ABSTRACT We propose a Essential Secret Image Sharing scheme using Linear Homogeneous Recurrence Relation and polynomials for sharing a grayscale or color secret image in the semihonest model. In our scheme, the dealer generates essential and nonessential shares of a secret image. A combiner needs shares to reconstruct the secret image, where at least are essential shares. Unlike most state‐of‐the‐art schemes restricting to be equal to , our scheme also allows for . This merit makes reconstruction possible even if up to essential shares are unavailable. Additionally, compared to state‐of‐the‐art schemes, our scheme offers substantial reductions in share sizes—by factors formed from , , , and . Thus, with this reduced size of shares, leading to reduced share storage costs, our scheme has a broader range of applications, including those with limited budgets. Moreover, in cases where , the shares generation period in our scheme, during which an adversary can potentially steal the secret image from the dealer, is at least 42% shorter than that in the state‐of‐the‐art scheme supporting .

Abstract We propose a novel secret image sharing scheme with ciphertext‐based share authentication (SISS‐CSA) for sharing grayscale and color secret images in the malicious model. In SISS‐CSA, the dealer and each participant, individually acting as a combiner, can identify each invalid share received from the malicious participant(s) before using it to reconstruct the secret image. This capability, which most comparable schemes lack, prevents reconstructing an incorrect secret image. In SISS‐CSA, the asymptotic time complexities of operations executed by the dealer in the shares generation phase and executed by each combiner in the secret image reconstruction phase are and , respectively. Here, is the number of grayscale values in the secret image, is the number of generated shares, and is the threshold number of shares required for reconstructing the secret image. These asymptotic time complexities and the size of additional information each combiner stores for identifying invalid share(s) are comparatively lesser than those in the state‐of‐the‐art schemes. Furthermore, we obtain a maximum of reduction in the size of additional information each combiner stores for share authentication using the ciphertext‐based share authentication compared to using the standard SHA‐256. To the best of our knowledge, none of the related share authentication approaches achieves this much reduction. We prove the properties of SISS‐CSA using theoretical analysis. We also provide experimental results validating the implications of theoretical analysis corresponding to asymptotic time complexities and the random nature of shares.

We explore the area of searchable encryption aiming to identify the schemes supporting multiple data owner (writers) and multiple data users (readers). Especially, we observe multi-writer multi-reader (MWMR) searchable encryption schemes focusing on multi-keyword search. However, such MWMR schemes offer a centralised token generation approach whereby an enterprise trusted authority (ETA) issues a search token to each reader in system, and thus introduce two serious issues, viz. leakage of keywords to ETA and O(q · R) communication overhead for R readers and q queries per reader. In this paper, we alleviate these issues by proposing an MWMR scheme with a decentralised token generation approach. With such an approach, a registered data reader constructs a search token without interacting with ETA and thus provides an efficient token generation with keyword privacy from ETA. Additionally, we incorporate a more expressive especially, conjunctive keyword search with the scheme. With formal security analysis, we prove that the scheme effectively stands against chosen keyword attack performed by inside or outside attacker. With theoretical and empirical analysis, we justify the effectiveness of the proposed scheme.

Internet of things (IoT) offers communication between user-to-machine and machine-to-machine. Due to their inherent characteristics of open medium, very dynamic topology, lack of infrastructure and lack of centralized management authority, IoT present serious vulnerabilities to security attacks. The routing protocol for low-power and lossy networks (RPL) does not have an inherent mechanism to detect routing attacks. Popular among these IoT attacks is blackhole attack. An attacker can exploit the routing system of RPL to launch blackhole attack against an IoT network. To secure IoT networks from blackhole attack, trust-integrated RPL protocol (TRPL) is proposed and implemented. The trust system is embedded in the RPL protocol to detect and isolate a blackhole attack while optimizing network performance. The trust is calculated from successful interaction between two nodes. The calculated trust value is considered in parent selection. TRPL demonstrates its superior performance over the standard RPL protocol and existing techniques in the detection and isolation of blackhole attacks.

