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Despite the widespread application of deep neural networks in finance, medical treatment, and autonomous driving, these networks face multiple security threats, such as maliciously constructed adversarial samples that can easily mislead deep neural network model classification, causing errors. Therefore, creating an interpretable model or designing an interpretation method is necessary to improve its security. This paper presents an interpretation scheme, named Convergent Interpretation for Deep Neural Networks (CIDNN), to obtain a provably convergent and consistent interpretation for deep neural networks. The main idea of CIDNN is to first convert the deep neural networks into a set of mathematically convergent Piecewise Linear Neural Networks (PLNN), then convert the PLNN into a set of equivalent linear classifiers. In this way, each linear classifier can be interpreted by its decision features. By analyzing the convergence of the local approximation interpretation scheme, we prove that this interpretable model can be sufficiently close to the deep neural network with certain conditions. Experiments show the convergence of CIDNN’s interpretation, and the interpretation conforms with similar samples in the synthetic dataset. Besides, we demonstrate the semantical meaning of CIDNN in the Fashion-MNIST dataset.
Xia Lei; Yongkai Fan; Kuan-Ching Li; Arcangelo Castiglione; Qian Hu. High-precision linearized interpretation for fully connected neural network. Applied Soft Computing 2021, 109, 107572 .
AMA StyleXia Lei, Yongkai Fan, Kuan-Ching Li, Arcangelo Castiglione, Qian Hu. High-precision linearized interpretation for fully connected neural network. Applied Soft Computing. 2021; 109 ():107572.
Chicago/Turabian StyleXia Lei; Yongkai Fan; Kuan-Ching Li; Arcangelo Castiglione; Qian Hu. 2021. "High-precision linearized interpretation for fully connected neural network." Applied Soft Computing 109, no. : 107572.
In recent times, we can see a massive increase in the number of devices that are being connected to the internet. These devices include but are not limited to smartphones, IoT, and cloud networks. In comparison to other possible cyber-attacks, these days, hackers are targeting these devices with phishing attacks since it exploits human vulnerabilities rather than system vulnerabilities. In a phishing attack, an online user is deceived by a seemingly trusted entity to give their personal data, i.e., login credentials or credit card details. When this private information is leaked to the hackers, this information becomes the source of other sophisticated attacks. In recent times many researchers have proposed the machine learning-based approach to solve phishing attacks; however, they have used a large number of features to develop reliable phishing detection techniques. A large number of features requires large processing powers to detect phishing, which makes it very much unsuitable for resource constrained devices. To address this issue, we have developed a phishing detection approach that only needs nine lexical features for effectively detecting phishing attacks. We used ISCXURL-2016 dataset for our experimental purpose, where 11964 instances of legitimate and phishing URLs are used. We have tested our approach against different machine learning classifiers and have obtained the highest accuracy of 99.57% with the Random forest algorithm.
Brij B. Gupta; Krishna Yadav; Imran Razzak; Konstantinos Psannis; Arcangelo Castiglione; Xiaojun Chang. A novel approach for phishing URLs detection using lexical based machine learning in a real-time environment. Computer Communications 2021, 175, 47 -57.
AMA StyleBrij B. Gupta, Krishna Yadav, Imran Razzak, Konstantinos Psannis, Arcangelo Castiglione, Xiaojun Chang. A novel approach for phishing URLs detection using lexical based machine learning in a real-time environment. Computer Communications. 2021; 175 ():47-57.
Chicago/Turabian StyleBrij B. Gupta; Krishna Yadav; Imran Razzak; Konstantinos Psannis; Arcangelo Castiglione; Xiaojun Chang. 2021. "A novel approach for phishing URLs detection using lexical based machine learning in a real-time environment." Computer Communications 175, no. : 47-57.
