Symmetric Key Encryption Technique: A Cellular Automata based Approach in Wireless Sensor Networks

Roy, Satyabrata; Karjee, Jyotirmoy; Rawat, Umashankar; N., Dayama Pratik; Dey, Nilanjan

doi:10.1016/j.procs.2016.02.082

Cited by 36 publications

(5 citation statements)

References 12 publications

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“…end if (38) end if (39) end for (40) that correspond to the target locations located in QR I MWSN are processed based on the exact values of μ t i,x j and/or n t i,x j , where μ t i,x j and n t i,x j denote the total data number and the qualified data number, respectively, corresponding to the location Loc t i,x j , which is supposed to be in the queried region QR I MWSN . During the procedure of processing the Data − proofPackets, the OPE-encrypted items are all removed from the original Data − proofPackets since the only use of them is to make fog nodes find out the qualified Top-k data items encrypted with the pairwise keys.…”

Section: Secure Spatial-temporal Top-k Query Processingmentioning

confidence: 99%

“…us, the computation complexity of the loop body depends on the pairwise-key encryption methods used in STQ-SCS and the total length of the data that need to be encrypted as well as the computation complexity of OPE. Although different pairwise-key cryptography methods, such as [34,37], may have different computation complexities, they are considered lightweight generally and fit for the resource-limited sensor nodes [38,39], let alone the fog nodes which are much more powerful than the sensor nodes. Moreover, OPE also has low computation complexity according to [35].…”

Section: Computation Complexity Analysismentioning

confidence: 99%

“…Decrypt all the ciphertext in RST t S i with Key i ; (7) if e end user cannot decrypt the ciphertext normally then (8) Completeness � false; return Completeness; (9) end if (10) Calculate the value of Ω i which is the total number of the queried locations in RST t S i ; (11) for j � 1 to Ω i do (12) if DPP t i,x j is not originally in RST t S i (DPP t i,x j is a Data-proof Packet corresponding to Loc t i,x j which is in QR I MWSN then (13) Completeness � false; return Completeness; (14) end if (15) Calculate the value of c t i,x j which is the total number of the sensed data items in DPP t i,x j ; ( 16) (33) if (n t i,x j is not included in DPP t i,x j in R t ) ‖ (no sensed data item in DPP t i,x j is encrypted with a sequence number) ‖ (the sequence numbers encrypted in DPP t i,x j are not sorted in ascending order from 1) ‖ (any sensed data item encrypted in DPP t i,x j is not originally encrypted with Loc t i,x j ) ‖ (E Key i μ t i,x j , Loc t i,x j is not originally included in DPP t i,x j ) then (34) Completeness � false; return Completeness; (35) end if (36) if n t i,x j � c t i,x j then (37) if c t i,x j ≠ μ t i,x j then (38) Completeness � false; return Completeness; (39) else…”

Section: Data Availabilitymentioning

confidence: 99%

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STQ-SCS: An Efficient and Secure Scheme for Fine-Grained Spatial-Temporal Top- $k$ Query in Fog-Based Mobile Sensor-Cloud Systems

Min

Liang

et al. 2021

Security and Communication Networks

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With the emergence of the fog computing and the sensor-cloud computing paradigms, end users can retrieve the desired sensory data generated by any wireless sensor network (WSN) in a fog-based sensor-cloud system transparently. However, the fog nodes and the cloud servers may suffer from many kinds of attacks on the Internet and become semitrusted, which threatens the security of query processing in the system. In this paper, we investigated the problem of secure, fine-grained spatial-temporal Top- k query in fog-based mobile sensor-cloud systems (FMSCSs) and proposed a novel scheme named STQ-SCS to tackle the problem based on the virtual grid construction and the size-order encryption-binding techniques. STQ-SCS can preserve the privacy of the sensed data items and their scores and make end users verify the completeness of the query results of fine-grained spatial-temporal Top- k queries with a 100% successful rate even if the fog nodes and the cloud servers are not totally trustworthy. Besides the good security performance, simulation results indicate that STQ-SCS is also an efficient scheme that incurs a much lower communication cost than the state-of-the-art schemes on securing fine-grained spatial-temporal Top- k query in FMSCSs.

