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The principal constituent of a block cipher in symmetric-key cryptography is the Boolean function, determining the substitution box (S-box). Block ciphers rely totally on S-boxes with excellent nonlinearity and upright cryptographic structures. In AES, an 8 × 8 S-box is a 16 × 16 lookup table over the Galois field GF 2 8 , that occupies 8 × 28 bytes storage of computer memory. By using traditional method to construct a 24 × 24 S-box over Galois field GF 2 24 , which lodges a storage memory of 24 × 224 bytes in traditional sense. Thus, the memory storage does not support a 24 × 24 S-box over a very larger order Galois field like GF 2 24 . A resolute of this difficulty is possibly coming out from the algebraic structure of the commutative finite chain ring F q [ x ] < x k > = ∑ i = 0 k - 1 x i F q. In this study, a subgroup of the multiplicative group of units of the chain ring F 2 [ x ] < x 24 > = ∑ i = 0 23 x i F 2 is considered to construct a 24 × 24 S-box that occupy just 24 × 28 bits storage memory of computer. The proposed S-box has a substantial potential to create confusion during substitution phase of the color image enciphering algorithm. While for the permutation component of the algorithm, DNA transform is applied for creating diffusion in the pixels of the color image. The proposed RGB image encryption attains the standard optimum level when compared it to the DNA and chaos-based image encryption techniques. [ABSTRACT FROM AUTHOR]

One of the routine exercises to manage and improve the performance and utility of the cloud is the migration or transfer of cloud data whether it is large or small. However, it is extremely challenging to protect both data privacy and integrity concurrently while moving cloud data, particularly when it is very vast. Collectively, prior works fail to offer a complete solution to these problem. Even though data encryption and steganography techniques are popular and efficient, they provide higher time and space complexities and introduce information loss. As a result, the goal of this research is to provide a chaos compression and encryption system based on chaos theory to guarantee both data privacy and integrity during the transit or migration of massive cloud data. During data transmission, the entire data are compressed using a chaotic substitution box followed by an adaptive Huffman encoding algorithms. Therefore, the input data are efficiently transformed into a non-readable form which replaces the original data, making it difficult for an unethical individual or group to determine its true sense. Our evaluation results show that the proposed chaotic technique has a maximum entropy value of 7.99, which supports its ability to provide more privacy when compared to previous techniques. It also delivers the best bits per code of 4.41, a throughput of 2.89 MB/s, and a minimal information loss percentage of 0.0011%, demonstrating its superior time, space efficiency, and ability to improve data integrity over existing methods. [ABSTRACT FROM AUTHOR]

In this paper, we discuss the quantum circuit implementations of the lightweight authenticated encryption algorithm ASCON by using the NOT gates, CNOT gates, Toffoli gates, measurements, and the dynamic quantum circuits. Firstly, the quantum circuit of addition of constants is realized by adding the NOT gates according to the position of 1 in round constants. Secondly, the quantum circuit of S-box of the permutation is synthesized according to the classical circuit diagram of S-box. Then the linear layer functions are expressed in matrix form, and their quantum circuits are synthesized according to Gaussian elimination. Finally, we synthesize the whole quantum circuits according to the general diagrams of the authenticated encryption algorithm ASCON. The correctness of the quantum circuits of the S-box and the linear layer was verified by the Aer simulator of the IBM Quantum platform. As far as we know, this is the first implementation of the quantum circuits for the Authenticated Encryption with Associated Data (AEAD) of ASCON in-place. The maximum quantum resources for the three ASCON authenticated encryption algorithms were estimated. The quantum circuit of ASCON-128 uses a total of 320 qubits, 30,639 NOT gates, 128,814 CNOT gates, 8064 Toffoli gates, 10,752 measurements, and 5376 dynamic quantum circuits. The quantum circuit of ASCON-128a uses a total of 320 qubits, 23,558 NOT gates, 98,144 CNOT gates, 6144 Toffoli gates, 8192 measurements, and 4096 dynamic quantum circuits. The quantum circuit of ASCON-80pq uses a total of 320 qubits, 30,736 NOT gates, 128,814 CNOT gates, 8064 Toffoli gates, 10,752 measurements, and 5376 dynamic quantum circuits. [ABSTRACT FROM AUTHOR]

In recent years, the popularity of blockchain application in healthcare sector has increased manifold due to features such as decentralized architecture, security, immutability and authentication. However, there are some challenges associated with blockchain-based healthcare frameworks. Firstly, blockchain provides data verifiability meaning that anything stored there is accessible to all nodes in the network for verification. However, it is unacceptable for sensitive medical data to be made accessible to everyone. Secondly, healthcare sectors are group-oriented and frequently involve open networks for communication which lead to data breaches and other security risks. Lastly, due to limited size of a block in blockchain, many hospitals prefer storing patient's data locally in a centralized server or opt for cloud storage which have their own threat vectors. In this work, we propose a three-phase unified approach to solve the above problems. Our framework utilizes proxy re-encryption and advanced cryptographic techniques to provide stringent access control. Next, a blockchain-based group encryption is proposed to ensure secure group communication. A group session key will be agreed upon by the authorized group members and used to protect sensitive patient information. Lastly, IPFS-based blockchain data storage is proposed to maintain data securely offsite. We provide a comparative security analysis of the proposed framework with other existing peer models and show that our framework offers several new security features. We also examine the security of the proposed framework using BAN logic. Furthermore, the proposed framework is simulated using the OMNET++ software, and its storage and computation costs are examined to establish its effectiveness. [ABSTRACT FROM AUTHOR]

IoT devices produce a vast amount of data ranging from personal to sensitive information. Usually, these devices remain connected to the internet so protecting the information produced by them is crucial. Since most of the IoT devices are resource-constrained, they must be supported with lightweight encryption standards to protect information. Recent research has used the concept of context awareness to select the most suitable data encryption standard based on the device resources along with the required information confidentiality level. However, to effectively use the context information, it is required to be organized explicitly while considering the dynamic nature of IoT systems. In this regard, ontology-based systems effectively reduce the volume of manual work while recommending solutions. Currently, these systems cannot work with precision due to multiple uncertain factors of IoT sensory data. To overcome this challenge, this research proposes a fuzzy ontology-based context-aware system to protect IoT device information with the help of an encryption algorithm that considers device capabilities and user priorities regarding the data confidentiality. In order to automate the recommendation process, Semantic Web Rule Language (SWRL) rules and fuzzy logic are used, whereas, Description Logic and RDF Query Language is used to evaluate the results. The evaluation results confirm that the proposed method can produce results according to human perception by significantly increasing the accuracy of prediction. [ABSTRACT FROM AUTHOR]

