Visible to the public Biblio

Found 1069 results

Filters: First Letter Of Title is C  [Clear All Filters]
Submitted
2020
Nooh, Sameer A..  2020.  Cloud Cryptography: User End Encryption. 2020 International Conference on Computing and Information Technology (ICCIT-1441). :1—4.
Cloud computing has made the life of individual users and work of business corporations so much easier by providing them data storage services at very low costs. Individual users can store and access their data through shared cloud storage service anywhere anytime. Similarly, business corporation consumers of cloud computing can store, manage, process and access their big data with quite an ease. However, the security and privacy of users' data remains vulnerable in cloud computing Availability, integrity and confidentiality are the three primary elements that users consider before signing up for cloud computing services. Many public and private cloud services have experienced security breaches and unauthorized access incidents. This paper suggests user end cryptography of data before uploading it to a cloud storage service platform like Google Drive, Microsoft, Amazon and CloudSim etc. The proposed cryptography algorithm is based on symmetric key cryptography model and has been implemented on Amazon S3 cloud space service.
Xu, Hui, Zhang, Wei, Gao, Man, Chen, Hongwei.  2020.  Clustering Analysis for Big Data in Network Security Domain Using a Spark-Based Method. 2020 IEEE 5th International Symposium on Smart and Wireless Systems within the Conferences on Intelligent Data Acquisition and Advanced Computing Systems (IDAACS-SWS). :1—4.
Considering the problem of network security under the background of big data, the clustering analysis algorithms can be utilized to improve the correctness of network intrusion detection models for security management. As a kind of iterative clustering analysis algorithm, K-means algorithm is not only simple but also efficient, so it is widely used. However, the traditional K-means algorithm cannot well solve the network security problem when facing big data due to its high complexity and limited processing ability. In this case, this paper proposes to optimize the traditional K-means algorithm based on the Spark platform and deploy the optimized clustering analysis algorithm in the distributed architecture, so as to improve the efficiency of clustering algorithm for network intrusion detection in big data environment. The experimental result shows that, compared with the traditional K-means algorithm, the efficiency of the optimized K-means algorithm using a Spark-based method is significantly improved in the running time.
Islam, M., Rahaman, S., Meng, N., Hassanshahi, B., Krishnan, P., Yao, D. D..  2020.  Coding Practices and Recommendations of Spring Security for Enterprise Applications. 2020 IEEE Secure Development (SecDev). :49—57.
Spring security is tremendously popular among practitioners for its ease of use to secure enterprise applications. In this paper, we study the application framework misconfiguration vulnerabilities in the light of Spring security, which is relatively understudied in the existing literature. Towards that goal, we identify 6 types of security anti-patterns and 4 insecure vulnerable defaults by conducting a measurement-based approach on 28 Spring applications. Our analysis shows that security risks associated with the identified security anti-patterns and insecure defaults can leave the enterprise application vulnerable to a wide range of high-risk attacks. To prevent these high-risk attacks, we also provide recommendations for practitioners. Consequently, our study has contributed one update to the official Spring security documentation while other security issues identified in this study are being considered for future major releases by Spring security community.
Kummerow, A., Monsalve, C., Rösch, D., Schäfer, K., Nicolai, S..  2020.  Cyber-physical data stream assessment incorporating Digital Twins in future power systems. 2020 International Conference on Smart Energy Systems and Technologies (SEST). :1—6.

Reliable and secure grid operations become more and more challenging in context of increasing IT/OT convergence and decreasing dynamic margins in today's power systems. To ensure the correct operation of monitoring and control functions in control centres, an intelligent assessment of the different information sources is necessary to provide a robust data source in case of critical physical events as well as cyber-attacks. Within this paper, a holistic data stream assessment methodology is proposed using an expert knowledge based cyber-physical situational awareness for different steady and transient system states. This approach goes beyond existing techniques by combining high-resolution PMU data with SCADA information as well as Digital Twin and AI based anomaly detection functionalities.