The concept of software-defined Internet of Things (SD-IoT) is becoming even more widespread. SD-IoT enables us to realize programmable networks and business, simplifying the management of the Internet of Things (IoT) and improving the IoT flexibility and scalability. However, with the promotion of SD-IoT-based applications and services, security issues in SD-IoT networks have become increasingly prominent. Aimed to deal with such issues, in this paper, we propose a two-stage intrusion detection approach for SD-IoT networks. It can more intelligently detect attacks under SD-IoT networks. In particular, we use the differential evolution algorithm's mutation mechanism to improve the firefly algorithm to solve the existing firefly algorithm's problems, such as slow convergence speed, easy to fall into local optimum on complex problems, and low accuracy. Next, based on the wrapper feature selection method, the selected features are sent to a novel ensemble classifier, composed of the C4.5 decision tree, multilayer perceptron, and instance-based learning. Again, the proposed approach uses the weighted voting method to determine whether network traffic is abnormal. Our proposal's detection performance is evaluated in binary and multiclass classifications by adopting the NSL-KDD and UNSW-NB15 public data sets. Experimental results show that the proposed multiclass classification approach's accuracy is 99.00% and 88.46%, respectively, while the false-positive rate is 0.81% and 4.16%, respectively. Finally, experimental results show that our proposal outperforms existing methods in terms of detection performance.
Qiuting Tian; Dezhi Han; Meng-Yen Hsieh; Kuan-Ching Li; Arcangelo Castiglione. A two-stage intrusion detection approach for software-defined IoT networks. Soft Computing 2021, 1 -17.
AMA StyleQiuting Tian, Dezhi Han, Meng-Yen Hsieh, Kuan-Ching Li, Arcangelo Castiglione. A two-stage intrusion detection approach for software-defined IoT networks. Soft Computing. 2021; ():1-17.
Chicago/Turabian StyleQiuting Tian; Dezhi Han; Meng-Yen Hsieh; Kuan-Ching Li; Arcangelo Castiglione. 2021. "A two-stage intrusion detection approach for software-defined IoT networks." Soft Computing , no. : 1-17.
To enhance the consensus performance of Blockchain in the Green Internet of Things (G-IoT) and improve the static network structure and communication overheads in the Practical Byzantine Fault Tolerance (PBFT) consensus algorithm, in this paper, we propose a Credit Reinforce Byzantine Fault Tolerance (CRBFT) consensus algorithm by using reinforcement learning. The CRBFT algorithm divides the nodes into three types, each with different responsibilities: master node, sub-nodes, and candidate nodes, and sets the credit attribute to the node. The node’s credit can be adjusted adaptively through the reinforcement learning algorithm, which can dynamically change the state of nodes. CRBFT algorithm can automatically identify malicious nodes and invalid nodes, making them exit from the consensus network. Experimental results show that the CRBFT algorithm can effectively improve the consensus network’s security. Besides, compared with the PBFT algorithm, in CRBFT, the consensus delay is reduced by about 40%, and the traffic overhead is reduced by more than 45%. This reduction is conducive to save energy and reduce emissions.
Peng Chen; Dezhi Han; Tien-Hsiung Weng; Kuan-Ching Li; Arcangelo Castiglione. A novel Byzantine fault tolerance consensus for Green IoT with intelligence based on reinforcement. Journal of Information Security and Applications 2021, 59, 102821 .
AMA StylePeng Chen, Dezhi Han, Tien-Hsiung Weng, Kuan-Ching Li, Arcangelo Castiglione. A novel Byzantine fault tolerance consensus for Green IoT with intelligence based on reinforcement. Journal of Information Security and Applications. 2021; 59 ():102821.
Chicago/Turabian StylePeng Chen; Dezhi Han; Tien-Hsiung Weng; Kuan-Ching Li; Arcangelo Castiglione. 2021. "A novel Byzantine fault tolerance consensus for Green IoT with intelligence based on reinforcement." Journal of Information Security and Applications 59, no. : 102821.
Penetration testing (PT) is nowadays one of the most common and used activities to evaluate a given asset’s security status. Penetration testing aims to secure networks and highlights the security issues of such networks. More precisely, PT, which is used for proactive defense and information systems protection, is a structured process, made up of various phases that typically needs to be carried out within a limited period. In this work, we first define a modular semi-automatic approach, which allows us to collect and integrate data from various exploit repositories. These data are then used to provide the penetration tester (i.e., the pentester) with information on the best available tools (i.e., exploits) to conduct the exploitation phase effectively. Also, the proposed approach has been implemented through a proof of concept based on the Nmap Scripting Engine (NSE), which integrates the features provided by the Nmap Vulscan vulnerability scanner, and allows, for each vulnerability detected, to find the most suitable exploits for this vulnerability. We remark that the proposed approach is not focused on the vulnerability mapping phase, which is carried out through Vulscan. Instead, it is focused on the automatic finding of the exploits that can be used to take advantage of the results achieved by such a phase.