Deep learning accelerators have domain-specific architectures, this special memory hierarchy and working mode could bring about new crucial security vulnerabilities. Neural network reuse PE resources layer by layer, after a layer finished, accelerator will give an interrupt to inform host processor dispatch the next layer. By snooping on the interrupt signal patterns, we can capture specific deep neural network (DNN) models and launch hardware trojan attacks. In this paper, we propose Int-Monitor, a novel neural network model triggered hardware trojan in DNN accelerators. By implanting a well-designed interrupt monitor between the host processor and DNN accelerator, this backdoor can capture specific DNN models and trigger the trojan to attack DNN bias buffers. By attacking the global bias buffer, this trojan can prevent the activation of neurons in a DNN model. As result, the network forward propagation will be invalid and the accelerator will deny service. Runtime experiments on LeNet, Resnet, YOLOv2 and YOLOv4tiny DNN models show Int-Monitor can successfully attack the FPGA-based DNN accelerator SoCs. RTL synthesis and implementation show this trojan takes only small hardware overhead and negligible power consumption. It brings 0.5%, 0.2% hardware overhead and 0.622%, 0.187% power consumption on average in the SIMD and NVDLA accelerators. Unlike previous trojan using specially dedicated input data as a trigger, this novel trojan can enable hackers utilize DNN model as a trigger. This mechanism can make its escape from data pre-processing and data encryption. [ABSTRACT FROM AUTHOR]

In order to improve the efficiency of cloud storage, deduplication technology has been widely used. In personal cloud storage, files are diverse. Diverse files contain files of different sizes and different popularity, some of which have many copies. Existing deduplication schemes mainly focus on data security but fail to improve the overall performance, including low computing overhead for diverse data. Using deterministic tags based on convergent encryption to identify data may leak data information, while using fully random tags generated by complex encryption algorithms may generate more computing overhead. To address the above issues, we proposed an encrypted deduplication scheme based on files diversity (FD-Dedup). Diverse files are identified by semi-random tags. We also designed a semi-random tag generation (SRTG) algorithm that coordinates the computing overhead and security. Security analysis and performance comparison show that FD-Dedup can balance security and computing overhead for diverse files in personal cloud storage. [ABSTRACT FROM AUTHOR]

Supply chain management has become increasingly complex, leading to information loss and delayed transmission, exacerbating the bullwhip effect. Furthermore, the need for more reliable information storage, traceability, and accountability has slowed supply chain management. In this context, blockchain technology (BCT) solves the bullwhip effect problem, as it supports distributed networking, information synchronization among nodes, digital encryption, traceable information, and unchangeable block content. This paper proposes using public blockchain to solve the bullwhip effect problem in the supply chain (SC), which has yet to be discussed in published academic research papers. To this end, a framework has been developed to determine the readiness of a supply chain for blockchain adoption. This framework includes a checklist to evaluate the motivation, timing, and appropriate platform for adopting blockchain. The framework has been validated using a case study of personal computer devices, which were affected by the Covid-19 pandemic and resulted in semiconductors supply chain disruption. The study involved polling four executives The study involved polling four executives (of large organizations in Egypt and some Middle Eastern countries) representing different stages in the supply chain, they are retail, distribution, manufacturing, and supply. The results showed that while the executives recognized the benefits of adopting blockchain, they were still determining if it was the right time for adoption and did not see the technology ready for their supply chains. Finally, some public blockchain platforms were introduced to help businesses choose the most suitable platform for adoption. [ABSTRACT FROM AUTHOR]

Traditional centralized cloud storage has difficulties in realizing the secure storage and sharing of speech and other multimedia data, as well as realizing fine-grained access control and privacy protection for speech data. To address this problem, we propose a distributed storage scheme for encryption speech data based on blockchain and inter planetary file system (IPFS). Our scheme is based on the characteristics of blockchain anti-tampering, decentralization and traceability. It is designed to ensure the security and controllability of private sensitive speech data of data users without the use of centralized cloud storage architecture. First, the ciphertext policy hierarchical attribute-based encryption (CP-HABE) scheme is used to encrypt the speech data. The encrypted speech data is then stored in the IPFS to achieve distributed storage. Second, a distributed and trusted access control policy is implemented by deploying an access control protocol Ethereum smart contract related to speech attributes. Finally, the proposed scheme is deployed and tested in the Linux environment, and the smart contract is deployed on the Ethereum test chain. Through experimental comparison with different storage schemes, analysis of the operational properties of our scheme and the evaluation of the quality index of the encryption scheme, the proposed scheme is shown to reliable, secure and scalable. [ABSTRACT FROM AUTHOR]

After the tremendous development and fast growth in communication systems and electronic devices, information security and preservation have become one of the most important procedures to be considered when transferring data between two parties. Encryption and data hiding are two of the most important techniques to protect the information sent over networks and the Internet. In this paper, a new technique of encryption and concealment is used through the following steps: First, the secret information is encrypted by using developed DNA to get (S1), second, by scrambling the encrypted data, the (S1) is diffused by using a zigzag method to get (S2), third, re-obfuscation the (S2) by using developed zigzag method through using Tinkerbell technique to get (S3), fourth, perform XoR operation between the (S3) and the Tinkerbell technique to get (S4), and fifth, the (S4) is hidden in the random locations of the cover image based on the LSB technique and the Tinkerbell technology, where the Tinkerbell has incredibly excellent characteristics and used to generate random sequence numbers twice with different initial and parameters value, once for the encryption process for scrambling secret information and once for the hiding process for determining hidden locations. Several metrics were used to evaluate the system's efficiency: histogram, PSNR, MSE, mean absolute error, bit error rate, encryption quality, Unified Average Changing Intensity, hamming distance, entropy, and correlation coefficient. The experimental results display that the suggested method has a good performance and reliability, high security, and greater embedding capacity and ensures higher image quality; also, the proposed method presented preferable outcomes when compared to other approaches. [ABSTRACT FROM AUTHOR]

Long-term care refers to any support, both medical and non-medical, provided to the elderly with a chronic illness or disability due to physical or mental conditions. Since the cost of long-term care insurance is not inexpensive, low-cost devices and sensors can be used to create medical assistance systems to reduce human maintenance costs. The requirement of security and privacy under healthcare information protection is a critical issue for internet of medical things (IoMT) data transmission. In this paper, we designed an IoMT security robot for a long-term care system. The goal of this IoMT security robot is to provide secure transmission of the residents' private information. It is composed of three layers, namely, collection, encryption, and transmission. The function of the IoMT security robot is to first collect data from the patient or the elderly, then provide efficient data encryption, and deliver secured data transmission mechanisms to send the valuable data to the cloud. This IoMT security robot also has a server authentication mechanism, and a support IoT and IoMT devices inspection function. Our evaluation results showed that even when we utilized a low power consumption device like Raspberry Pi, AES algorithm achieved an encrypt and decrypt of 100–100 K bytes under 9 ms, which is a lot better than ECC, which takes about 104 ms. Further, we found that the AES only takes 0.00015 s to decrypt 100 Bytes data, which is way faster than the ECC algorithm, which takes 0.09 s. [ABSTRACT FROM AUTHOR]

