Visible to the public Biblio

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2021-07-08
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.
2021-06-30
Maalla, Allam.  2020.  Research on Data Transmission Security Architecture Design and Process. 2020 IEEE International Conference on Information Technology,Big Data and Artificial Intelligence (ICIBA). 1:1195—1199.
With the development of business, management companies are currently facing a series of problems and challenges in terms of resource allocation and task management. In terms of the technical route, this research will use cloud services to implement the public honesty system, and carry out secondary development and interface development on this basis, the architecture design and the formulation of the process are realized for various types, relying on the support of the knowledge base and case library, through the system intelligent configuration corresponding work instructions, safety work instructions, case references and other reference information to the existing work plan to provide managers Reference; managers can configure and adjust the work content by themselves through specific requirements to efficiently and flexibly adapt to the work content.
2021-06-24
Liu, Zhibin, Liu, Ziang, Huang, Yuanyuan, Liu, Xin, Zhou, Xiaokang, Zhou, Rui.  2020.  A Research of Distributed Security and QoS Testing Framework. 2020 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech). :174—181.
Since the birth of the Internet, the quality of network service has been a widespread concerned problem. With the continuous development of communication and information technology, people gradually realized that the contradiction between the limited resources and the business requirements of network cannot be fundamentally solved. In this paper, we design and develop a distributed security quality of service testing framework called AweQoS(AwesomeQoS), to adapt to the current complex network environment. This paper puts forward the necessity that some security tests should be closely combined with quality of service testing, and further discusses the basic methods of distributed denial of service attack and defense. We introduce the design idea and working process of AweQoS in detail, and introduce a bandwidth test method based on user datagram protocol. Experimental results show that this new test method has better test performance and potential under the AweQoS framework.
2021-05-05
Singh, Sukhpreet, Jagdev, Gagandeep.  2020.  Execution of Big Data Analytics in Automotive Industry using Hortonworks Sandbox. 2020 Indo – Taiwan 2nd International Conference on Computing, Analytics and Networks (Indo-Taiwan ICAN). :158—163.

The market landscape has undergone dramatic change because of globalization, shifting marketing conditions, cost pressure, increased competition, and volatility. Transforming the operation of businesses has been possible because of the astonishing speed at which technology has witnessed the change. The automotive industry is on the edge of a revolution. The increased customer expectations, changing ownership, self-driving vehicles and much more have led to the transformation of automobiles, applications, and services from artificial intelligence, sensors, RFID to big data analysis. Large automobiles industries have been emphasizing the collection of data to gain insight into customer's expectations, preferences, and budgets alongside competitor's policies. Statistical methods can be applied to historical data, which has been gathered from various authentic sources and can be used to identify the impact of fixed and variable marketing investments and support automakers to come up with a more effective, precise, and efficient approach to target customers. Proper analysis of supply chain data can disclose the weak links in the chain enabling to adopt timely countermeasures to minimize the adverse effects. In order to fully gain benefit from analytics, the collaboration of a detailed set of capabilities responsible for intersecting and integrating with multiple functions and teams across the business is required. The effective role played by big data analysis in the automobile industry has also been expanded in the research paper. The research paper discusses the scope and challenges of big data. The paper also elaborates on the working technology behind the concept of big data. The paper illustrates the working of MapReduce technology that executes in the back end and is responsible for performing data mining.

