The ISC International Journal of Information Security

Abstract The wireless communication with delivering variety of services to users is growing rapidly in recent years. The third generation of cellular networks (3G), and local wireless networks (WLAN) are the two widely used technologies in wireless networks. 3G networks have the capability of covering a vast area; while, WLAN networks provide higher transmission rates with less coverage. Since the two networks have complementary properties, some attempts are made for their integration which could lead to an advantageous heterogeneous network. In such a heterogeneous network, provision of services like authentication, billing and quality of service are essential. In this article, a new mutual authentication protocol, namely, Non-Reputation Billing Protocol (NRBP) is proposed based on extensible authentication protocols. This authentication scheme provides a non-repudiation property for the billing problem. The proposed scheme is analyzed based on different security features and computation overhead. In comparison with previous approaches, this protocol contains all the considered security parameters. Moreover, the computation overhead of this protocol is less than other schemes.

Abstract Nowadays, the growth of virtual environments such as virtual organizations, social networks, and ubiquitous computing, has led to the adoption of trust concept. One of the methods of making trust in such environments is to use a long-term relationship with a trusted partner. The main problem of this kind of trust, which is based on personal experiences, is its limited domain. Moreover, both parties of such trust relationship will face big problems of collecting data and forming reasonable and reliable beliefs. Considering the concept of "group" in modeling trust is a way to overcome the above mentioned problems. Since, group-based trust is more suited with the nature of trust in new virtual environments. In this paper, a new trust model called "GTrust" is proposed in which trust is considered as a collective and shared feature of all group members. Therefore, group membership is used as the judgment criteria regarding a person's expected behavior and how he can be a trustee. GTrust is based on Metagraphs which are graphical data structures for representing a collection of directed set-to-set mappings. We show that by using GTrust, large trust spaces between unknown individuals can be shaped effectively. The proposed model not only offers a better description of human sense of trust when considering communities, but also provides the setting for evaluating the trust of individuals whom we do not know, and therefore provides an extended evaluation domain.

Abstract This paper analyses the security and efficiency of some notable privacy preserving data aggregation schemes, SP2DAS, 3PDA, and EPPA. For SP2DAS and 3PDA schemes, We show that despite the designers’ claims, there are efficient forgery attacks on the signature scheme used. We present a
selective forgery attack on the signature scheme of SP2DAS in the key-only attack model and a selective forgery attack on the 3PDA’s signature scheme in the known-message attack model,
requiring only two pairs of message-signature. These attacks enable the attacker to inject any arbitrary faulty data into the data aggregated by the network, without being detected, which is a serious threat to the performance of the whole network.
We also present an improved version of the broadcast encryption scheme used in EPPA scheme, in which the decryption key is half, the decryption complexity is half, and the ciphertext size is 3=4 of the original one. The semantic security of the proposed scheme is proved under the same assumption as the original scheme.

Abstract This article presents new methods and tools used in the field of text analysis to identify fake news in the media. The problem with the research is that, as a rule, to identify fakes, a training dataset is required, on which thematic fakes were tested. This is not always feasible and requires additional resources. To solve this problem, a comprehensive research methodology has been developed that covers most detection tools, even in the absence of an established database containing reliable and fake news. The study includes a combination of various algorithms combined into a single analytical structure, presented in the work in the form of pseudocode. The authors introduce the concept of an "emotional fake model" similar to individual emotions included in a broader emotional spectrum. The essence of the model is to evaluate fakes based on the structure of definitions of emotions formed in fakes, which differ from the original signals due to different weight coefficients. The innovation involves a two—stage identification of fakes - initially clusters of messages from the text corpus are identified, and then, based on text analysis tools, their linguistic features and emotional differences are revealed (based on a set of emotions POMS). In the context of creating fake news using neural networks, emotional coloring plays a crucial role, providing a permanent foundation that can serve as a cornerstone for identification.

Abstract In Ciphertext-Policy Attribute-Based Encryption (CP-ABE) schemes, an access structure is sent with each ciphertext to specify the intended recipients. This design can reveal sensitive information about the encrypted data and its recipients. Moreover, it may introduce new security concerns regarding user privacy. Policy-hiding CP-ABE schemes have been proposed to address this challenge and protect user privacy. In this paper, we present the cryptanalysis of two policy-hiding CP-ABE schemes. For the first scheme, we demonstrate that it leaks attribute value information through the ciphertext. An adversary can exploit this flaw to perform an offline dictionary attack, revealing the attribute values used in the access structure, and thereby exposing the entire access structure. For the second scheme, we show that its security is compromised due to the improper establishment of the decryption key component utilized in the attribute matching phase. Data users can exploit the secret key components used in the attribute matching phase to decrypt any ciphertext, regardless of their attribute set.