Arcangelo Castiglione; Francesco Palmieri; Mariangela Petraglia; Raffaele Pizzolante. Vulsploit: A Module for Semi-automatic Exploitation of Vulnerabilities. Transactions on Petri Nets and Other Models of Concurrency XV 2020, 89 -103.
AMA StyleArcangelo Castiglione, Francesco Palmieri, Mariangela Petraglia, Raffaele Pizzolante. Vulsploit: A Module for Semi-automatic Exploitation of Vulnerabilities. Transactions on Petri Nets and Other Models of Concurrency XV. 2020; ():89-103.
Chicago/Turabian StyleArcangelo Castiglione; Francesco Palmieri; Mariangela Petraglia; Raffaele Pizzolante. 2020. "Vulsploit: A Module for Semi-automatic Exploitation of Vulnerabilities." Transactions on Petri Nets and Other Models of Concurrency XV , no. : 89-103.
The Time-based One-Time Password (TOTP) algorithm is commonly used for two-factor authentication. In this algorithm, a shared secret is used to derive a One-Time Password (OTP). However, in TOTP, the client and the server need to agree on a shared secret (i.e., a key). As a consequence, an adversary can construct an OTP through the compromised key if the server is hacked. To solve this problem, Kogan et al. proposed T/Key, an OTP algorithm based on a hash chain. However, the efficiency of OTP generation and verification is low in T/Key. In this article, we propose a novel and efficient Merkle tree-based One-Time Password (MOTP) algorithm to overcome such limitations. Compared to T/Key, this proposal reduces the number of hash operations to generate and verify the OTP, at the cost of small server storage and tolerable client storage. Experimental analysis and security evaluation show that MOTP can resist leakage attacks against the server and bring a tiny delay to two-factor authentication and verification time.
Xinming Yin; Junhui He; Yi Guo; Dezhi Han; Kuan-Ching Li; Arcangelo Castiglione. An Efficient Two-Factor Authentication Scheme Based on the Merkle Tree. Sensors 2020, 20, 5735 .
AMA StyleXinming Yin, Junhui He, Yi Guo, Dezhi Han, Kuan-Ching Li, Arcangelo Castiglione. An Efficient Two-Factor Authentication Scheme Based on the Merkle Tree. Sensors. 2020; 20 (20):5735.
Chicago/Turabian StyleXinming Yin; Junhui He; Yi Guo; Dezhi Han; Kuan-Ching Li; Arcangelo Castiglione. 2020. "An Efficient Two-Factor Authentication Scheme Based on the Merkle Tree." Sensors 20, no. 20: 5735.
Debiao He; Gerhard Hancke; Arcangelo Castiglione; Weizhi Meng. Introduction to the special section on blockchain techniques for the internet of vehicles security (VSI-bciov). Computers & Electrical Engineering 2020, 87, 106860 .
AMA StyleDebiao He, Gerhard Hancke, Arcangelo Castiglione, Weizhi Meng. Introduction to the special section on blockchain techniques for the internet of vehicles security (VSI-bciov). Computers & Electrical Engineering. 2020; 87 ():106860.
Chicago/Turabian StyleDebiao He; Gerhard Hancke; Arcangelo Castiglione; Weizhi Meng. 2020. "Introduction to the special section on blockchain techniques for the internet of vehicles security (VSI-bciov)." Computers & Electrical Engineering 87, no. : 106860.