Zhao, Bushi, Zhang, Hao, Luo, Yixi.  2020.  Automatic Error Correction Technology for the Same Field in the Same Kind of Power Equipment Account Data. 2020 IEEE 3rd International Conference of Safe Production and Informatization (IICSPI). :153—157.
Account data of electrical power system is the link of all businesses in the whole life cycle of equipment. It is of great significance to improve the data quality of power equipment account data for improving the information level of power enterprises. In the past, there was only the error correction technology to check whether it was empty and whether it contained garbled code. The error correction technology for same field of the same kind of power equipment account data is proposed in this paper. Combined with the characteristics of production business, the possible similar power equipment can be found through the function location type and other fields of power equipment account data. Based on the principle of search scoring, the horizontal comparison is used to search and score in turn. Finally, the potential spare parts and existing data quality are identified according to the scores. And judge whether it is necessary to carry out inspection maintenance.
2021-04-27
Zhou, X..  2020.  Improvement of information System Audit to Deal With Network Information Security. 2020 International Conference on Communications, Information System and Computer Engineering (CISCE). :93–96.
With the rapid development of information technology and the increasing popularity of information and communication technology, the information age has come. Enterprises must adapt to changes in the times, introduce network and computer technologies in a timely manner, and establish more efficient and reasonable information systems and platforms. Large-scale information system construction is inseparable from related audit work, and network security risks have become an important part of information system audit concerns. This paper analyzes the objectives and contents of information system audits under the background of network information security through theoretical analysis, and on this basis, proposes how the IS audit work will be carried out.
2021-03-30
Ashiku, L., Dagli, C..  2020.  Agent Based Cybersecurity Model for Business Entity Risk Assessment. 2020 IEEE International Symposium on Systems Engineering (ISSE). :1—6.

Computer networks and surging advancements of innovative information technology construct a critical infrastructure for network transactions of business entities. Information exchange and data access though such infrastructure is scrutinized by adversaries for vulnerabilities that lead to cyber-attacks. This paper presents an agent-based system modelling to conceptualize and extract explicit and latent structure of the complex enterprise systems as well as human interactions within the system to determine common vulnerabilities of the entity. The model captures emergent behavior resulting from interactions of multiple network agents including the number of workstations, regular, administrator and third-party users, external and internal attacks, defense mechanisms for the network setting, and many other parameters. A risk-based approach to modelling cybersecurity of a business entity is utilized to derive the rate of attacks. A neural network model will generalize the type of attack based on network traffic features allowing dynamic state changes. Rules of engagement to generate self-organizing behavior will be leveraged to appoint a defense mechanism suitable for the attack-state of the model. The effectiveness of the model will be depicted by time-state chart that shows the number of affected assets for the different types of attacks triggered by the entity risk and the time it takes to revert into normal state. The model will also associate a relevant cost per incident occurrence that derives the need for enhancement of security solutions.

2021-03-29
Aigner, A., Khelil, A..  2020.  An Effective Semantic Security Metric for Industrial Cyber-Physical Systems. 2020 IEEE Conference on Industrial Cyberphysical Systems (ICPS). 1:87—92.

The emergence of Industrial Cyber-Physical Systems (ICPS) in today's business world is still steadily progressing to new dimensions. Although they bring many new advantages to business processes and enable automation and a wider range of service capability, they also propose a variety of new challenges. One major challenge, which is introduced by such System-of-Systems (SoS), lies in the security aspect. As security may not have had that significant role in traditional embedded system engineering, a generic way to measure the level of security within an ICPS would provide a significant benefit for system engineers and involved stakeholders. Even though many security metrics and frameworks exist, most of them insufficiently consider an SoS context and the challenges of such environments. Therefore, we aim to define a security metric for ICPS, which measures the level of security during the system design, tests, and integration as well as at runtime. For this, we try to focus on a semantic point of view, which on one hand has not been considered in security metric definitions yet, and on the other hand allows us to handle the complexity of SoS architectures. Furthermore, our approach allows combining the critical characteristics of an ICPS, like uncertainty, required reliability, multi-criticality and safety aspects.

2021-03-22
Xu, P., Chen, L., Jiang, Y., Sun, Q., Chen, H..  2020.  Research on Sensitivity Audit Scheme of Encrypted Data in Power Business. 2020 IEEE International Conference on Energy Internet (ICEI). :6–10.

With the rapid progress of informatization construction in power business, data resource has become the basic strategic resource of the power industry and innovative element in power production. The security protection of data in power business is particularly important in the informatization construction of power business. In order to implement data security protection, transparent encryption is one of the fifteen key technical standards in the Construction Guideline of the Standard Network Data Security System. However, data storage in the encrypted state is bound to affect the security audit of data to a certain extent. Based on this problem, this paper proposes a scheme to audit the sensitivity of the power business data under the protection of encryption to achieve an efficient sensitivity audit of ciphertext data with the premise of not revealing the decryption key or data information. Through a security demonstration, this paper fully proves that this solution is secure under the known plaintext attacks.