Javid, T., Faris, M., Beenish, H., Fahad, M..  2020.  Cybersecurity and Data Privacy in the Cloudlet for Preliminary Healthcare Big Data Analytics. 2020 International Conference on Computing and Information Technology (ICCIT-1441). :1—4.

In cyber physical systems, cybersecurity and data privacy are among most critical considerations when dealing with communications, processing, and storage of data. Geospatial data and medical data are examples of big data that require seamless integration with computational algorithms as outlined in Industry 4.0 towards adoption of fourth industrial revolution. Healthcare Industry 4.0 is an application of the design principles of Industry 4.0 to the medical domain. Mobile applications are now widely used to accomplish important business functions in almost all industries. These mobile devices, however, are resource poor and proved insufficient for many important medical applications. Resource rich cloud services are used to augment poor mobile device resources for data and compute intensive applications in the mobile cloud computing paradigm. However, the performance of cloud services is undesirable for data-intensive, latency-sensitive mobile applications due increased hop count between the mobile device and the cloud server. Cloudlets are virtual machines hosted in server placed nearby the mobile device and offer an attractive alternative to the mobile cloud computing in the form of mobile edge computing. This paper outlines cybersecurity and data privacy aspects for communications of measured patient data from wearable wireless biosensors to nearby cloudlet host server in order to facilitate the cloudlet based preliminary and essential complex analytics for the medical big data.

Dodson, Michael, Beresford, Alastair R., Richardson, Alexander, Clarke, Jessica, Watson, Robert N. M..  2020.  CHERI Macaroons: Efficient, host-based access control for cyber-physical systems. 2020 IEEE European Symposium on Security and Privacy Workshops (EuroS PW). :688–693.
Cyber-Physical Systems (CPS) often rely on network boundary defence as a primary means of access control; therefore, the compromise of one device threatens the security of all devices within the boundary. Resource and real-time constraints, tight hardware/software coupling, and decades-long service lifetimes complicate efforts for more robust, host-based access control mechanisms. Distributed capability systems provide opportunities for restoring access control to resource-owning devices; however, such a protection model requires a capability-based architecture for CPS devices as well as task compartmentalisation to be effective.This paper demonstrates hardware enforcement of network bearer tokens using an efficient translation between CHERI (Capability Hardware Enhanced RISC Instructions) architectural capabilities and Macaroon network tokens. While this method appears to generalise to any network-based access control problem, we specifically consider CPS, as our method is well-suited for controlling resources in the physical domain. We demonstrate the method in a distributed robotics application and in a hierarchical industrial control application, and discuss our plans to evaluate and extend the method.
Johnson, N., Near, J. P., Hellerstein, J. M., Song, D..  2020.  Chorus: a Programming Framework for Building Scalable Differential Privacy Mechanisms. 2020 IEEE European Symposium on Security and Privacy (EuroS P). :535–551.