In today’s interconnected society, cyberattacks have become more frequent and sophisticated, and existing intrusion detection systems may not be adequate in the complex cyberthreat landscape. For instance, existing intrusion detection systems may have overfitting, low classification accuracy, and high false positive rate (FPR) when faced with significantly large volume and variety of network data. An intrusion detection approach based on improved deep belief network (DBN) is proposed in this paper to mitigate the above problems, where the dataset is processed by probabilistic mass function (PMF) encoding and Min-Max normalization method to simplify the data preprocessing. Furthermore, a combined sparsity penalty term based on Kullback-Leibler (KL) divergence and non-mean Gaussian distribution is introduced in the likelihood function of the unsupervised training phase of DBN, and sparse constraints retrieve the sparse distribution of the dataset, thus avoiding the problem of feature homogeneity and overfitting. Finally, simulation experiments are performed on the NSL-KDD and UNSW-NB15 public datasets. The proposed method achieves 96.17% and 86.49% accuracy, respectively. Experimental results show that compared with the state-of-the-art methods, the proposed method achieves significant improvement in classification accuracy and FPR.
Qiuting Tian; Dezhi Han; Kuan-Ching Li; Xingao Liu; Letian Duan; Arcangelo Castiglione. An intrusion detection approach based on improved deep belief network. Applied Intelligence 2020, 50, 3162 -3178.
AMA StyleQiuting Tian, Dezhi Han, Kuan-Ching Li, Xingao Liu, Letian Duan, Arcangelo Castiglione. An intrusion detection approach based on improved deep belief network. Applied Intelligence. 2020; 50 (10):3162-3178.
Chicago/Turabian StyleQiuting Tian; Dezhi Han; Kuan-Ching Li; Xingao Liu; Letian Duan; Arcangelo Castiglione. 2020. "An intrusion detection approach based on improved deep belief network." Applied Intelligence 50, no. 10: 3162-3178.
In recent years, the automotive industry has made significant investments in the Internet of Things (IoT) paradigm, aiming to develop technologies and services for connected vehicles that focus on user-oriented solutions, providing unique and tailored driving experiences. Nowadays, the vehicles are connected to the car manufacturer network, the road operator networks, and the Internet. Such interconnections are used for infotainment applications and driving assistance services, such as real-time HD-maps, and road safety applications. For these reasons, the concept of the Internet of Vehicles (IoVs) is increasingly emerging and, vehicles become Internet terminals exposed to cyber-attacks. In this context, the main weakness is given by the Controller Area Network (CAN) protocol. This protocol, which governs the in-vehicle network, was designed to reduce transmission error problems and minimize latency times. However, it does not employ any security facility to protect the communication. In particular, one of the main issues of this protocol is that it uses unencrypted communication. Improving the security of this protocol is necessary while preserving its performance in terms of communication efficiency. This paper investigates the possibility of using lightweight block ciphers to secure in-vehicle devices such as microcontrollers, which have constrained hardware and software capabilities. The results obtained have shown that this proposal while guaranteeing a high degree of safety, has a negligible impact on the vehicle’s performance.
Arcangelo Castiglione; Francesco Palmieri; Francesco Colace; Marco Lombardi; Domenico Santaniello; Giuseppe D’Aniello. Securing the internet of vehicles through lightweight block ciphers. Pattern Recognition Letters 2020, 135, 264 -270.
AMA StyleArcangelo Castiglione, Francesco Palmieri, Francesco Colace, Marco Lombardi, Domenico Santaniello, Giuseppe D’Aniello. Securing the internet of vehicles through lightweight block ciphers. Pattern Recognition Letters. 2020; 135 ():264-270.
Chicago/Turabian StyleArcangelo Castiglione; Francesco Palmieri; Francesco Colace; Marco Lombardi; Domenico Santaniello; Giuseppe D’Aniello. 2020. "Securing the internet of vehicles through lightweight block ciphers." Pattern Recognition Letters 135, no. : 264-270.
Smart personal devices are assuming a fundamental role in the ubiquitous communication and computing arena. They provide new sophisticated cameras and new visual search interfaces and facilities that can drastically improve their presence and role in complex IoT-based critical infrastructures, such as healthcare monitoring and emergency systems, or remote access control facilities and smart authentication services. This new scenario calls for strong secure and resilient visual query mechanisms for these devices. In this work we propose an innovative secure visual search system, which is well-suited for ubiquitous computing scenarios empowered by modern smart personal devices. More precisely, we show how to insert, at the visual data acquisition time, a watermark inside the already compressed descriptor characterizing an MPEG-CDVS data stream used in visual queries, to make it possible to decode the watermark on the server side in order to improve the robustness against image-based identity spoofing. Such a security enforcement solution may be practical in several real-life applications involving visual queries performed from personal trusted devices, and it is particularly suitable in all those application domains that require performing visual queries with a high degree of security. It has been extensively tested and achieved satisfactory results: the presence of such a watermark does not affect the image matching performance and functionality.