2020-11-30
Chai, W. K., Pavlou, G., Kamel, G., Katsaros, K. V., Wang, N..  2019.  A Distributed Interdomain Control System for Information-Centric Content Delivery. IEEE Systems Journal. 13:1568–1579.
The Internet, the de facto platform for large-scale content distribution, suffers from two issues that limit its manageability, efficiency, and evolution. First, the IP-based Internet is host-centric and agnostic to the content being delivered and, second, the tight coupling of the control and data planes restrict its manageability, and subsequently the possibility to create dynamic alternative paths for efficient content delivery. Here, we present the CURLING system that leverages the emerging Information-Centric Networking paradigm for enabling cost-efficient Internet-scale content delivery by exploiting multicasting and in-network caching. Following the software-defined networking concept that decouples the control and data planes, CURLING adopts an interdomain hop-by-hop content resolution mechanism that allows network operators to dynamically enforce/change their network policies in locating content sources and optimizing content delivery paths. Content publishers and consumers may also control content access according to their preferences. Based on both analytical modeling and simulations using real domain-level Internet subtopologies, we demonstrate how CURLING supports efficient Internet-scale content delivery without the necessity for radical changes to the current Internet.
2020-11-23
Zhu, L., Dong, H., Shen, M., Gai, K..  2019.  An Incentive Mechanism Using Shapley Value for Blockchain-Based Medical Data Sharing. 2019 IEEE 5th Intl Conference on Big Data Security on Cloud (BigDataSecurity), IEEE Intl Conference on High Performance and Smart Computing, (HPSC) and IEEE Intl Conference on Intelligent Data and Security (IDS). :113–118.
With the development of big data and machine learning techniques, medical data sharing for the use of disease diagnosis has received considerable attention. Blockchain, as an emerging technology, has been widely used to resolve the efficiency and security issues in medical data sharing. However, the existing studies on blockchain-based medical data sharing have rarely concerned about the reasonable incentive mechanism. In this paper, we propose a cooperation model where medical data is shared via blockchain. We derive the topological relationships among the participants consisting of data owners, miners and third parties, and gradually develop the computational process of Shapley value revenue distribution. Specifically, we explore the revenue distribution under different consensuses of blockchain. Finally, we demonstrate the incentive effect and rationality of the proposed solution by analyzing the revenue distribution.
2020-11-09
Zaman, M., Sengupta, A., Liu, D., Sinanoglu, O., Makris, Y., Rajendran, J. J. V..  2018.  Towards provably-secure performance locking. 2018 Design, Automation Test in Europe Conference Exhibition (DATE). :1592–1597.
Locking the functionality of an integrated circuit (IC) thwarts attacks such as intellectual property (IP) piracy, hardware Trojans, overbuilding, and counterfeiting. Although functional locking has been extensively investigated, locking the performance of an IC has been little explored. In this paper, we develop provably-secure performance locking, where only on applying the correct key the IC shows superior performance; for an incorrect key, the performance of the IC degrades significantly. This leads to a new business model, where the companies can design a single IC capable of different performances for different users. We develop mathematical definitions of security and theoretically, and experimentally prove the security against the state-of-the-art-attacks. We implemented performance locking on a FabScalar microprocessor, achieving a degradation in instructions per clock cycle (IPC) of up to 77% on applying an incorrect key, with an overhead of 0.6%, 0.2%, and 0% for area, power, and delay, respectively.
2020-11-04
Dai, J..  2018.  Situation Awareness-Oriented Cybersecurity Education. 2018 IEEE Frontiers in Education Conference (FIE). :1—8.

This Research to Practice Full Paper presents a new methodology in cybersecurity education. In the context of the cybersecurity profession, the `isolation problem' refers to the observed isolation of different knowledge units, as well as the isolation of technical and business perspectives. Due to limitations in existing cybersecurity education, professionals entering the field are often trapped in microscopic perspectives, and struggle to extend their findings to grasp the big picture in a target network scenario. Guided by a previous developed and published framework named “cross-layer situation knowledge reference model” (SKRM), which delivers comprehensive level big picture situation awareness, our new methodology targets at developing suites of teaching modules to address the above issues. The modules, featuring interactive hands-on labs that emulate real-world multiple-step attacks, will help students form a knowledge network instead of isolated conceptual knowledge units. Students will not just be required to leverage various techniques/tools to analyze breakpoints and complete individual modules; they will be required to connect logically the outputs of these techniques/tools to infer the ground truth and gain big picture awareness of the cyber situation. The modules will be able to be used separately or as a whole in a typical network security course.