Internet of Things (IoT) has a wide concentration in today's technological world. It has a significant impact on smart infrastructure with a security vision. So, IoT devices with sensors or smart gadgets are used to gather important data. The data gathered from IoT are vulnerable to signal processing attacks due to the interconnection of different network categories. In this paper, a system for securing data in IoT communication is proposed. The proposed system includes two techniques. Initially, a technique with the combination of Fuzzy and Particle swarm optimization (F-PSO) is utilized to determine a secure path. Then a cryptographic technique using the Learning with Errors over Rings (R-LWE) encryption scheme is adopted for data encryption. The trust value of every node in the network is calculated using trustworthiness analysis. Then based on the trust value, the malicious nodes are segregated. After that, the characteristics of secure nodes are utilized to find the secure path between source and destination. The secure path is selected optimally using F-PSO. After finding the secure path, the data are encrypted using the R-LWE technique. The proposed system attained a throughput of 96% with less than 0.1 ms delay. An enhanced trust-based secure routing and message delivery protocol attained better performance than existing such as Advanced Encryption Standard, Tiny Encryption Algorithm, eXtended TEA, and Rivest–Shamir–Adleman encryption schemes. [ABSTRACT FROM AUTHOR]

Outsourcing data to the cloud can be considered as a perfect solution for the storage and computationally constrained data owners. However, data confidentiality is compromised when data are shared through the cloud. Cryptographic techniques like searchable encryption offer possible solutions of protect data from unauthorized access while facilitating searching without disclosure. Different searchable encryption techniques have been proposed; however, the techniques are limited in one way or the other, and none of them satisfies all the needs of confidentiality while sharing of data outsourced on the cloud. In this survey, we have identified the key performance indicators for confidentiality while sharing for cloud data along with possible attacks on searchable encryption techniques. A comprehensive study of the existing techniques searchable encryption on the anvil of the key performance indicators and robustness to attacks has been done. It was found that a technique may be suitable for an application with specific data confidentiality requirements, although no cryptographic silver bullet exists that satisfies all the performance metrics or is impervious to all the attacks. Moreover, most of the existing techniques are impracticable due to paradoxical requirements of data confidentiality and performance. A single mechanism may not suffice, and there is a need for a basket of efficient techniques that may provide accurate search with data confidentiality to make data sharing over the cloud an economically attractive option. [ABSTRACT FROM AUTHOR]

Attribute-based encryption(ABE) can enable user-centered data sharing in untrusted cloud scenario where users usually lack control on their outsourced data. However, existing ABE schemes have intrinsic limitations on scalability and revocation efficiency due to the bottleneck of a central authority and heavy re-encryption overhead on revocations. In this paper, we present a revocable decentralized attribute-based encryption scheme for data access control in cloud storage. In particular, by integrating decentralized attribute-based encryption, key regression technique, all-or-nothing transform, revocation list for involved attributes, and blacklist in a novel way, we provide a revocable ABE scheme with practical dynamic group membership and identity privacy protection, and meanwhile, it enhances the re-encryption efficiency caused by revocations without sacrificing security. We analyzed the security of our scheme. The experimental evaluation demonstrates that the cryptographic overhead on key derivation, encryption(decryption), and ABE ciphertext update are reasonable, and for the throughput of accessing encrypted data from the cloud, our scheme outperforms other schemes. [ABSTRACT FROM AUTHOR]

Cloud computing has gained great attention among the individual user and the organization. Transitioning to the cloud platform is not simple as it involves various cybersecurity and operational issues. Due to a large amount of data storage in the cloud, ensuring the security of the data outsourced in the cloud is highly important. A Key Management System (KMS) is a secure data protection method that is commonly used in e-healthcare information systems, information security (confidentiality, integrity, authenticity), large-scale organizations, architecture security, sensor security, identity management, access control (privacy preservation), identity proofing (authentication), and legal issues. Because this approach allows the secret key information to be exchanged safely, the security level may be guaranteed to be high. Using a random prime number, a master secret key, and a parameter value, one can generate a secure key that is difficult for hackers to break. Secure data transfer with exact and consistent authentication is the goal of this new approach. This research focuses on the development of secure secret key creation and the improvement in secure key sharing. To generate the key (in the form of a QR code), we have used an asymmetric Elliptic Curve Cryptography (ECC) method, whereas encryption and decryption of data have been done by a hybrid of Advanced Encryption Standard (AES) and ECC cryptography. The hybrid ECC-AES model was found to take less amount of time than the AES model and other existing models. Current algorithms have certain security issues, such as vulnerability to plaintext attacks, brute force attacks, side-channel attacks, and computational complexity. The proposed algorithm has been able to overcome the issue of key exchange that plagues AES, simpler than ECC and more reliable than AES. As a result, KMS has been designed to provide high levels of security for healthcare information. We have proposed a Hybrid Cryptographic Approach to enhance the Mode of Key Management System (HCA-KMS) in a Cloud Environment based on authenticated encryption with AES and ECC. The proposed algorithm has been compared to existing methods concerning confidentiality, integrity, time complexity, storage overhead, resource utilization, security, and log time to demonstrate its efficacy. The proposed HCA-KMS has time complexity, encryption time (O (n)), and decryption time (O (logn)). [ABSTRACT FROM AUTHOR]

The resource-constrained nature of Internet of Things (IoT) devices and their diversity and abundancy represent a major challenge for the development of efficient security solutions that fit IoT systems and ensure end-to-end security. This paper presents an efficient IoT authentication scheme that provides mutual authentication between three different entities making up the IoT system under study; IoT devices, an IoT manufacturer server, and an authentication server. The authentication process is accomplished by the exchange of only six small messages in three successive stages: the IoT device association stage, the IoT device–AS server communication initialization stage, and the exchanged data encryption stage. The scheme employs the HMAC keyed hash function to provide mutual authentication and the AES-GCM lightweight symmetric cryptographic function to provide integrity and confidentiality for the exchanged data. The proposed scheme was simulated using the Network Simulator NS3 with C++ crypto++ library, using the various IoT enabling technology models. The obtained simulation results verified the proper functioning of the designed scheme and demonstrated the efficiency of the proposed scheme in terms of the low computational and communication overheads. The scheme needed 13.04 ms and 470 bytes to complete the mutual authentication process, including session key exchange. The low computational and communicational overhead of the proposed scheme are due to the scheme's small-sized messages, lightweight cryptographic functions, and passive discovery of IoT device. Security analysis of the scheme shows that the essential security requirements, which includes mutual authentication, confidentiality, and integrity, have been met by the proposed authentication scheme. Moreover, the scheme is inherently robust against common cyber-attacks such as the DoS, impersonation, spoofing, sniffing, and man-in-the-middle attacks. [ABSTRACT FROM AUTHOR]