Bruno Carpentieri; Arcangelo Castiglione; Alfredo De Santis; Francesco Palmieri; Raffaele Pizzolante; Xiaofei Xing. Securing visual search queries in ubiquitous scenarios empowered by smart personal devices. Information Sciences 2019, 508, 393 -404.
AMA StyleBruno Carpentieri, Arcangelo Castiglione, Alfredo De Santis, Francesco Palmieri, Raffaele Pizzolante, Xiaofei Xing. Securing visual search queries in ubiquitous scenarios empowered by smart personal devices. Information Sciences. 2019; 508 ():393-404.
Chicago/Turabian StyleBruno Carpentieri; Arcangelo Castiglione; Alfredo De Santis; Francesco Palmieri; Raffaele Pizzolante; Xiaofei Xing. 2019. "Securing visual search queries in ubiquitous scenarios empowered by smart personal devices." Information Sciences 508, no. : 393-404.
Conventional privacy‐enforcement mechanisms, such as encryption‐based ones, are frequently used to prevent third‐party eavesdroppers to intercept confidential information exchanged between two or more parties. However, the use of such mechanisms can be perceivable and it alerts the involved intercepting entities that could devote some effort in trying to remove the protection, eg, by cracking the encryption keys used or by exploiting the vulnerabilities of the technological solution used to protect the data. Sometimes, from the security point of view, avoiding to draw the attention or suspect to intermediate intercepting entities, may be better than protecting a data in a conventional manner. In such direction, one of the most effective approaches is hiding the secret information to be exchanged inside other data, through steganographic techniques. In this work, we exploit, for this specific purpose, the hierarchical structure of a compressed archive, as well as the algorithms and parameters used to create and maintain such archive. It is important to point out that, by doing this, the secret information is in no way semantically related to the contents of the compressed archive. This can be extremely useful in many cloud‐based situations where several confidential data is moved across multiple independent data center, which are under the control of different and not always fully trusted authorities. The effectiveness of this proposal has been assessed by using a properly designed and implemented prototype, where extensive tests have been performed within the context of a proof‐of‐concept.
Bruno Carpentieri; Arcangelo Castiglione; Alfredo De Santis; Francesco Palmieri; Raffaele Pizzolante. Compression‐based steganography. Concurrency and Computation: Practice and Experience 2019, 32, 1 .
AMA StyleBruno Carpentieri, Arcangelo Castiglione, Alfredo De Santis, Francesco Palmieri, Raffaele Pizzolante. Compression‐based steganography. Concurrency and Computation: Practice and Experience. 2019; 32 (8):1.
Chicago/Turabian StyleBruno Carpentieri; Arcangelo Castiglione; Alfredo De Santis; Francesco Palmieri; Raffaele Pizzolante. 2019. "Compression‐based steganography." Concurrency and Computation: Practice and Experience 32, no. 8: 1.
The weighted possibilistic c-means algorithm is an important soft clustering technique for big data analytics with cloud computing. However, the private data will be disclosed when the raw data is directly uploaded to cloud for efficient clustering. In this paper, a secure weighted possibilistic c-means algorithm based on the BGV encryption scheme is proposed for big data clustering on cloud. Specially, BGV is used to encrypt the raw data for the privacy preservation on cloud. Furthermore, the Taylor theorem is used to approximate the functions for calculating the weight value of each object and updating the membership matrix and the cluster centers as the polynomial functions which only include addition and multiplication operations such that the weighed possibilistic c-means algorithm can be securely and correctly performed on the encrypted data in cloud. Finally, the presented scheme is estimated on two big datasets, i.e., eGSAD and sWSN, by comparing with the traditional weighted possibilistic c-means method in terms of effectiveness, efficiency and scalability. The results show that the presented scheme performs more efficiently than the traditional weighted possiblistic c-means algorithm and it achieves a good scalability on cloud for big data clustering.
Qingchen Zhang; Laurence T. Yang; Arcangelo Castiglione; Zhikui Chen; Peng Li. Secure weighted possibilistic c-means algorithm on cloud for clustering big data. Information Sciences 2019, 479, 515 -525.