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Section: Secure Spatial-temporal Top-k Query Processingmentioning

confidence: 99%

Section: Computation Complexity Analysismentioning

confidence: 99%

Section: Data Availabilitymentioning

confidence: 99%

See 1 more Smart Citation

STQ-SCS: An Efficient and Secure Scheme for Fine-Grained Spatial-Temporal Top- $k$ Query in Fog-Based Mobile Sensor-Cloud Systems

Min

Liang

et al. 2021

Security and Communication Networks

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“…Recently some good cryptographic algorithms using CA characteristics have been introduced [24]- [26] and they have shown comparatively better behaviors at times with the likes of DES, 2-DES etc. In this paper, a very efficient rule selection algorithm is used to generate a random sequence.…”

Section: A Significance Of Ca In Lightweight Encryptionmentioning

confidence: 99%

A Lightweight Cellular Automata Based Encryption Technique for IoT Applications

2019

Self Cite

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The Internet of Things (IoT) devices are resource-constrained devices with limitations such as low computation power, low communication capabilities, low bandwidths, high latency, and short-lived power. Therefore, securing communication among these devices is a key challenge for various sensitive applications. However, the conventional encryption and decryption algorithms, known as ciphers, cannot be implemented because of their inherent complexities of implementation and power requirements. One of the promising options available is to implement light-weight ciphers for these resource-constrained devices. Moreover, the choice of lightweight encryption tool has a great dependency on the type of IoT devices being used in an application. In this paper, a lightweight cellular automata (CA)-based cipher, named as Lightweight CA Cipher (LCC), has been proposed for IoT applications. In the proposed method, encryption is done at the perception layer, where the sensor nodes are deployed and decryption is done at the network layer where gateway devices are installed. The experimental results show that the proposed method is efficient than some of the existing ciphers like DES, 3DES when randomness, execution time, and implementation simplicity are considered as prime requirements. This cipher passes the randomness tests as prescribed by the National Institute of Standards and Technology (NIST), and it also passes all the DIEHARD tests and it establishes the security feature of LCC. Though it is specially designed for resource-constrained environments, it can be scaled up for a large number of sensor nodes.

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“…Cryptography has mainly two types. Symmetric-key cryptography (SKC) and Asymmetric-key cryptography (AKC) (Parikshit N. Mahalle & Poonam N. Railkar, 2015) (Roy & Dey 2016).…”

Section: Introductionmentioning

confidence: 99%

Lightweight Key Management for Adaptive Addressing in Next Generation Internet

Kimbahune

Deshpande

Mahalle

2017

International Journal of Ambient Computing and Intelligence

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The continuous evolution of Next Generation Internet (NGI) amplifies the demand for efficient and secure communication capable of responding effectively to the challenges posed by the emerging applications. For secure communication between two sensor nodes, a secret key is needed. Cryptographic key management is a challenging task in sensor networks as the hostile environment of sensor networks makes it more prone to attacks. Apart from resource constraints of the devices, unknown topology of the network, the higher risk of node capture and lack of a fixed infrastructure makes the key management more challenging in Wireless Sensor Network (WSN). Paper surveys different key Management schemes for WSN. The paper presents the efficiency versus security requirements tradeoffs in key management for WSN. Paper also proposes a novel key management protocol which provides strong resistance against replay attacks. The results obtained from the mathematical model based on conditional probability of the scheme suggest that the proposed key management in NGI is efficient and attack resistant.

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Symmetric Key Encryption Technique: A Cellular Automata based Approach in Wireless Sensor Networks

Cited by 36 publications

References 12 publications

STQ-SCS: An Efficient and Secure Scheme for Fine-Grained Spatial-Temporal Top- $k$ Query in Fog-Based Mobile Sensor-Cloud Systems

STQ-SCS: An Efficient and Secure Scheme for Fine-Grained Spatial-Temporal Top- $k$ Query in Fog-Based Mobile Sensor-Cloud Systems

A Lightweight Cellular Automata Based Encryption Technique for IoT Applications

Lightweight Key Management for Adaptive Addressing in Next Generation Internet

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Symmetric Key Encryption Technique: A Cellular Automata based Approach in Wireless Sensor Networks

Cited by 36 publications

References 12 publications

STQ-SCS: An Efficient and Secure Scheme for Fine-Grained Spatial-Temporal Top- k Query in Fog-Based Mobile Sensor-Cloud Systems

STQ-SCS: An Efficient and Secure Scheme for Fine-Grained Spatial-Temporal Top- k Query in Fog-Based Mobile Sensor-Cloud Systems

A Lightweight Cellular Automata Based Encryption Technique for IoT Applications

Lightweight Key Management for Adaptive Addressing in Next Generation Internet

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Product

Resources

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STQ-SCS: An Efficient and Secure Scheme for Fine-Grained Spatial-Temporal Top- $k$ Query in Fog-Based Mobile Sensor-Cloud Systems

STQ-SCS: An Efficient and Secure Scheme for Fine-Grained Spatial-Temporal Top- $k$ Query in Fog-Based Mobile Sensor-Cloud Systems