With the rapid development in world-wide technologies affecting large-scale applications, the Internet of Things (IoT) has gained a lot of attention from such applications. The Internet of Vehicles (IoV) technology is an exploration of the IoT where radio frequency identification (RFID), one of the promising technologies, can be employed in the IoV systems. However, security and privacy are a key concern in RFID-based IoV system. In the RFID systems during wireless communication among the tag and the reader, an adversary can perform malicious attacks and compromise data privacy. Apart from privacy and security issues, the computation capability and memory of the tags are very limited as compared to the backend server and the reader; therefore, an RFID-based authentication protocol suffers from the high computational overhead. To overcome these issues, we have put forward an anonymous and secure ultralightweight RFID protocol for Internet of Vehicles (AnonSURP). In order to reduce the overhead of the RFID tags, we have exploited the cross and the left rotate operations instead of a hash function for data encryption. In particular, the proposed protocol aims at ensuring the user's location privacy, data privacy, and resisting typical known attacks. Also, the proposed protocol is ensuring the low-cost of the RFID tags and providing fast certification speed. The informal analysis ensures that the protocol AnonSURP meets the various security requirements and provides resistance from various known attacks. Finally, a comparative analysis has been performed that demonstrates the better performance of the proposed protocol from the existing protocols. [ABSTRACT FROM AUTHOR]

CAVLC (Context-Adaptive Variable Length Coding) is a high-performance entropy method for video and image compression. It is the most commonly used entropy method in the video standard H.264. In recent years, several hardware accelerators for CAVLC have been designed. In contrast, high-performance software implementations of CAVLC (e.g., GPU-based) are scarce. A high-performance GPU-based implementation of CAVLC is desirable in several scenarios. On the one hand, it can be exploited as the entropy component in GPU-based H.264 encoders, which are a very suitable solution when GPU built-in H.264 hardware encoders lack certain necessary functionality, such as data encryption and information hiding. On the other hand, a GPU-based implementation of CAVLC can be reused in a wide variety of GPU-based compression systems for encoding images and videos in formats other than H.264, such as medical images. This is not possible with hardware implementations of CAVLC, as they are non-separable components of hardware H.264 encoders. In this paper, we present CAVLCU, an efficient implementation of CAVLC on GPU, which is based on four key ideas. First, we use only one kernel to avoid the long latency global memory accesses required to transmit intermediate results among different kernels, and the costly launches and terminations of additional kernels. Second, we apply an efficient synchronization mechanism for thread-blocks (In this paper, to prevent confusion, a block of pixels of a frame will be referred to as simply block and a GPU thread block as thread-block.) that process adjacent frame regions (in horizontal and vertical dimensions) to share results in global memory space. Third, we exploit fully the available global memory bandwidth by using vectorized loads to move directly the quantized transform coefficients to registers. Fourth, we use register tiling to implement the zigzag sorting, thus obtaining high instruction-level parallelism. An exhaustive experimental evaluation showed that our approach is between 2.5 × and 5.4 × faster than the only state-of-the-art GPU-based implementation of CAVLC. [ABSTRACT FROM AUTHOR]

The main challenge in database-as-a-service is the security and privacy of data because service providers are not usually considered as trustworthy. So, the data must be encrypted before storing into the database. Another challenge arises that the performance is degraded on the deployment of encryption algorithm on runtime. Furthermore, the connectivity through the Internet adds more delay. To tackle this, we have proposed parallel query execution methodology using multithreading technique up to 6 threads. We have conducted experiments up to 1000,000 (1 million) encrypted records. Our results are quite promising. For data encryption/decryption, we have used advance encryption standard with blocking length of 256 bits. We have designed our methodology in the context of parallel computation method proposed in the literature (Ho et al., in: Proceedings of the 2017 international conference on machine learning and soft computing, pp 47–52, 2017). We compared the results with state-of-art algorithms. The state-of-art algorithms execute the experiments on 10,120 encrypted records maximum which took about time of 1000 ms with 2 threads. But the proposed methodology is proved outstanding that executed the experiments which were performed on 100,000 encrypted records. It outperformed with 6 threads which took only 507 ms even with 2 threads, and the proposed methodology is much better which took only 994 ms. So, the efficiency and scalability of the proposed methodology are proved better as compared to state-of-the-art algorithms. [ABSTRACT FROM AUTHOR]

Smart phones have changed the way we interact with this world and our peers. They have not only become powerful, but they have become affordable. In this current day and age, smart phones are getting smarter with every subsequent iteration. Every aspect of today's smart phones is far more efficient and powerful than the computers we had a few years back. Mobile crowd sensing (MCS) is the recent attractive research area that follows the crowd's basic principle wisdom. Complex tasks can be performed easily with (MCS) network using the enormous amount of human involvement and powerful mobile devices. Even though there are a plethora of options available to users in terms of services to choose from, the one thing that remains a concern is security, privacy & data breach. Mobile crowd sensing -centralized design approach can give a lot of durable services. However, the trust of centralized service providers cannot be assured within the real world, owing to the profit-driven facts of service providers, when the privacy policy goes into conflict with their profit, they're most likely to perform dishonest work, going against the work ethics and even performing malicious activities for gaining more profit. The prime example is Mark Zuckerberg providing their Facebook User data to third parties for monetary benefits. Besides the emergence of assorted attacks, particularly for inner attacks, service providers cannot offer full protection for task information, attribution information, or collected knowledge. Therefore, a decentralized design approach for mobile crowd sensing is strongly required. This paper aims to design and implement a real-time privacy-preserving data aggregation distributed-scheme to mobile crowd sensing called SMARTEE. Our design uses elliptic curve-based Public Key Encryption and digital signature for data encryption and verification, which performs faster computations, uses less storage and employs a shorter key. The digital signature ensures integrity and privacy-preserving of the data. We incorporate blockchain technology with the traditional (MCS) to process and analyze obtained crowd sensed data that ensures automotive security and privacy. Our proposed architecture with the features of blockchain protects the user information's privacy and increases the security of the (MCS) environment. [ABSTRACT FROM AUTHOR]

Graphics processing units have proved their capability for general-purpose computing in many research areas. In this paper, we propose the mechanism and implementation of a database system that encrypts and decrypts data by using GPU. The proposed mechanism is mainly designed for database systems that require data encryption and decryption to support high security level. The outsourced database systems or database cloud service could be a good candidate for our system. By exploiting the computation capability of GPU, we achieve not only a fast encryption and decryption time per operation, but also a higher overall performance of a database system by offloading computation to GPU. Moreover, the proposed system includes a mechanism which can decide whether to offload computation to GPU or not for more performance gain. We implemented the AES algorithm based on CUDA framework and integrate with MySQL, a commodity database system. Our evaluation demonstrates that the encryption and decryption on GPU show eight times better performance compared to that on CPU when the data size is 16 MB and the performance gain is proportional to the data size. We also show that the proposed system alleviates the utilization of CPU, and the overall performance of the database system is improved by offloading heavy encrypting and decrypting computation to GPU. [ABSTRACT FROM AUTHOR]