AMA StyleQingchen Zhang, Laurence T. Yang, Arcangelo Castiglione, Zhikui Chen, Peng Li. Secure weighted possibilistic c-means algorithm on cloud for clustering big data. Information Sciences. 2019; 479 ():515-525.
Chicago/Turabian StyleQingchen Zhang; Laurence T. Yang; Arcangelo Castiglione; Zhikui Chen; Peng Li. 2019. "Secure weighted possibilistic c-means algorithm on cloud for clustering big data." Information Sciences 479, no. : 515-525.
The guest editors of the IEEE Cloud Computing special issue on Biometrics-as-a-Service discuss the benefits and challenges of using cloud computing with biometric authentication systems as well as the articles included in this issue.
Silvio Barra; Kim-Kwang Raymond Choo; Michele Nappi; Arcangelo Castiglione; Fabio Narducci; Rajiv Ranjan. Biometrics-as-a-Service: Cloud-Based Technology, Systems, and Applications. IEEE Cloud Computing 2018, 5, 33 -37.
AMA StyleSilvio Barra, Kim-Kwang Raymond Choo, Michele Nappi, Arcangelo Castiglione, Fabio Narducci, Rajiv Ranjan. Biometrics-as-a-Service: Cloud-Based Technology, Systems, and Applications. IEEE Cloud Computing. 2018; 5 (4):33-37.
Chicago/Turabian StyleSilvio Barra; Kim-Kwang Raymond Choo; Michele Nappi; Arcangelo Castiglione; Fabio Narducci; Rajiv Ranjan. 2018. "Biometrics-as-a-Service: Cloud-Based Technology, Systems, and Applications." IEEE Cloud Computing 5, no. 4: 33-37.
The information obtained by means of spectral remote sensing (i.e., the hyperspectral images) are involved in several real-life scenarios and applications. Historical research, monitoring of environmental hazards, forensics and counter-terrorism are some examples of contexts in which the hyperspectral data play an important role. In many contexts, the hyperspectral images could also play sensitive roles (e.g., in military applications, etc.) and are generally exchanged among several entities, in order to carry out different tasks on them. Therefore, it is important to guarantee their protection. A meaningful choice is the protection through data hiding techniques. In fact, by means of reversible data hiding techniques, the imaging data become a sort of information carrier and can be used for delivering other important data that can be used, for instance, to check the integrity of the original imaging data. In this paper, we introduce a one-pass framework that is able to perform the lossless data hiding and the lossless compression of the marked stream, at the same time, by exploiting the capabilities of the predictive paradigm. Substantially, in a single pass, a marked and compressed stego image is obtained, which can be exactly restored by the receiver: by decompressing and reversibly reconstructing the original unaltered image. In addition, our framework also permits to perform only the decompression (without the extraction of the hidden information). In this manner, the resulting stego (marked) hyperspectral image, could be used for several purposes, in which it is not necessary to extract the original data and an acceptable grade of degradation is tolerated. We also implement a proof-of-concept of the proposed framework to assess the effectiveness of our contribution. Finally, we report the achieved experimental results, which outperform other similar approaches.
Bruno Carpentieri; Arcangelo Castiglione; Alfredo De Santis; Francesco Palmieri; Raffaele Pizzolante. One-pass lossless data hiding and compression of remote sensing data. Future Generation Computer Systems 2018, 90, 222 -239.
AMA StyleBruno Carpentieri, Arcangelo Castiglione, Alfredo De Santis, Francesco Palmieri, Raffaele Pizzolante. One-pass lossless data hiding and compression of remote sensing data. Future Generation Computer Systems. 2018; 90 ():222-239.
Chicago/Turabian StyleBruno Carpentieri; Arcangelo Castiglione; Alfredo De Santis; Francesco Palmieri; Raffaele Pizzolante. 2018. "One-pass lossless data hiding and compression of remote sensing data." Future Generation Computer Systems 90, no. : 222-239.