When specifying user requirements, not only is it critical to ensure correct and unambiguous specification of functional requirements, but also that of Non-Functional Requirements (NFRs). A critical success factor in Requirements Engineering (RE) involves recognizing conflicts among NFRs specified by multiple stakeholders having differing concerns, priorities, and responsibilities. There indeed are numerous attempts made in the literature to resolve the conflicts between two NFRs, with the traditional view of considering the two NFRs different from each other e.g. security conflicting with the availability. In this paper, however, we propose that to introduce fine-grained conflict resolution – by also focusing on those situations where one NFR conflicts with another NFR of the same type. For ease of understanding, we propose to differentiate such conflicts by coining the term intra-conflicts. Thus, we propose fine-grained conflict resolution – by focusing on the notion of resolving conflicts between two NFRs of the same type. Needless to say, non-detection of any conflict between two NFRs – whether the NFRs are of the same type or not – at an early stage of RE, leads to higher costs for changes. The process of conflict resolution is essentially intuitive and hence is iterative. Our proposal hence is motivated by a view that differentiating the inter-conflicts with intra-conflicts, helps one in better focusing on the conflict resolution. We also propose an approach that allows a requirements analyst to semi-automatically identify intra-conflicts among NFRs at an early stage of RE using natural language processing, machine learning, and ontology-based semantic analysis. The controlled experiments, conducted on five publicly available datasets, achieve an average recall, precision, and F-measure of 0.57, 0.77, and 0.65 respectively.

Abstract The existing Key Aggregate Searchable Encryption (KASE) schemes allow searches on the encrypted dataset using a single query trapdoor, with a feature to delegate the search rights of multiple files using a constant size key. However, the operations required to generate the ciphertext and decrypt it in these schemes incur higher computational costs, due to the computationally expensive pairing operations in encryption/decryption. This makes the use of such schemes in resource-constrained devices, such as Radio Frequency Identification Devices, Wireless Sensor Network nodes, Internet of Things nodes, infeasible. Motivated with the goal to reduce the computational cost, in this paper, we propose a Revocable Online/Offline KASE (R-OO-KASE) scheme, based on the idea of splitting the encryption/decryption operations into two distinct phases: online and offline. The offline phase computes the majority of costly operations when the device is on an electrical power source. The online phase generates final output with the minimal computational cost when the message (or ciphertext) and keywords become known. In addition, the proposed scheme R-OO-KASE also offers multi-keyword search capability and allows the data owners to revoke the delegated rights at any point in time, the two features are not supported in the existing schemes. The security analysis and empirical evaluations show that the proposed scheme is efficient to use in resource-constrained devices and provably secure as compared to the existing KASE schemes.

Delegation is a technique that allows a subject receiving a delegation (the delegatee) to act on behalf of the delegating subject (the delegator). Although the existing Key Aggregate Searchable Encryption (KASE) schemes support delegation of search rights over any set of ciphertexts using a key of constant‐size, two critical issues still should be considered. Firstly, an adversary can intercept the aggregate key or query trapdoor from the insecure communication channels involving the cloud server and impersonate as an authorized user to the server for accessing the data. Secondly, the existing KASE schemes only discuss the delegation of rights from the data owner to other users. However, if a subject receiving a delegation cannot perform the time‐critical task on the shared data because of the unavailability, it becomes necessary for the delegatee to further delegate his received rights to another user. In this paper, we propose a novel KASE scheme that allows a fine‐grained multi‐delegation, i.e., if the attributes of the delegatee satisfy the hidden access policy (defined by the data owner), the delegatee can delegate his received rights to another user, without compromising data privacy. The proposed scheme provides security against the impersonation attack by verifying the user's authentication.

With searchable encryption (SE), the user is allowed to extract partial data from stored ciphertexts from the storage server, based on a chosen query of keywords. A majority of the existing SE schemes support SQL search query, i.e. 'Select * where (list of keywords).' However, applications for encrypted data analysis often need to count data matched with a query, instead of data extraction. For such applications, the execution of SQL aggregate query, i.e. 'Count * where (list of keywords)' at server is essential. Additionally, in case of semi-honest server, privacy of aggregate result is of primary concern. In this article, the authors propose an aggregate searchable encryption with result privacy (ASE-RP) that includes ASearch() algorithm. The proposed ASearch() performs aggregate operation (i.e. Count *) on the implicitly searched ciphertexts (for the conjunctive query) and outputs an encrypted result. The server, due to encrypted form of aggregate result, would not be able to get actual count unless having a decryption key and hence ASearch() offers result privacy.