The ultimate goal of modern cryptography is to protect the information resource and make it absolutely unbreakable and beyond compromise. However, throughout the history of cryptography, thousands of cryptosystems emerged and believed to be invincible and yet attackers were able to break and compromise their security. The main objective of this paper is to design a robust cryptosystem that will be suitable to be implemented in Internet of Things. The proposed cryptosystem is based on algebraic geometric curves, more specifically on Hermitian curves. The new cryptosystem design is called Hermitian-based cryptosystem (HBC). During the development of the HBC design, Kerckhoffs's desideratum was the main guidance principle, which has been satisfied by choosing the Hermitian curves as the core of the proposed design. The proposed HBC inherits all the advantageous characteristics of Hermitian curve which are large number of points that satisfy the curve and high genus curves. The aforementioned characteristics play a crucial role in generating a large size encryption key for HBC and determine the block size of plaintext. Due to the fact that HBC used algebraic geometric codes over Hermitian curve, it has the ability to perform error correction in addition to data encryption. The error correction is another advantage of HBC compared with many existing cryptosystems such as McEliece cryptosystem. The number of errors that can be corrected by HBC is larger (high data rate) than other algebraic geometric codes such as elliptic and hyperelliptic curves. It also uses non-binary representation which increases its attack resistance. In this paper, the proposed HBC has been mathematically compared with elliptic curve cryptosystem. The results show that HBC has many advantages over the elliptic curves in terms of number of points and genus of the curve. [ABSTRACT FROM AUTHOR]

The security of modern cryptosystems relies on the secrecy of the keys. Against the expectation that the keys used in cryptographic algorithms are perfectly secure, the keys can get compromised when implemented on physical devices. Because of the computational leakages from the execution of cryptographic algorithms, a variety of side-channel measurements can lead to full breaks of the targeted physical devices. Leakage-resilient cryptography aims at defining leakages in a generic model and designing provably secure primitives to capture side-channel attacks. For this purpose, several re-keying schemes are proposed to prevent encryption scheme from using the same key many times. In this paper, we propose a leakage-resilient authenticated encryption scheme, called Re-keying Code Book (RCB), that is secure against the side-channel attacks by combining with existing re-keying schemes. Our approach is to find efficient composition by combining two independent primitives, authenticated encryption, and re-keying schemes, rather than designing new algorithms. We also give the precise definitions of privacy and authenticity for authenticated encryption in a leakage-resilient model, and then, we provide the security proofs for RCB in a leakage-resilient model. [ABSTRACT FROM AUTHOR]

Homomorphic encryption scheme is one of the useful tools for handling encrypted information in storage services. However, most of existing schemes have not been used in practical applications due to their inefficiency or lack of functionalities. For example, fully homomorphic encryption, which can provide arbitrary operations, is inefficient. On the other hand, other homomorphic encryptions, including additive homomorphic encryptions, which are efficient enough to be used in practice, are limited in operations for practical applications. In this paper, we devise a message-encoding technique which can split a message space of an additive homomorphic encryption into multiple sub-spaces for different messages. Our technique guarantees that we can deal with multiple sets of data (each data set is assigned to each sub-space), so that multiple data can be computed at once in an additive manner. Using our new technique, we construct two additive homomorphic encryptions with valuable properties. The first one is an additive homomorphic encryption scheme which can be used for evaluating some statistical information, such as the mean and the variance. To give a concrete scheme, we apply our technique to Paillier’s scheme which supports the additive homomorphism. Note that our scheme is the first additive homomorphic encryption which supports the evaluation of both the mean and the variance of encrypted data. We also give two modifications of the first application to improve its practicality. As the second application of our technique, we propose an additive homomorphic encryption scheme which can support the functionality of error detection in homomorphic operations. The second scheme is also designed based on Paillier’s scheme. Note that one of the remarkable advantages of our technique is that it can be applied to any additive homomorphic encryption for supporting the above-mentioned functionalities. [ABSTRACT FROM AUTHOR]

Searchable encryption is an encryption system which provides confidentiality of stored documents and usability of document search at the same time. Remote cloud storage is the most typical application for searchable encryption. By applying searchable encryption, inside attacks can be prevented fundamentally. Designing searchable encryption which supports various queries-for example, range query, conjunctive keyword query, etc.-is also important for convenience. In this paper, we focus on range query problem. Up to now, only a few results have been proposed, in which the main functions are constructed using public key cryptosystems. Therefore, the amount of computations for encryption and search is large. Furthermore, search time depends on the size of the entire database. We propose a new searchable encryption protocol which is based on a symmetric key encryption and linked chain structure instead of public key-based techniques. The main contribution of the protocol is reducing the computation cost for search remarkably. In reality, the amount of computations depends on the number of documents that are matched to a query instead of the size of the entire database. [ABSTRACT FROM AUTHOR]

In order to hide information, Yu et al. (Appl Res Comput 26(3):1082-1083, 1103, ) presented a method by using the numerical value relation of three pixel values in spatial domain. Their algorithm is very easy to realize and has a big hiding capacity. But its visual performance is not very good, because it is based on spatial domain and cannot control the modification value effectively in edge region or texture region of image. Our work embedded watermark by comparing the numerical value relation of three neighboring DCT coefficients with Zig-Zag order of block image to enhance the visual performance. First, each block of the host image was transformed by DCT. Then the DCT coefficient matrix was scanned by Zig-Zag scanning order to ensure the continuity of the neighboring coefficients. And then through modifying the numerical value relation of three Zig-Zag neighboring DCT coefficients, the three corresponding watermark bits were embedded in. To further improve its performance, the algorithm also employed redundant encoding, watermark scrambling encryption techniques, etc. The experiments show that the algorithm can guarantee a better quality of watermarked image, and has stronger robust to general image processing operations than the method proposed by Yu et al. (Appl Res Comput 26(3):1082-1083, 1103, ). [ABSTRACT FROM AUTHOR]

In large-scale networks, such as cloud computing and Internet of Things, functional encryption mechanism provides a flexible and powerful cryptographic primitive in constructing the secure transmission and communication protocols. However, as the side-channel attacks in open environments, the attacker can gain partial sensitive information from the pre-defined system by virtue of the time, power analysis, cold-boot attacks, etc. In this work, we design a leakage-resilient functional encryption scheme, which tolerates amount of bounded master-key leakage and user private-key leakage. In our scheme, encryption policies are specified as point vectors and decryption roles are defined as affine subspaces. Role delegation is implemented by specifying the affine transformation over subspaces. Our scheme achieves payload hiding and attribute hiding in the sense that the attacker is able to specify any efficiently computable leakage functions and learns the function outputs taking the master/private keys as inputs. Also, our scheme can tolerate the continual leakage for master key and private key, since we can periodically update the master key and the private key to generate a new and re-randomized key with the same distribution to the previous keys. We construct the scheme in composite-order bilinear groups and prove the security with dual system encryption methodology. We also analyze and discuss the performance of allowable leakage bound, leakage ratio and possible leakage probability. Our scheme has flexible applications in secure data communication and authorization delegation in open cloud computing systems. [ABSTRACT FROM AUTHOR]