Several companies have recently emerged to provide online Direct-To-Consumer (DTC) DNA analysis and sequencing. Those activities will be, in the near future, the foundations of the emerging Internet of Living Things. The concept of Internet of Living Things has been introduced to characterize networks of biological sequencing sensors, which could rely on cloud-based analysis capabilities, to support the users in deeply studying DNA or other molecules. Sequencing sensors have many fields of application and much more will likely to come. In this context, DNA microarray images represent the core of modern genomic data analysis, since they allow the simultaneous monitoring of many thousands of genes and represent a sort of "container", not only for storing genomics data, but also for managing, sharing and exchanging such type of data.In this scenario, the ability to protect genomics and medical big data is a growing challenge. In particular, for what concerns DNA microarray images, the techniques commonly employed for data protection are not effective due for example to the unauthorized use or manipulation after decryption or the lost of metadata during image processing.In this paper we address the problem of protecting such type of information, by means of watermarking techniques. In particular, we propose reversible watermarking techniques explicitly tailored for the characteristics of DNA microarray images to ensure the protection of such images in terms of authenticity and integrity, besides enabling the binding of those imaging data with other information related to them. We assess the effectiveness and efficiency of our techniques by means of a working prototype
Raffaele Pizzolante; Arcangelo Castiglione; Bruno Carpentieri; Alfredo De Santis; Francesco Palmieri; Aniello Castiglione. On the protection of consumer genomic data in the Internet of Living Things. Computers & Security 2018, 74, 384 -400.
AMA StyleRaffaele Pizzolante, Arcangelo Castiglione, Bruno Carpentieri, Alfredo De Santis, Francesco Palmieri, Aniello Castiglione. On the protection of consumer genomic data in the Internet of Living Things. Computers & Security. 2018; 74 ():384-400.
Chicago/Turabian StyleRaffaele Pizzolante; Arcangelo Castiglione; Bruno Carpentieri; Alfredo De Santis; Francesco Palmieri; Aniello Castiglione. 2018. "On the protection of consumer genomic data in the Internet of Living Things." Computers & Security 74, no. : 384-400.
Christian Esposito; Arcangelo Castiglione; Francesco Palmieri; Massimo Ficco. Building a network embedded FEC protocol by using game theory. Information Sciences 2018, 433-434, 365 -380.
AMA StyleChristian Esposito, Arcangelo Castiglione, Francesco Palmieri, Massimo Ficco. Building a network embedded FEC protocol by using game theory. Information Sciences. 2018; 433-434 ():365-380.
Chicago/Turabian StyleChristian Esposito; Arcangelo Castiglione; Francesco Palmieri; Massimo Ficco. 2018. "Building a network embedded FEC protocol by using game theory." Information Sciences 433-434, no. : 365-380.
Lu Zhou; Quanlong Wang; Xin Sun; Piotr Kulicki; Arcangelo Castiglione. Quantum technique for access control in cloud computing II: Encryption and key distribution. Journal of Network and Computer Applications 2018, 103, 178 -184.
AMA StyleLu Zhou, Quanlong Wang, Xin Sun, Piotr Kulicki, Arcangelo Castiglione. Quantum technique for access control in cloud computing II: Encryption and key distribution. Journal of Network and Computer Applications. 2018; 103 ():178-184.
Chicago/Turabian StyleLu Zhou; Quanlong Wang; Xin Sun; Piotr Kulicki; Arcangelo Castiglione. 2018. "Quantum technique for access control in cloud computing II: Encryption and key distribution." Journal of Network and Computer Applications 103, no. : 178-184.
Bruno Carpentieri; Arcangelo Castiglione; Alfredo De Santis; Francesco Palmieri; Raffaele Pizzolante. Data hiding using compressed archives. Proceedings of the 2018 Conference on Research in Adaptive and Convergent Systems 2018, 136 -142.
AMA StyleBruno Carpentieri, Arcangelo Castiglione, Alfredo De Santis, Francesco Palmieri, Raffaele Pizzolante. Data hiding using compressed archives. Proceedings of the 2018 Conference on Research in Adaptive and Convergent Systems. 2018; ():136-142.
Chicago/Turabian StyleBruno Carpentieri; Arcangelo Castiglione; Alfredo De Santis; Francesco Palmieri; Raffaele Pizzolante. 2018. "Data hiding using compressed archives." Proceedings of the 2018 Conference on Research in Adaptive and Convergent Systems , no. : 136-142.