Abstract In the last two decades bilinear pairings have found many applications in cryptography. Meanwhile identity-based cryptosystems based on bilinear pairings have received particular attention. The IEEE, IETF, and ISO organizations have been working on standardization of pairing-based cryptographic schemes. The Boneh-Franklin identity-based encryption and Sakai-Kasahara identity-based signature are the most well-known identity-based schemes that have been standardized. So far, various schemes have been proposed to reduce the computational overhead of pairing operations. All these schemes are trying to outsource pairing operations in a secure manner. But besides pairing operations, there are other basic and costly operations in pairing-based cryptography and identity-based schemes, including scalar multiplication on elliptic curves. In this research, we outsource the Boneh-Franklin encryption in a more secure and efficient (in terms of computational and communication complexity) way than existing schemes. Also we outsource the BLMQ signature (based on Sakai-Kasahara) scheme for the first time. The proposed schemes are secure in the OMTUP model. Also, unlike previous schemes, we considered communication channels insecure. Moreover, compared with the trivial solution which outsources every single operation (such as pairing, scalar multiplication and modular exponentiation) as a separate subroutine, our schemes offer less complexity by seamlessly outsourcing the whole encryption scheme for the first time.

Abstract Selecting optimal cybersecurity countermeasures requires integration with mission-critical objectives beyond technical risk minimization. This paper presents a mission-centric framework for countermeasure selection in cybersecurity situation awareness systems by extending the RiskMAP methodology with agent-based and discrete-event simulation. The framework employs a multi-criteria decision-making approach based on the Confidentiality, Integrity, and Availability (CIA) triad, weighing mission objectives and mapping vulnerabilities and threats using MITRE ATT&CK and D3FEND taxonomies. Candidate countermeasures are evaluated considering risk reduction, implementation cost, operational impact, and mission alignment. We demonstrate the approach through a case study on a critical infrastructure organization’s network modeled in AnyLogic. Results show improved alignment between security posture and organizational priorities while maintaining effective risk reduction, outperforming traditional methods. This framework enables quantitative visualization and optimization of security investments relative to mission continuity. All simulation models, data, and scripts are openly available to support reproducibility.

Abstract Medical images show a great interest since it is needed in various medical applications. In order to decrease the size of medical images which are needed to be transmitted in a faster way; Region of Interest (ROI) and hybrid lossless compression techniques are applied on medical images to be compressed without losing important data. In this paper, a proposed model will be presented and assessed based on size of the image, the Peak Signal to Noise Ratio (PSNR),and the time that is required to compress and reconstruct the original image.
The major objective of the proposed model is to minimize the size of image and the transmission time. Moreover, improving the PSNR is a critical challenge.The results of the proposed model illustrate that applying hybrid lossless
techniques on the ROI of medical images reduces size by 39% and gives better results in terms of the compression ratio and PSNR.

Abstract Mandatory access control models have traditionally been employed as a robust security mechanism in multilevel security environments such as military domains. In traditional mandatory models, the security classes associated with entities are context-insensitive. However, context-sensitivity of security classes and flexibility of access control mechanisms may be required especially in pervasive computing environments. To this aim, we propose a context-aware mandatory access control model (CAMAC) capable of dynamic adaptation of access control policies to context, and of handling context-sensitive class association, in addition to preservation of confidentiality and integrity as specified in traditional mandatory access control models. In order to prevent any ambiguity, a formal specification of the model and its elements such as context predicates, context types, level update rules, and operations is required. High expressiveness of the model allows specification of the traditional mandatory access control models such as BLP, Biba, Dion, and Chinese Wall. The model can also be considered as an information flow control model with context-sensitive association of security classes.

Abstract Nowadays, users of information systems have inclination to use a central server to decrease data transferring and maintenance costs. Since such a system is not so trustworthy, users' data usually upkeeps encrypted. However, encryption is not a nostrum for security problems and cannot guarantee the data security. In other words, there are some techniques that can endanger security of encrypted data. Majority of existing methods for encrypted data management have some critical defects such as cryptanalysis attacks, encryption/decryption overhead, and inefficient data storing and retrieval. In this paper, at first we propose a prototype model of private key based search on encrypted data. Then we try to improve it significantly to meet security requirements. Our main goal is to offer a practical method of querying arbitrary words on encrypted data using a minimal trust model. Moreover, we present a model for balancing between performance and security based on user's requirements. In comparison with other methods, query response time is improved and the probability of statistical deductions is reduced.