Spatial crowdsourcing is a promising architecture for collecting various types of data online with the aid of participants’ powerful mobile devices. However, it is also associated with certain privacy and security issues, which can reduce the quality of the crowdsourcing service. Some crowd tasks require the collection of connected data points. When a location-anonymous method is employed to ensure the privacy of location data points, the location trajectory data may become meaningless. To solve the privacy problem for trajectory data in large-scale crowdsourcing systems, we proposed a spatial task management method for privacy-preserving trajectory-based crowdsourcing, using a 3DES encryption and compressive-sensing-based trajectory data decryption method which is called DES-TraVec (3DES-based trajectory vector) cryptography algorithm. To provide a real-time crowdsourcing service, we proposed the use of an extended TPR*-Tree to bulk load the crowdsourcing results and manage the benders service requests so that the proposed method could support participants’ privacy and ensure quick answers for crowdsourcing services. The experimental results demonstrated that the proposed method is efficient in preserving trajectory-based crowdsourcing data and is faster than the current method. [ABSTRACT FROM AUTHOR]

Due to the limited computational capability of mobile devices, the research organization and academia are working on computationally secure schemes that have capability for offloading the computational intensive data access operations on the cloud/trusted entity for execution. Most of the existing security schemes, such as proxy re-encryption, manager-based re-encryption, and cloud-based re-encryption, are based on El-Gamal cryptosystem for offloading the computational intensive data access operation on the cloud/trusted entity. However, the resource hungry pairing-based cryptographic operations, such as encryption and decryption, are executed using the limited computational power of mobile device. Similarly, if the data owner wants to modify the encrypted file uploaded on the cloud storage, after modification the data owner must encrypt and upload the entire file on the cloud storage without considering the altered portion(s) of the file. In this paper, we have proposed an incremental version of proxy re-encryption scheme for improving the file modification operation and compared with the original version of the proxy re-encryption scheme on the basis of turnaround time, energy consumption, CPU utilization, and memory consumption while executing the security operations on mobile device. The incremental version of proxy re-encryption scheme shows significant improvement in results while performing file modification operations using limited processing capability of mobile devices. [ABSTRACT FROM AUTHOR]

In multi-privileged group communications, since users, who can subscribe to different data streams according to their interests, have multiple access privileges, security issues are more difficult to be solved than those in traditional group communications. The common drawback of traditional key management schemes is that they will result in the 'one-affect-many' problem, because they use a key graph to manage all the keys in a group, which makes one key being shared by many users. Recently, a key-policy attribute-based encryption (KP-ABE) scheme is proposed to encrypt messages to multiple users efficiently, which has been applied in secure multi-privileged group communications. However, user revocation in KP-ABE is still not resolved when applied to multi-privileged group communications. So, in this paper, by uniquely combining a collusion-resistant broadcast encryption system and a KP-ABE system with a non-monotone access structure, we propose a scalable encryption scheme for multi-privileged group communications (EMGC). Based on the features of different multi-privileged group communication systems, we also propose two constructions for our EMGC scheme. With the two constructions, a system can support a user not only to join/leave a group at will, but also to change his access privilege on demand, and the expenses during rekeying operations are small. Therefore, our scheme, which can accommodate a dynamic group of users, is more applicable to multi-privileged group communications. [ABSTRACT FROM AUTHOR]

In this paper, we describe a privacy manager for cloud computing that controls policy-based obfuscation and de-obfuscation of personal, sensitive, or confidential data within cloud service provision. By these means, cloud computing users may reduce the risk of their private data being stolen or misused, and in addition assistance may be given to cloud computing providers in helping them conform to privacy law. We describe different possible architectures for such privacy management in cloud computing, give an algebraic description of obfuscation features provided by the privacy manager, and describe how policies may be defined to control such obfuscation. Furthermore, we assess the performance and scalability of this approach and consider mechanisms to enhance usability. Several examples of how the privacy manager might be used are given, including protection of private metadata associated with online photos and of confidential information contained within share portfolios. [ABSTRACT FROM AUTHOR]

Privacy preservation in a distributed environment is a challenging task as it requires efficient control strategies for authentication and integrity preservation of various users and applications. In a distributed environment, most of the data items are distributed among various parties which may be located across different geographical locations. In the literature, most of the techniques proposed for privacy preserving consider only two parties collaboration for data items sharing using data perturbation and homomorphic encryption technique. Since data perturbation is less accurate and homomorphic encryption incurs high computation cost, so to fill these gaps, this paper proposes a Cloud-based Multi-party Privacy Preserving Classification Scheme (ClaMPP), which uses Naive Bayesian Classifier using multi-party random masking and polynomial aggregation technique for privacy preservation among different parties. The proposed ClaMPP scheme consists of four protocols which are described as follows. Protocols I and II are used to calculate conditional probabilities between the item vectors in a secure manner by using Privacy Preserving Conditional Probability Protocol. In the protocol III, the prior probabilities between the item vectors are computed by using additive property of Paillier homomorphic encryption technique. The naive Bayesian classification model constructed from the calculated values from protocols I, II and III is used in protocol IV to generate the predictions for items based on user's interest. Three datasets MovieLens100K, MovieLens20M and Jester are used in ClaMPP to analyse the privacy, accuracy and overhead costs incurred. It has been experimentally demonstrated that the proposed scheme is secure, and the privacy preservation does not affect the accuracy of the prediction. Comparative analysis of ClaMPP has been done with other related schemes based on off-line model computation cost. It has been demonstrated from the results obtained that computation cost decreases significantly in comparison with the other state-of-art techniques. [ABSTRACT FROM AUTHOR]

Public-key encryption is an important security mechanism used in cloud environment. To ensure the confidentiality of data encrypted using public-key encryption, countermeasures against cryptographic key leakage by side-channel attacks should be applied to the encryption scheme implemented both in locality and in cloud server. Traditional public-key encryption does not capture side-channel attacks. Moreover, the adversary can inject fault to tamper with the secret key and observe the output of the public-key encryption scheme under this modified key which is called "tampering attack". In this paper, we present two continuous leakage and tampering resilient CCA secure public-key encryption schemes. For implementations of our schemes during the key update, bounded number of tampering queries for arbitrary key relations and bounded leakage is allowed. By updating the secret key, our schemes are secure against continuous leakage and tampering attacks. [ABSTRACT FROM AUTHOR]

In this paper, we proposed an secure IoT framework to ensure an End-To-End security from an IoT application to IoT devices. The proposed IoT framework consists of the IoT application, an IoT broker and the IoT devices. The IoT devices can be deployed along a board line or a boundary of the area of IoT broker. The IoT broker manages their own devices and aggregates their sensing data. The IoT application provides users with IoT services. To use the IoT services, it needs to access to sensing data. Especially, the case of real-time healthcare services should consider intermediate security issues because medical information of patients is one of very sensitive privacy information. However, most of IoT protocols such as CoAP and MQTT have no concern about the End-To-End security, they only depended on the security of DTLS. Therefore, we proposed a new IoT framework to satisfy the End-To-End security feature under the CoAP communication. The proposed framework encrypts sensitive data by a symmetric encryption and an attribute-based encryption for efficiencies of communication and computation costs. In addition, each IoT device has a unique identification used as one of their attributes. Consequently, although the IoT broker is one of the intermediate nodes, it decrypts and shows data only if it satisfies all attributes. [ABSTRACT FROM AUTHOR]