Differential privacy is fast becoming the gold standard in enabling statistical analysis of data while protecting the privacy of individuals. However, practical use of differential privacy still lags behind research progress because research prototypes cannot satisfy the scalability requirements of production deployments. To address this challenge, we present Chorus, a framework for building scalable differential privacy mechanisms which is based on cooperation between the mechanism itself and a high-performance production database management system (DBMS). We demonstrate the use of Chorus to build the first highly scalable implementations of complex mechanisms like Weighted PINQ, MWEM, and the matrix mechanism. We report on our experience deploying Chorus at Uber, and evaluate its scalability on real-world queries.
Ponomarenko, Vladimir, Navrotskaya, Elena, Prokhorov, Mikhail, Lapsheva, Elena, Ishbulatov, Yuri.  2020.  Communication System Based on Chaotic Time-Delayed Feedback Generator. 2020 4th Scientific School on Dynamics of Complex Networks and their Application in Intellectual Robotics (DCNAIR). :192–194.
We study communication systems based on chaotic time-delayed feedback generator. The aim of the study is a comparative assessment of the noise immunity for the four different communication systems at the same levels of the external noise. It is shown that the principle of correlation receiver, which is used in classical communication systems, can be also used in the case where chaotic signals generated by self-oscillating systems with complex behavior are used as reference signals. Systems based on the correlation receiver principles have very high immunity to the external noise.
Boespflug, Etienne, Ene, Cristian, Mounier, Laurent, Potet, Marie-Laure.  2020.  Countermeasures Optimization in Multiple Fault-Injection Context. 2020 Workshop on Fault Detection and Tolerance in Cryptography (FDTC). :26–34.
Fault attacks consist in changing the program behavior by injecting faults at run-time, either at hardware or at software level. Their goal is to change the correct progress of the algorithm and hence, either to allow gaining some privilege access or to allow retrieving some secret information based on an analysis of the deviation of the corrupted behavior with respect to the original one. Countermeasures have been proposed to protect embedded systems by adding spatial, temporal or information redundancy at hardware or software level. First we define Countermeasures Check Point (CCP) and CCPs-based countermeasures as an important subclass of countermeasures. Then we propose a methodology to generate an optimal protection scheme for CCPs-based countermeasure. Finally we evaluate our work on a benchmark of code examples with respect to several Control Flow Integrity (CFI) oriented existing protection schemes.
Pialov, K., Slutsky, R., Maizel, A..  2020.  Coupled calculation of hydrodynamic and acoustic characteristics in the far-field of the ship propulsor. 2020 International Conference on Dynamics and Vibroacoustics of Machines (DVM). :1–6.
This report provides a calculation example of hydrodynamic and acoustic characteristics of the ship propulsor using numerical modelling with the help of RANS-models and eddy-resolving approaches in the hydrodynamics task, acoustic analogy in the acoustics tasks and harmonic analysis of the propulsor under hydrodynamic loads.
Atlidakis, V., Godefroid, P., Polishchuk, M..  2020.  Checking Security Properties of Cloud Service REST APIs. 2020 IEEE 13th International Conference on Software Testing, Validation and Verification (ICST). :387—397.