The Internet of things networks is vulnerable to many DOS attacks. Among them, Blackhole attack is one of the severe attacks as it hampers communication among network devices. In general, the solutions presented in the literature for Blackhole detection are not efficient. In addition, the existing approaches do not factor-in, the consumption in resources viz. energy, bandwidth and network lifetime. Further, these approaches are also insensitive to the mechanism used for selecting a parent in on Blackhole formation. Needless to say, a blackhole node if selected as parent would lead to orchestration of this attack trivially and hence it is an important factor in selection of a parent. In this paper, we propose SIEWE (Strainer based Intrusion Detection of Blackhole in 6LoWPAN for the Internet of Things) - an Intrusion detection mechanism to identify Blackhole attack on Routing protocol RPL in IoT. In contrast to the Watchdog based approaches where every node in network runs in promiscuous mode, SIEWE filters out suspicious nodes first and then verifies the behavior of those nodes only. The results that we obtain, show that SIEWE improves the Packet Delivery Ratio (PDR) of the system by blacklisting malicious Blackhole nodes.

Recent attempts at key-aggregate searchable encryption (KASE) combine the advantages of searching encrypted data with support for data owners to share an aggregate searchable key with a user delegating search rights to a set of data. A user, in turn, is required to submit only one single aggregate trapdoor to the cloud to perform a keyword search across the shared set of data. However, the existing KASE methods do not support searching through data that are shared by multiple owners using a single aggregate trapdoor. Therefore, we propose a MULKASE method that allows a user to search across different data records owned by multiple users using a single trapdoor. In MULKASE, the size of the aggregate key is independent of the number of documents held by a data owner. The size of an aggregate key remains constant even though the number of outsourced ciphertexts goes beyond the predefined limit. Security analysis proves that MULKASE is secure against chosen message attacks and chosen keyword attacks. In addition, the security analysis confirms that MULKASE is secure against cross-pairing attacks and provides query privacy. Theoretical and empirical analyses show that MULKASE performs better than the existing KASE methods. We also illustrate how MULKASE can carry out federated searches.

The grid-based networks are formed by applications where objects being monitored form a square grid. These applications often demand critical security concerns as the compromise to the data yields adverse effects. There are indeed, several lightweight data aggregation schemes proposed in the literature that aims to minimize the resource overhead, albeit providing the required security attributes. However, as per our observations, the information about the actual deployment of the nodes is not exploited in any of these attempts. In this paper, we exploit the linearity in the deployment of grid-based networks to design an aggregation scheme that eventually entails lesser overhead as compared to the other existing schemes while offering the same level of resilience. As homomorphic encryption is considered to be more secure than obfuscation, we also propose a variant to the proposed scheme using homomorphic encryption. In the scenario with lesser restriction on computation, one can opt for the variant to the proposed scheme. The security analysis using mathematical induction and formal security proofs proves the security of the proposed scheme. To the best of our knowledge, the proposed scheme is the first that achieves privacy preservation, data verification, resilience against node capture and avoidance against collusion attacks in grid-based networks with lesser requirement of key storage and communication cost.

A Multiuser Searchable Encryption (MUSE) can be defined with the notion of Functional Encryption (FE) where a user constructs a search token from a search key issued by an Enterprise Trusted Authority (ETA). In such scheme, a user possessing search key constructs search token at any time and consequently requests the server to search over encrypted data. Thus, an FE based MUSE scheme is not suitable for the applications where a log of search activities is maintained at the enterprise site to identify dishonest search query from any user. In addition, none of the existing searchable schemes provides security against token replay attack to avoid reuse of the same token. In this paper, therefore we propose an FE based scheme, Multiuser Searchable Encryption with Token Freshness Verification (MUSE-TFV). In MUSE-TFV, a user prepares one-time usable search token in cooperation with ETA and thus every search activity is logged at the enterprise site. Additionally, by verifying the freshness of a token, the server prevents reuse of the token. With formal security analysis, we prove the security of MUSE-TFV against chosen keyword attack and token replay attack. With theoretical and empirical analysis, we justify the effectiveness of MUSE-TFV in practical applications.

A tremendous amount of personal data of an individual is being collected and analyzed using data mining techniques. Such collected data, however, may also contain sensitive data about an individual. Thus, when analyzing such data, individual privacy can be breached. Therefore, to preserve individual privacy, one can find numerous approaches proposed for the same in the literature. One of the solutions proposed in the literature is k-anonymity which is used along with the clustering approach. During the investigation, the authors observed that the k-anonymization based clustering approaches all the times result in the loss of information. This paper presents a fractional calculus-based bacterial foraging optimization algorithm (FC-BFO) to generate an optimal cluster. In addition to this, the authors utilize the concept of fractional calculus (FC) in the chemotaxis step of a bacterial foraging optimization (BFO) algorithm. The main objective is to improve the optimization ability of the BFO algorithm. The authors also evaluate their proposed FC-BFO algorithm, empirically, focusing on information loss and execution time as a vital metric. The experimental evaluations show that our proposed FC-BFO algorithm generates an optimal cluster with lesser information loss as compared with the existing clustering approaches.