Radio frequency identification (RFID) technology enables unique identification and tracking of the tag attached to an object. Widespread usage of RFID technologies in supply chain management (SCM) has drawn attention for developing security protocols to protect data stored in the tag. In SCM objects move from one place/department to another, the same RFID readers are not used throughout the supply chain. So, current reader delegates its access right to the new reader. When an object is moved inside the organization, delegation takes place between the readers. Many of the existing delegation protocols use trusted third party (TTP), which is practically difficult to incorporate or requires a keyed hash function/symmetric key encryption to be executed in the RFID tag, whereas tags are computationally intensive. Our work aims to simplify the delegation process by removing the usage of a TTP as well as eliminating reader-to-reader communication which avoids fixing the reader sequence in advance. Also, it preserves the security and privacy requirements for cloud-based applications. The proposed protocol withstands many attacks like tracing attack, tag impersonation attack, reader impersonation attack, and privacy attack. The proposed protocol not only resists the above-mentioned attacks but also achieves mutual authentication, anonymity property, and forward/backward secrecy. The proposed protocol is analyzed formally using GNY logic, which ensures that the protocol achieves mutual authentication. Performance analysis is carried out and it shows that our protocol is relatively better than the existing related schemes with respect to tag computation and communication cost. [ABSTRACT FROM AUTHOR]

Present advanced precise race detection techniques leverage strict causal relation to locate data races, leading to false negatives and missing many hidden races. In this paper, we present a novel race detection technique, called DigHR, which can detect more hidden races than existing precise techniques. DigHR is based on a weak causal relation, called afterward-confirm (AC) relation, which relaxes restrictions of existing causal relations and is proved to be sound. To represent AC relations between events, we propose a new data structure, called water-flow graph, which enable DigHR to analyze AC relations and detect hidden races at run-time. We have implemented DigHR in C/C++ and evaluated the effectiveness of DigHR by detecting races from real-world benchmarks and applications. The experimental results show that DigHR can precisely detect 21% more races than previous techniques, including FastTrack and CP. [ABSTRACT FROM AUTHOR]

Cloud storage is one of the most important applications in our daily lives. User can store their own data into cloud storage and remotely access the saved data. Owing to the social media develops, users can share the digital files to other users, leading to the amount of data growing rapidly and searching abilities necessarily. In the some cases, servers cannot avoid data leakage even if the server provides complete access control. The encrypted data is a best way to resolve this problem but it may eliminate original structure and searching may become impossible. Applying searchable encryption for each receiver may produce messy duplication and occupy the quota of cloud storage from each receiver. User requires keeping their shared documents belonging up to date which are compared with the latest version. To this aim, we thus propose a sharable ID-based encryption with keyword search in cloud computing environment, which enables users to search in data owners' shared storage while preserving privacy of data. For the performance analysis, we demonstrate the compared resultant with others ID-based or ID-relative encryption. In addition to that, we show the formal proof to verify the security of our proposed. [ABSTRACT FROM AUTHOR]

Secret sharing (SS) schemes based on cellular automata (CA) are considered as secure encrypting algorithms, where several secret data can be shared among some persons. Recently the SS schemes can be applied to solve real-world problems, such as security in cloud computing. The principal obstacle of use of the SS scheme is its considerably high computational cost; especially if a large amount of secret data must be encrypted and shared. In this work, we propose a parallel CA-based SS scheme suitable for any kinds of digital data in the graphic processing unit using compute unified device architecture technology. The uses of global memory and shared memory are analyzed from computational effectiveness and security points of view. The experimental results show the proposed parallel implementation provides a speedup rate more than 18-fold compared with its sequential implementation. Also we show the increase of the security level of the parallel implementation with respect to the sequential implementation. [ABSTRACT FROM AUTHOR]

In the paper we use recently proposed cellular automata (CA) based methodology (Szaban and Seredynski in LNCS, vol. 5191, pp. 478-485, ) to design the 6×4 S-boxes functionally equivalent to S-boxes used in current cryptographic standard known as Data Encryption Standard (DES). We provide an exhaustive experimental analysis of the proposed CA-based S-boxes in terms of non-linearity, autocorrelation, balance and strict avalanche criterion, and compare results with ones corresponding to DES S-boxes. We show that the proposed CA-based S-boxes have cryptographic properties comparable to or better than classical S-box tables. The interesting feature of the proposed S-boxes is a dynamic flexible structure fully functionally realized by CA, while the classical DES S-boxes are represented by predefined unchangeable table structures. [ABSTRACT FROM AUTHOR]

In this paper, we present a new pseudorandom number generator (PRNG) on graphics processing units (GPU). This PRNG is based on the so-called chaotic iterations. It is firstly proven to be chaotic according to the Devaney's formulation. We, thus, propose an efficient implementation for GPU that successfully passes the BigCrush tests, deemed to be the hardest battery of tests in TestU01. Experiments show that this PRNG can generate about 20 billion of random numbers per second on Tesla C1060 and NVidia GTX280 cards. It is then established that under reasonable assumptions, the proposed PRNG can be cryptographically secure. A chaotic version of the Blum-Goldwasser asymmetric key encryption scheme is finally proposed. [ABSTRACT FROM AUTHOR]

Authentication is an important security requirement for session initiation protocol (SIP). The conventional authentication method for SIP is HTTP Digest authentication which is insecure against several security attacks. Hence, several authentication schemes have been proposed for SIP. Most recently, Jiang et al. and Yeh et al. proposed two separate authentication and key agreement schemes for SIP using smart cards. The present paper shows that Jiang et al.'s scheme is vulnerable to user impersonation attacks and Yeh et al.'s scheme is insecure against offline password guessing attacks and does not provide perfect forward secrecy. Furthermore, in order to overcome the mentioned drawbacks, this paper proposes a new two-factor authentication and key agreement scheme for SIP. Security and performance analyses show that the proposed scheme not only enhances the security, but also improves the efficiency. [ABSTRACT FROM AUTHOR]

As an emerging patient-centric model of health information exchange, personal health record (PHR) is often outsourced to be stored at a third party. The value of PHR data is its long-term cumulative record relevant with personal health which can be significant in the future when faced with disease occurrences. As a promising public key primitive, attribute-based encryption (ABE) has been used to design PHR sharing systems. However, the existing solutions fail to achieve several important security objectives, that is, no need for a single authority to issue private keys to all PHR users, user access privacy protection, and user accountability. In this paper, we propose a multi-authority ciphertext-policy ABE scheme with user accountability and apply it to design an attribute-based PHR sharing system. In the proposed solution, the access policy is hidden and hence user access privacy is protected. In particular, the global identity of a misbehaving PHR user who leaked the decryption key to other unauthorized users can be traced, and thus the trust assumptions on both the authorities and the PHR users are reduced. Extensive analysis shows that the proposed scheme is provably secure and efficient. [ABSTRACT FROM AUTHOR]