Most modern cloud and web services are programmatically accessed through REST APIs. This paper discusses how an attacker might compromise a service by exploiting vulnerabilities in its REST API. We introduce four security rules that capture desirable properties of REST APIs and services. We then show how a stateful REST API fuzzer can be extended with active property checkers that automatically test and detect violations of these rules. We discuss how to implement such checkers in a modular and efficient way. Using these checkers, we found new bugs in several deployed production Azure and Office365 cloud services, and we discuss their security implications. All these bugs have been fixed.

Djordjevic, Ivan B..  2020.  Cluster States-based Quantum Networks. 2020 IEEE Photonics Conference (IPC). :1—2.
We propose to implement multipartite quantum communication network (QCN) by employing the cluster- state-based concept. The proposed QCN can be used to: (i) perform distributed quantum computing, (ii) teleport quantum states between any two nodes in QCN, and (iii) enable next generation of cyber security systems.
Alamsyah, Zaenal, Mantoro, Teddy, Adityawarman, Umar, Ayu, Media Anugerah.  2020.  Combination RSA with One Time Pad for Enhanced Scheme of Two-Factor Authentication. 2020 6th International Conference on Computing Engineering and Design (ICCED). :1—5.
RSA is a popular asymmetric key algorithm with two keys scheme, a public key for encryption and private key for decryption. RSA has weaknesses in encryption and decryption of data, including slow in the process of encryption and decryption because it uses a lot of number generation. The reason is RSA algorithm can work well and is resistant to attacks such as brute force and statistical attacks. in this paper, it aims to strengthen the scheme by combining RSA with the One Time Pad algorithm so that it will bring up a new design to be used to enhance security on two-factor authentication. Contribution in this paper is to find a new scheme algorithm for an enhanced scheme of RSA. One Time Pad and RSA can combine as well.
Primo, Abena.  2020.  A Comparison of Blockchain-Based Wireless Sensor Network Protocols. 2020 11th IEEE Annual Ubiquitous Computing, Electronics Mobile Communication Conference (UEMCON). :0793—0799.
Wireless sensors are often deployed in environments where it is difficult for them to discern friend from enemy. An example case is a military tactical scenario, where sensors are deployed to map the location of an item but where some of the nodes have been compromised or where there are other malicious nodes present. In this scenario, sharing data with other network nodes may present a critical security risk to the sensor nodes. Blockchain technology, with its ability to house a secure distributed ledger, offers a possible solution. However, blockchain applications for Wireless Sensor Networks suffer from poor latency in block propagation which in turn decreases throughput and network scalability. Several researchers have proposed solutions for improved network throughput. In this work, a comparison of these existing works is performed leading to a taxonomy of existing algorithms. Characteristics consistently found in algorithms reporting improved throughput are presented and, later, these characteristics are used in the development of a new algorithm for improving throughput. The proposed algorithm utilizes a proof-of- authority consensus algorithm with a node trust-based scheme. The proposed algorithm shows strong results over the base case algorithm and was evaluated with blockchain network simulations of up to 20000 nodes.
Doğu, S., Alidoustaghdam, H., Dilman, İ, Akıncı, M. N..  2020.  The Capability of Truncated Singular Value Decomposition Method for Through the Wall Microwave Imaging. 2020 IEEE Microwave Theory and Techniques in Wireless Communications (MTTW). 1:76–81.
In this study, a truncated singular value decomposition (TSVD) based computationally efficient through the wall imaging (TWI) is addressed. Mainly, two different scenarios with identical and non-identical multiple scatterers behind the wall have been considered. The scattered data are processed with special scheme in order to improve quality of the results and measurements are performed at four different frequencies. Next, effects of selecting truncation threshold in TSVD methods are analyzed and a detailed quantitative comparison is provided to demonstrate capabilities of these TSVD methods over selection of truncation threshold.
Yang, Chien-Sheng, Avestimehr, A. Salman.  2020.  Coded Computing for Boolean Functions. 2020 International Symposium on Information Theory and Its Applications (ISITA). :141–145.
The growing size of modern datasets necessitates splitting a large scale computation into smaller computations and operate in a distributed manner for improving overall performance. However, adversarial servers in a distributed computing system deliberately send erroneous data in order to affect the computation for their benefit. Computing Boolean functions is the key component of many applications of interest, e.g., classification problem, verification functions in the blockchain and the design of cryptographic algorithm. In this paper, we consider the problem of computing a Boolean function in which the computation is carried out distributively across several workers with particular focus on security against Byzantine workers. We note that any Boolean function can be modeled as a multivariate polynomial which can have high degree in general. Hence, the recently proposed Lagrange Coded Computing (LCC) can be used to simultaneously provide resiliency, security, and privacy. However, the security threshold (i.e., the maximum number of adversarial workers that can be tolerated) provided by LCC can be extremely low if the degree of the polynomial is high. Our goal is to design an efficient coding scheme which achieves the optimal security threshold. We propose two novel schemes called coded Algebraic normal form (ANF) and coded Disjunctive normal form (DNF). Instead of modeling the Boolean function as a general polynomial, the key idea of the proposed schemes is to model it as the concatenation of some linear functions and threshold functions. The proposed coded ANF and coded DNF outperform LCC by providing the security threshold which is independent of the polynomial's degree.
Noel, M. D., Waziri, O. V., Abdulhamid, M. S., Ojeniyi, A. J., Okoro, M. U..  2020.  Comparative Analysis of Classical and Post-quantum Digital Signature Algorithms used in Bitcoin Transactions. 2020 2nd International Conference on Computer and Information Sciences (ICCIS). :1–6.