Abstract A non-malleable code is a variant of an encoding scheme which is resilient to tampering attacks. The main idea behind non-malleable coding is that the adversary should not be able to obtain any valuable information about the message. Non-malleable codes are used in tamper-resilient cryptography and protecting memories against tampering attacks. Many different types of non-malleability have already been formalized and defined in current literature, among which continuous non-malleability is the setup in which the messages are protected against adversaries who may issue polynomially many tampering queries. The first continuous non-malleable encoding scheme has been proposed by Faust et al. (FMNV) in 2014. In this article, we propose a new proof of continuous non-malleability of the FMNV scheme. The new proof will give rise to an improved and more efficient version of this scheme. Also, the new proof shows that one may achieve continuous non-malleability of the same security by using a leakage resilient storage scheme with fewer bits for the leakage bound. This shows that the new scheme is more efficient and practical for tamper-resilient applications.

Abstract Today, the use of the Internet and Internet sites has been an integrated part of the people’s lives, and most activities and important data are in the Internet websites. Thus, attempts to intrude into these websites have grown exponentially. Intrusion detection systems (IDS) of web attacks are an approach to protect users. But, these systems are suffering from such drawbacks as low accuracy in detecting new attacks. To tackle this problem, various methods of machine learning have been presented in recent years. Since malicious web requests have more delicate distinction than normal requests, these methods have failed to exhibit a good accuracy in new attack detection. This paper presents a new method for web attack detection using seq2seq networks using attention. The results show that this method could predict the possible responses and use the difference from the real responses of the server to model the normal traffic. Thereby, it could use the similarity measure to discriminate between normal and anomalous traffic. The highest accuracy of this method versus similar methods shows that the use of attention mechanism can cope with the challenge of studying long web requests to a great extent.

Abstract In this paper we present a new finite field-based public key cryptosystem(NETRU) which is a non-commutative variant of CTRU. The original CTRU is defined by the ring of polynomials in one variable over a finite field F2. This system works in the ring R = F2[x]=hxN 􀀀 1i and is already broken by some attacks such as linear algebra attack. We extend this system over finite fields Zp, where p is a prime (or prime power) and it operates over the non-commutative ring M = Mk(Zp)[T; x]=hXn 􀀀 Ikki, where M is a matrix ring of k by k matrices of polynomials in R = Zp[T; x]=hxn 􀀀1i. In the proposed NETRU, the encryption and decryption computations are non-commutative and hence the system is secure against linear algebra attack as lattice-based attacks. NETRU is designed based on the CTRU core and exhibits high levels of security with two-sided matrix multiplication.

Abstract Resources and services are accessible in pervasive computing environments from anywhere and at any time. Also, due to ever-changing nature of such environments, the identity of users is unknown. However, users must be able to access the required resources based on their contexts. These and other similar complexities necessitate dynamic and context-aware access control models for such environments. In other words, an efficient access control model for pervasive computing environments should be aware of context information. Changes in context information imply some changes in the users' authorities. Accordingly, an access control model for a pervasive computing environment should control all accesses of unknown users to the resources based upon the participating context information, i.e., contexts of the users, resources and the environment. In this paper, a new context-aware access control model is proposed for pervasive computing environments. Contexts are classified into long-term contexts (which do not change during a session) and short-term contexts (which their steady-state period is less than an average time of a session). The model assigns roles to a user dynamically at the beginning of their sessions considering the long-term contexts. However, during a session the active permission set of the assigned roles are determined based on the short-term context conditions. Formal specification of the proposed model as well as the proposed architecture are presented in this paper. Furthermore, by presenting a real case study, it is shown that the model is applicable, decidable, and dynamic. Expressiveness and complexity of the model is also evaluated.

Abstract In this study, a novel approach which uses combination of steganography and cryptography for hiding information into digital images as host media is proposed. In the process, secret data is first encrypted using the mono-alphabetic substitution cipher method and then the encrypted secret data is embedded inside an image using an algorithm which combines the random patterns based on Space Filling Curves (SFC) and the optimal pair-wise LSB matching method. We employ a modified Imperialist Competitive Algorithm by Genetic Algorithm operations, namely Discrete Imperialist Competitive Algorithm (DICA), to perform the optimal pair-wise LSB matching method and find the suboptimum adjustment list. The performance of the proposed method is compared with other methods with respect to Peak Signal to Noise Ratio (PSNR). The PSNR value of the proposed method is higher than the state-of-the-art methods by almost 4dB to 5dB.