The RSA public-key cryptosystem is an algorithm that converts a plain-text to its corresponding cipher-text, and then converts the cipher-text back into its corresponding plain-text. In this article, we propose five DNA-based algorithms-parallel adder, parallel subtractor, parallel multiplier, parallel comparator, and parallel modular arithmetic-that construct molecular solutions for any (plain-text, cipher-text) pair for the RSA public-key cryptosystem. Furthermore, we demonstrate that an eavesdropper can decode an encrypted message overheard with the linear steps in the size of the encrypted message overheard. [ABSTRACT FROM AUTHOR]

Generally, in mobile communication environments, Wireless Authentication and Key Establishment (WAKE) protocols are essential for secure information transmission. Key Recovery (KR) protocols, including WAKE protocols, can enable an authorized third party to gain access to encrypted message data under certain lawful circumstances. However, it is not easy to construct secure and strongly privacy-preserved KR protocols for mobile communication environments due to mobile hardware resources' limitation. In this paper, we propose a security-enhanced KR protocol and then we construct a privacy-enhanced KR protocol, which is based on the security-enhanced KR protocol, for protecting users' location privacy. [ABSTRACT FROM AUTHOR]

In the current world that we live in, of rapid growing technology, and especially reliance on the Internet for our daily lively hood (Banking, shopping, entertainment, news), and also with current crimes (Identity-theft, hacking, spyware), computer security is becoming more and more important. By “computer security” we often refer to addressing three important aspects of a computer-related system: Confidentiality, integrity, and availability. Encryption clearly addresses the need for confidentiality of data, both in storage and transmission. However, the use of encryption can be cumbersome and time consuming. It is important to have a fast algorithm to both encrypt and decrypt data as needed. Public key encryption, though secure, is definitely not fast enough to be used for large size data. We introduce a Parallel Algorithm for computation of inverses of matrices modulo n. This is used in conjunction with Block Ciphers and Hill Ciphers in symmetric encryption and decryption of data for transmission on open lines. Experimental studies were done to compare the run-time of this algorithm on parallel machines, to the traditional one. The new algorithm was found to perform much better than the traditional one, and would be useful to use in encryption/decryption of large sensitive data. [ABSTRACT FROM AUTHOR]

With the tremendous growth of cloud computing, verifiable computation has been firstly formalized by Gennaro et al. and then studied widely to provide integrity guarantees in the outsourced computation. However, existing verifiable computation protocols either work in the secret key setting or in the public key setting, namely, work either for single client or for all clients, which rules out some practical applications with access control policies. In this paper, we introduce and formalize the notion of verifiable computation with access control (AC-VC), in which only the computationally weak clients with necessary access control permissions can be allowed by a trusted source to apply the outsourced computation of a function to a server. We present a formal security definition and a proved secure black-box construction for AC-VC. This construction is built based on any verifiable computation in the secret key model and ciphertext-policy attribute-based encryption (CP-ABE). The access control policies that our AC-VC can realize depend on that realized in the based CP-ABE. [ABSTRACT FROM AUTHOR]

In broadband wireless technology, due to having many salient advantages, such as high data rates, quality of service, scalability, security, mobility, etc., LTE-A currently has been one of the trends of wireless system development. This system provides several sophisticated authentication and encryption techniques to enhance its system security. However, LTE-A still suffers from various attacks, like eavesdropping and replay attacks. Therefore, in this paper, we propose a novel security scheme, called the security system for a 4G environment (Se4GE for short), which as an LTE-A-based system integrates the RSA and Diffie-Hellman algorithms to solve some of LTE-A's security drawbacks where LTE-A stands for LTE-Advance which is a 4G system. The Se4GE is an end-to-end ciphertext transfer mechanism which dynamically changes encryption keys to enforce the security of data transmission in an LTE-A system. The Se4GE also produces several logically connected random keys, called the intelligent protection-key chain, which invokes two encryption/decryption techniques to provide users with broader demands for security services. The analytical results show that the Se4GE has higher security level than that of an LTE-A system. [ABSTRACT FROM AUTHOR]

Cloud computing is ideal for image storage and processing because it provides enormously scalable storage and processing resources at low cost. One of the major drawbacks of cloud computing, however, is the lack of robust mechanisms for the users to control the privacy of the data they farm out to the clouds. In this paper, we develop an image encoding scheme that enhances the privacy of image data that is outsourced to the clouds for processing. Unlike previously proposed image encryption schemes, our encoding scheme allows different forms of pixel-level image processing to take place in the clouds while the actual image is not revealed to the cloud provider. Our encoding scheme uses a chaotic map to transform the image after it is masked with an arbitrarily chosen ambient image. We use template matching as a common image processing task to demonstrate the ability of our scheme to perform computations on privacy enhanced images. A simplified prototype of the image processing system was implemented and the experimental results are presented in this paper. [ABSTRACT FROM AUTHOR]

The deployment of virtual network functions (VNFs) at edge servers potentially impairs the performance of latency-sensitive applications due to their computational cost. This work considers a new approach to addressing this problem that provides line rate acceleration of VNFs by employing field-programmable gate array (FPGA) equipped edge servers. This approach has been validated by practical use cases with both TCP and UDP as underlying protocol on a physical testbed environment. We examine the performance implications of executing a security VNF at an FPGA-equipped edge server. We experimentally demonstrate reduced VNF execution latency and energy consumption for a real-time video streaming application in comparison with a software-only baseline. In particular, the results show that the approach lowers VNF execution latency and power consumption at the edge by up to 44% and 76%, respectively, in our experiments while satisfying time constraints and maintaining confidentiality with high scalability. We also highlight the potential research challenges to make this approach viable in practice. [ABSTRACT FROM AUTHOR]

In recent years, the need for high-performance network monitoring tools, which can cope with rapidly increasing network bandwidth, has become vital. A possible solution is to utilize the processing power of multi-core processors that nowadays are available as commercial-off-the-shelf (COTS) hardware. In this paper, we introduce a software solution for wire-speed packet capturing and transmission for TCP/IP networks under Linux operating system, called DashCap. The results of our experimental evaluations show that the proposed solution causes more than two times performance boost for packet capturing in comparison to the existing software solutions under Linux. We have proposed a scalable software architecture for network monitoring tools called DashNMon, which is based on DashCap. Multi-core awareness is a distinguished property of this architecture. Comparing to the existing cluster-based solutions, DashNMon can be used with COTS multi-core processors. In order to evaluate the proposed solutions, we have developed several prototype tools. The results of the experiments carried out using these tools show the scalability and high performance of the network monitoring tools that are based on the proposed architecture. Using the proposed architecture, it is possible to design and implement high-performance multi-threaded network intrusion detection systems (NIDSs) or application-layer firewalls, completely in the user space and with better utilization of the computational resources of multi-processor/multi-core systems. [ABSTRACT FROM AUTHOR]