Nowadays Sensor Networks and Ad Hoc Networks are widely used communication facilities, mainly because of their many application settings. Again, though above types of network are paradigms of communication widespread and well-established in the state of the art, however, they turn out to be among the most important concepts underlying the modern and increasingly expanding User-Centric Networks, which can be used to build dynamic middleware services for heterogeneous distributed computing. In this way, can be addressed the strong dynamic behavior of user communities and of resource collections they use.In this paper we focus our attention on key predistribution for secure communications in those types of networks. In particular, we first analyze some schemes proposed in the literature for enabling a group of two or more nodes to compute a common key, which can be used later on to encrypt or authenticate exchanged messages. The schemes we have chosen are well representative of different design strategies proposed in the state of the art. Moreover, in order to find out under which conditions and in which settings a scheme is more suitable than others, we provide an evaluation and a performance comparison of those schemes. Furthermore, we look at the problem of identifying optimal values for the parameters of such schemes, with respect to a certain desirable security degree and reasonable security assumptions. Finally, we extend one of those schemes, showing both analytically and through experiments, the improvement the new scheme provides in terms of security compared to the basic one. User-Centric Networks can be used for dynamic heterogeneous distributed computing.We analyze key predistribution schemes for secure communications in those types of networks.We provide an evaluation and a performance comparison of those schemes.We look at the problem of identifying optimal values for parameters of such schemes.We improve one of those schemes with respect to the basic one.
Arcangelo Castiglione; Paolo D’Arco; Alfredo De Santis; Rosario Russo. Secure group communication schemes for dynamic heterogeneous distributed computing. Future Generation Computer Systems 2017, 74, 313 -324.
AMA StyleArcangelo Castiglione, Paolo D’Arco, Alfredo De Santis, Rosario Russo. Secure group communication schemes for dynamic heterogeneous distributed computing. Future Generation Computer Systems. 2017; 74 ():313-324.
Chicago/Turabian StyleArcangelo Castiglione; Paolo D’Arco; Alfredo De Santis; Rosario Russo. 2017. "Secure group communication schemes for dynamic heterogeneous distributed computing." Future Generation Computer Systems 74, no. : 313-324.
With the wide diffusion of cloud technologies, an ever increasing amount of sensitive data is moved on centralized network-based repository services, providing elastic outsourced storage capacity, available through remote access. This introduces new challenges associated to the security and privacy of outsourced data that has to be dynamically created, shared, updated and removed by a large number of users, characterized by different access rights and views structured according to hierarchical roles.To address such challenges, and implement secure access control policies in those application domains, several cryptographic solutions have been proposed. In particular, hierarchical key assignment schemes represent an effective solution to deal with cryptographic access control. Starting from the first proposal due to Akl and Taylor in 1983, many hierarchical key assignment schemes have been proposed. However, the highly dynamic nature of cloud-based storage solutions may significantly stress the applicability of such schemes on a wide scale.In order to overcome such limitations, in this work we provide new results on the AklTaylor scheme, by carefully analyzing the problem of supporting dynamic updates, as well as key replacement operations. In doing this, we also perform a rigorous analysis of the AklTaylor scheme in the dynamic setting characterizing storage clouds, by considering different key assignment strategies and proving that the corresponding schemes are secure with respect to the notion of key recovery.
Arcangelo Castiglione; Alfredo De Santis; Barbara Masucci; Francesco Palmieri; Xinyi Huang; Aniello Castiglione. Supporting dynamic updates in storage clouds with the Akl–Taylor scheme. Information Sciences 2017, 387, 56 -74.
AMA StyleArcangelo Castiglione, Alfredo De Santis, Barbara Masucci, Francesco Palmieri, Xinyi Huang, Aniello Castiglione. Supporting dynamic updates in storage clouds with the Akl–Taylor scheme. Information Sciences. 2017; 387 ():56-74.
Chicago/Turabian StyleArcangelo Castiglione; Alfredo De Santis; Barbara Masucci; Francesco Palmieri; Xinyi Huang; Aniello Castiglione. 2017. "Supporting dynamic updates in storage clouds with the Akl–Taylor scheme." Information Sciences 387, no. : 56-74.