The use of public key cryptosystems ranges from securely encrypting bitcoin transactions and creating digital signatures for non-repudiation. The cryptographic systems security of public key depends on the complexity in solving mathematical problems. Quantum computers pose a threat to the current day algorithms used. This research presents analysis of two Hash-based Signature Schemes (MSS and W-OTS) and provides a comparative analysis of them. The comparisons are based on their efficiency as regards to their key generation, signature generation and verification time. These algorithms are compared with two classical algorithms (RSA and ECDSA) used in bitcoin transaction security. The results as shown in table II indicates that RSA key generation takes 0.2012s, signature generation takes 0.0778s and signature verification is 0.0040s. ECDSA key generation is 0.1378s, signature generation takes 0.0187s, and verification time for the signature is 0.0164s. The W-OTS key generation is 0.002s. To generate a signature in W-OTS, it takes 0.001s and verification time for the signature is 0.0002s. Lastly MSS Key generation, signature generation and verification has high values which are 16.290s, 17.474s, and 13.494s respectively. Based on the results, W-OTS is recommended for bitcoin transaction security because of its efficiency and ability to resist quantum computer attacks on the bitcoin network.

Wang, Wei, Liu, Tieyuan, Chang, Liang, Gu, Tianlong, Zhao, Xuemei.  2020.  Convolutional Recurrent Neural Networks for Knowledge Tracing. 2020 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC). :287–290.
Knowledge Tracing (KT) is a task that aims to assess students' mastery level of knowledge and predict their performance over questions, which has attracted widespread attention over the years. Recently, an increasing number of researches have applied deep learning techniques to knowledge tracing and have made a huge success over traditional Bayesian Knowledge Tracing methods. Most existing deep learning-based methods utilized either Recurrent Neural Networks (RNNs) or Convolutional Neural Networks (CNNs). However, it is worth noticing that these two sorts of models are complementary in modeling abilities. Thus, in this paper, we propose a novel knowledge tracing model by taking advantage of both two models via combining them into a single integrated model, named Convolutional Recurrent Knowledge Tracing (CRKT). Extensive experiments show that our model outperforms the state-of-the-art models in multiple KT datasets.
Aydeger, A., Saputro, N., Akkaya, K..  2020.  Cloud-based Deception against Network Reconnaissance Attacks using SDN and NFV. 2020 IEEE 45th Conference on Local Computer Networks (LCN). :279—285.

An attacker's success crucially depends on the reconnaissance phase of Distributed Denial of Service (DDoS) attacks, which is the first step to gather intelligence. Although several solutions have been proposed against network reconnaissance attacks, they fail to address the needs of legitimate users' requests. Thus, we propose a cloud-based deception framework which aims to confuse the attacker with reconnaissance replies while allowing legitimate uses. The deception is based on for-warding the reconnaissance packets to a cloud infrastructure through tunneling and SDN so that the returned IP addresses to the attacker will not be genuine. For handling legitimate requests, we create a reflected virtual topology in the cloud to match any changes in the original physical network to the cloud topology using SDN. Through experimentations on GENI platform, we show that our framework can provide reconnaissance responses with negligible delays to the network clients while also reducing the management costs significantly.

Sidhu, H. J. Singh, Khanna, M. S..  2020.  Cloud's Transformative Involvement in Managing BIG-DATA ANALYTICS For Securing Data in Transit, Storage And Use: A Study. 2020 Sixth International Conference on Parallel, Distributed and Grid Computing (PDGC). :297—302.

with the advent of Cloud Computing a new era of computing has come into existence. No doubt, there are numerous advantages associated with the Cloud Computing but, there is other side of the picture too. The challenges associated with it need a more promising reply as far as the security of data that is stored, in process and in transit is concerned. This paper put forth a cloud computing model that tries to answer the data security queries; we are talking about, in terms of the four cryptographic techniques namely Homomorphic Encryption (HE), Verifiable Computation (VC), Secure Multi-Party Computation (SMPC), Functional Encryption (FE). This paper takes into account the various cryptographic techniques to undertake cloud computing security issues. It also surveys these important (existing) cryptographic tools/techniques through a proposed Cloud computation model that can be used for Big Data applications. Further, these cryptographic tools are also taken into account in terms of CIA triad. Then, these tools/techniques are analyzed by comparing them on the basis of certain parameters of concern.

