 March-3 April 2003, pp. 1976 – 1986. [16] P. Gaudry, F. Hess, and N. P. Smart, “Constructive and Destructive Facets of Weil Descent on Elliptic Curves,” tech-reports/2000/2000-gaudry.ps.gz, Department of Computer Science, University of Bristol, Tech. Rep. CSTR-00-016, October 2000. [17] W. Diffie and M. E. Hellman, “New directions in cryptography,” IEEE Transactions on Information Theory, vol. 22, pp. 644–654, Nov. 1976. [18] R. L. Rivest, A. Shamir, and L. M. Adleman, “A method for obtaining digital signatures and publickey cryptosystems,” Communications of the ACM, vol. 21, no. 2, pp. 120–126. [19] A. Perrig, R. Szewczyk, V. Wen, D. Cullar, and J. D. Tygar, “Spins: Security protocols for sensor networks,” in Proceedings of the 7th Annual ACM/IEEE Internation Conference on Mobile Computing and [20] David J. Malan, Matt Welsh, Michael D. Smith, “A Public-Key Infrastructure for Key Distribution in TinyOS Based on Elliptic Curve Cryptography,” 2005. [21] Haodong Wang, Bo Sheng, and Qun Li, “TelosB Implementation of Elliptic curve Cryptography over Primary Field”, WM-CS Technical Report (WM-CS-2005-12). [22]Dragongate Technologies Limited. jborzoi 0.9. http://dragongate-technologies.com/products.html, August 2003. [23] Alfred Menezes, Scott Vanstone, and Tatsuaki Okamoto. “Reducing elliptic curve logarithms to logarithms in a finite field,” In Proceedings of the twenty-third annual ACM symposiumon Theory of computing, pages 80-89. ACM Press, 1991.

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