Abstract Nowadays there are different kinds of attacks on Field Programmable Gate Array (FPGA). As FPGAs are used in many different applications, its security becomes an important concern, especially in Internet of Things (IoT) applications. Hardware Trojan Horse (HTH) insertion is one of the major security threats that can be implemented in unused space of the FPGA. This unused space is unavoidable to meet the place and route requirements. In this paper, we introduce an efficient method to fill this space and thus to leave no free space for inserting HTHs. Using a shift register in combination with gate-chain is the best way of filling unused space, which incurs a no increase in power consumption of the main design. Experimental results of implementing a set of IWLS benchmarks on Xilinx Virtex devices show that the proposed prevention and detection scheme imposes a no power overhead with no degradation to performance and critical path delay of the main design

Abstract Image watermarking refers to the process of embedding an authentication message, called watermark, into the host image to uniquely identify the ownership. In this paper a novel, intelligent, scalable, robust wavelet-based watermarking approach is proposed. The proposed approach employs a genetic algorithm to find nearly optimal positions to insert watermark. The embedding positions coded as chromosomes and GA operators (e.g. selection, crossover, mutation and elitism), are used to find the nearly optimal embedding positions. A fitness function, which includes both factors related to transparency and robustness, is used to assess and compare chromosomes. The watermarked test images do not show any perceptual degradation. This approach supports scalable watermark detection and provides robustness against progressive wavelet image compression. The experimental results very efficiently prove the robustness of the approach against progressive wavelet image coding even at very low bit-rates and some other attacks. This approach is a good candidate for providing efficient authentication for secure and progressive image transmission applications especially over heterogeneous networks, such as the Internet.

Abstract Due to wireless nature and hostile environment, providing of security is a critical and vital task in wireless sensor networks (WSNs). It is known that key management is an integral part of a secure network. Unfortunately, in most of the previous methods, security is compromised in favor of reducing energy consumption. Consequently, they lack perfect resilience and are not fit for applications with high security demands. In this paper, a novel method is proposed to improve the security of key management system based on broadcast messages from the base station. Another problem with WSNs is the cryptographic materials (such as private keys) stored in dead nodes. Adversaries may exploit these nodes to mount more effective attacks. Any secure key management system should also address this problem. It is argued that in the proposed method keying materials of dead nodes lose their validity, and therefore are of no use for an adversary. Finally, it is shown through simulation that the proposed method is almost three times more energy-efficient than conventional certificate-based key management systems.

Abstract FPGA platforms have been widely used in many modern digital applications due to their low prototyping cost, short time-to-market and flexibility. Field-programmability of FPGA bitstream has made it as a flexible and easy-to-use platform. However, access to bitstream degraded the security of FPGA IPs because there is no efficient method to authenticate the originality of bitstream by the FPGA programmer. The issue of secure transmission of configuration information to the FPGAs is of paramount importance to both users and IP providers. In this paper we presented a "Self Authentication" methodology in which the originality of sub-components in bitstream is authenticated in parallel with the intrinsic operation of the design. In the case of discovering violation, the normal data flow is obfuscated and the circuit would be locked. Experimental results show that this methodology considerably improves the IP security against malicious updates with reasonable overheads.

Abstract The medical system remains among the fastest to adopt the Internet of Things. The reason for this trend is that integration Internet of Things(IoT) features into medical devices greatly improve the quality and effectiveness of service. However, there are many unsolved security problems. Due to medical information is critical and important, authentication between users and medical servers is an essential issue.
Recently, Park et al. proposed an authentication scheme using Shamir's threshold technique for IoT-based medical information system and claimed that their scheme satisfies all security requirements and is immune to various types of attacks. However, in this paper, we show that Park et al.'s scheme does not achieve user anonymity, forward security, and mutual authentication and it is not resistant to the DoS attacks and then we introduce an improved mutual authentication scheme based on Elliptic Curve Cryptography (ECC) and Shamir 's secret sharing for IoT-based medical information system.
In this paper, we formally analyze the security properties of our scheme via the ProVerif. Moreover, we compare our proposed scheme with other related schemes in terms of security and performance.

Abstract In recent years, due to their potential applications, proxy blind signatures became an active research topic and are an extension of the basic proxy signature. A proxy blind signature scheme enables a proxy signer to produce a blind signature on behalf of an original signer. Such schemes are useful in many practical applications such as e-commerce, e-voting, e-tendering systems. Many proxy blind signature schemes have been proposed in the literature. In order to improve the efficiency and to adopt resource constrained devices, in this paper, we propose a pairing free ID-based proxy blind signature scheme with message recovery. The proposed scheme is proven secure against the random oracle model under the hardness assumption of the elliptic curve discrete logarithm problem. We compare our scheme with the other proxy blind signature schemes. The efficiency analysis shows that our scheme is more efficient in terms of computational and communicational point of view. Also due to the message recovery property, our scheme can be deployed easily in low band width devices.