Le, T. V., Huan, T. T..  2020.  Computational Intelligence Towards Trusted Cloudlet Based Fog Computing. 2020 5th International Conference on Green Technology and Sustainable Development (GTSD). :141—147.

The current trend of IoT user is toward the use of services and data externally due to voluminous processing, which demands resourceful machines. Instead of relying on the cloud of poor connectivity or a limited bandwidth, the IoT user prefers to use a cloudlet-based fog computing. However, the choice of cloudlet is solely dependent on its trust and reliability. In practice, even though a cloudlet possesses a required trusted platform module (TPM), we argue that the presence of a TPM is not enough to make the cloudlet trustworthy as the TPM supports only the primitive security of the bootstrap. Besides uncertainty in security, other uncertain conditions of the network (e.g. network bandwidth, latency and expectation time to complete a service request for cloud-based services) may also prevail for the cloudlets. Therefore, in order to evaluate the trust value of multiple cloudlets under uncertainty, this paper broadly proposes the empirical process for evaluation of trust. This will be followed by a measure of trust-based reputation of cloudlets through computational intelligence such as fuzzy logic and ant colony optimization (ACO). In the process, fuzzy logic-based inference and membership evaluation of trust are presented. In addition, ACO and its pheromone communication across different colonies are being modeled with multiple cloudlets. Finally, a measure of affinity or popular trust and reputation of the cloudlets is also proposed. Together with the context of application under multiple cloudlets, the computationally intelligent approaches have been investigated in terms of performance. Hence the contribution is subjected towards building a trusted cloudlet-based fog platform.

Garcia-Luna-Aceves, J.J., Ali Albalawi, Abdulazaz.  2020.  Connection-Free Reliable and Efficient Transport Services in the IP Internet. 2020 16th International Conference on Network and Service Management (CNSM). :1—7.
The Internet Transport Protocol (ITP) is introduced to support reliable end-to-end transport services in the IP Internet without the need for end-to-end connections, changes to the Internet routing infrastructure, or modifications to name-resolution services. Results from simulation experiments show that ITP outperforms the Transmission Control Protocol (TCP) and the Named Data Networking (NDN) architecture, which requires replacing the Internet Protocol (IP). In addition, ITP allows transparent content caching while enforcing privacy.
Segovia, Mariana, Rubio-Hernan, Jose, Cavalli, Ana R., Garcia-Alfaro, Joaquin.  2020.  Cyber-Resilience Evaluation of Cyber-Physical Systems. 2020 IEEE 19th International Symposium on Network Computing and Applications (NCA). :1—8.
Cyber-Physical Systems (CPS) use computational resources to control physical processes and provide critical services. For this reason, an attack in these systems may have dangerous consequences in the physical world. Hence, cyber- resilience is a fundamental property to ensure the safety of the people, the environment and the controlled physical processes. In this paper, we present metrics to quantify the cyber-resilience level based on the design, structure, stability, and performance under the attack of a given CPS. The metrics provide reference points to evaluate whether the system is better prepared or not to face the adversaries. This way, it is possible to quantify the ability to recover from an adversary using its mathematical model based on actuators saturation. Finally, we validate our approach using a numeric simulation on the Tennessee Eastman control challenge problem.
Ming, Kun.  2020.  Chinese Coreference Resolution via Bidirectional LSTMs using Word and Token Level Representations. 2020 16th International Conference on Computational Intelligence and Security (CIS). :73–76.
Coreference resolution is an important task in the field of natural language processing. Most existing methods usually utilize word-level representations, ignoring massive information from the texts. To address this issue, we investigate how to improve Chinese coreference resolution by using span-level semantic representations. Specifically, we propose a model which acquires word and character representations through pre-trained Skip-Gram embeddings and pre-trained BERT, then explicitly leverages span-level information by performing bidirectional LSTMs among above representations. Experiments on CoNLL-2012 shared task have demonstrated that the proposed model achieves 62.95% F1-score, outperforming our baseline methods.