Abstract In CRYPTO'13, Gentry et al. proposed the first homomorphic encryption (HE) scheme for the attribute‐based encryption (ABE). However, Gentry's scheme requires the same index for encryption of each ciphertext and supports only the key‐policy ABE. Indeed, in SECRYPT'13, Clear et al. left an open problem in the Gentry et al. scheme viz. a scheme that requires different sets of index in HE using ABE and supports the ciphertext‐policy ABE (CP‐ABE), where the sender is assumed to be intelligent. In addition, in INDOCRYPT'12, Vaikuntanathan discussed an open problem viz. to work out the HE using cryptographic techniques other than lattice‐based cryptography. With an aim to propose the CP‐ABE scheme using HE, in this research attempt, we propose an approach that integrates the benefits of HE in CP‐ABE and yet uses pairing‐based cryptography. In our approach viz. attribute‐based HE (AB‐HE), a user is able to successfully decrypt the ciphertext only if the attributes in the policy match those in the secret key. However, in addition, our approach also allows multiple invocations of multiplication operation on the ciphertext as in a typical partially HE, coupling the advantages of the partial HE in the CP‐ABE. Further, we also propose an extension of the proposed scheme that serves as a pseudo‐fully HE, but requires the help of a key authority. The security of the proposed scheme is based on the decisional bilinear Diffie–Hellman problem. To the best of our knowledge, ours is a unique attempt in integrating HE into the attribute‐based cryptography with different indexes/policies. In addition, our AB‐HE scheme is pairing‐based, and by adding more ciphertexts, it does not blow the final ciphertext size because we use the constant length ciphertext approach for the encryption. Copyright © 2016 John Wiley & Sons, Ltd.

Abstract Privacy preservation while undertaking collaborative data mining is a significant research problem. The vertically partitioned data model is an important data partition model and has varied applications. The vertically partitioned data model necessitates a non‐collusive scheme and an efficient scheme for the problem of privacy‐preserving distributed frequent itemset mining (PPDFIM). The current literature has schemes based on secure sum, set intersection cardinality and secure binary dot product (SBDP) for PPDFIM across vertically partitioned data. [m,m] Shamir's additive secret sharing has been proposed as a non‐collusive scheme for PPDFIM in a vertically partitioned setup that uses the secure sum sub‐protocol. However, such a scheme leads to information leakage in the distributed frequent itemset mining scenario and defeats the purpose of privacy preservation. We give a critique on the non‐collusive secret sharing‐based approaches when used for privacy preservation in frequent itemset mining in a vertically partitioned model. Further, we propose Du‐Atallah's efficient multiplication protocol for SBDP of two vectors for PPDFIM. We also propose an extension of the non‐collusive Du‐Atallah's SBDP protocol for a vertically partitioned setup to mine frequent itemsets for a multi‐party multi‐vector scenario. We show how such a collusion‐resistant scheme does not lead to loss of privacy and give the theoretical and empirical analysis therein. Further, we show that our proposed scheme is more efficient than the seminal public key‐based scheme proposed by Vaidyaet al.in terms of the execution cost for a multi‐party scenario. Copyright © 2015 John Wiley & Sons, Ltd.

ABSTRACT In PKC 2010, Herranz et al. proposed the first fully threshold ciphertext policy attribute‐based encryption (CP‐ABE) scheme with constant length ciphertext. However, their scheme is selectively secure with respect to the chosen plaintext attack. They have left three open problems for CP‐ABE with constant ciphertext length, that is, Security against the Chosen Ciphertext Attacks, Security Reduction to a better mathematical problem and to make the scheme Fully Secure. Indeed, in ACISP 2012, Ge et al. proposed the solutions to the first two problems but left their proposed scheme selective secure. This makes their scheme weaker because it is secure only for a particular policy. With an aim to propose a fully secure constant ciphertext length CP‐ABE scheme, in this paper, we discuss our attempts at extending the approach of Lewko et al. (in EUROCRYPT 2010). The scheme that we propose here allows any subset of attributes of the secret key as a part of the ciphertext policy. Copyright © 2013 John Wiley & Sons, Ltd.