Abstract Ensuring fair task validation and reward distribution remains a significant challenge in decentralized crowdsourcing systems. Existing platforms often suffer from malicious evaluations, unfair compensation, central points of failure, and limited transparency. In this work, we propose a fully decentralized crowdsourcing protocol built on blockchain technology and smart contracts to address these issues. Our system introduces a validator-based task evaluation process and ensures secure and private task handling through encryption and decentralized IPFS storage. Participants interact through smart contracts, which manage task assignment, output verification, and automated reward distribution. To promote fairness, we employ a reward allocation strategy based on the actual contribution of each participant. The proposed system addresses critical crowdsourcing challenges including malicious or biased evaluations, Sybil attacks, collusion, single points of failure, lack of revision mechanisms, and excessive transaction costs. Experimental results show that our smart contracts are executed with low cost (total deployment cost of 0.0511 ETH, with function calls as low as 47,878 gas units). The system sustains reliable operation and maintains integrity even when adversarial validators control up to 49% of the total reputation.

Abstract To control the exponential growth of malware files, security analysts pursue dynamic approaches that automatically identify and analyze malicious software samples. Obfuscation and polymorphism employed by malwares make it difficult for signature-based systems to detect sophisticated malware files. The dynamic analysis or run-time behavior provides a better technique to identify the threat. In this paper, a dynamic approach is proposed in order to extract features from binaries. The run-time behavior of the binary files were found and recorded using a homemade tool that provides a controlled environment. The approach based on DyVSoR assumes that the run-time behavior of each binary can be represented by the values of registers. A method to compute the similarity between two binaries based on the value sets of the registers is presented. Hence, the values are traced before and after invoked API calls in each binary and mapped to some vectors. To detect an unknown file, it is enough to compare it with dataset binaries by computing the distance between registers, content of this file and all binaries. This method could detect malicious samples with 96.1% accuracy and 4% false positive rate. The list of execution traces and the dataset are reachable at: http://home.shirazu.ac.ir/˷ sami/malware

Abstract Ciphertext-policy attribute-based encryption(CP-ABE) is considered a promising solution for secure data sharing in the cloud environment. Although very well expressiveness in ABE constructions can be achieved using a linear secret sharing scheme(LSSS), there is a significant drawback in such constructions. In the LSSS-based ABE constructions, the number of heavy pairing operations increases with an increase in the number of required attributes in the decryption. In this paper, we propose an LSSS-based CP-ABE scheme with a fixed number of pairings(four pairings) during the decryption process. In our scheme increasing the number of required attributes in the decryption does not affect the number of pairings. The simulation shows that our scheme has significant advantages in the encryption and the decryption processes compared to previous schemes. In addition, we use the outsourcing method in the decryption to get better performance on the user side. The main burden of decryption computations is done by the cloud without revealing any information about the plaintext. Furthermore, in our revocation method, the users’ communication channels are not used during the revocation process. All of these features make our scheme suitable for applications such as IoT. The proposed scheme is selectively CPA-secure in the standard model.

Abstract Distributed Denial of Service (DDoS) is a common attack in recent years that can deplete the bandwidth of victim nodes by flooding packets. Based on the type and quantity of traffic used for the attack and the exploited vulnerability of the target, DDoS attacks are grouped into three categories as Volumetric attacks, Protocol attacks and Application attacks. The volumetric attack, which the proposed method attempts to detect it, is the most common type of DDoS attacks. The aim of this paper is to reduce the delay of real-time detection of DDoS attacks utilizing hybrid structures based on data stream algorithms. The proposed data structure (BHM ) improves the data storing mechanism presented in STONE method and consequently reduces the detection time. STONE characterizes regular network traffic of a service by aggregating it into common prefixes of IP addresses, and detecting attacks when the aggregated traffic deviates from the regular one. In BHM, history refers to the output traffic information obtained from each monitoring period to form a reference profile. The reference profile is created by employing historical information and only includes normal traffic information. The delay of DDoS attack detection increases in STONE due to long-time intervals between each monitoring period. The proposed method (F-STONE) has been compared to STONE based on attack detection time, Expected Profile Update Time (EPUT), and rate of attack detection. The evaluation results indicated significant improvements in terms of the EPUT, acceleration of attack detection and reduction of false positive rate.