2020-11-02
Aman, W., Khan, F..  2019.  Ontology-based Dynamic and Context-aware Security Assessment Automation for Critical Applications. 2019 IEEE 8th Global Conference on Consumer Electronics (GCCE). :644–647.

Several assessment techniques and methodologies exist to analyze the security of an application dynamically. However, they either are focused on a particular product or are mainly concerned about the assessment process rather than the product's security confidence. Most crucially, they tend to assess the security of a target application as a standalone artifact without assessing its host infrastructure. Such attempts can undervalue the overall security posture since the infrastructure becomes crucial when it hosts a critical application. We present an ontology-based security model that aims to provide the necessary knowledge, including network settings, application configurations, testing techniques and tools, and security metrics to evaluate the security aptitude of a critical application in the context of its hosting infrastructure. The objective is to integrate the current good practices and standards in security testing and virtualization to furnish an on-demand and test-ready virtual target infrastructure to execute the critical application and to initiate a context-aware and quantifiable security assessment process in an automated manner. Furthermore, we present a security assessment architecture to reflect on how the ontology can be integrated into a standard process.

2020-10-26
Eryonucu, Cihan, Ayday, Erman, Zeydan, Engin.  2018.  A Demonstration of Privacy-Preserving Aggregate Queries for Optimal Location Selection. 2018 IEEE 19th International Symposium on "A World of Wireless, Mobile and Multimedia Networks" (WoWMoM). :1–3.
In recent years, service providers, such as mobile operators providing wireless services, collected location data in enormous extent with the increase of the usages of mobile phones. Vertical businesses, such as banks, may want to use this location information for their own scenarios. However, service providers cannot directly provide these private data to the vertical businesses because of the privacy and legal issues. In this demo, we show how privacy preserving solutions can be utilized using such location-based queries without revealing each organization's sensitive data. In our demonstration, we used partially homomorphic cryptosystem in our protocols and showed practicality and feasibility of our proposed solution.
Yaswinski, Matthew R., Chowdhury, Md Minhaz, Jochen, Mike.  2019.  Linux Security: A Survey. 2019 IEEE International Conference on Electro Information Technology (EIT). :357–362.
Linux is used in a large variety of situations, from private homes on personal machines to businesses storing personal data on servers. This operating system is often seen as more secure than Windows or Mac OS X, but this does not mean that there are no security concerns to be had when running it. Attackers can crack simple passwords over a network, vulnerabilities can be exploited if firewalls do not close enough ports, and malware can be downloaded and run on a Linux system. In addition, sensitive information can be accessed through physical or network access if proper permissions are not set on the files or directories containing it. However, most of these attacks can be prevented by keeping a system up to date, maintaining a secure firewall, using an antivirus, making complex passwords, and setting strong file permissions. This paper presents a list of methods for securing a Linux system from both external and internal threats.
2020-10-19
Aladwan, Mohammad, Awaysheh, Feras, Cabaleiro, José, Pena, Tomás, Alabool, Hamzeh, Alazab, Mamoun.  2019.  Common Security Criteria for Vehicular Clouds and Internet of Vehicles Evaluation and Selection. 2019 18th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/13th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE). :814–820.
Internet of Things (IoT) is becoming increasingly important to intelligent transportation system stakeholders, including cloud-based vehicular cloud (VC) and internet of vehicles (IoV) paradigms. This new trend involves communication and data exchange between several objects within different layers of control. Security in such a deployment is pivotal to realize the general IoT-based smart city. However, the evaluation of the degree of security regarding these paradigms remains a challenge. This study aims to discover and identify common security criteria (CSC) from a context-based analysis pattern and later to discuss, compare, and aggregate a conceptual model of CSC impartially. A privacy granularity classification that maintains data confidentiality is proposed alongside the security selection criteria.
2020-08-24
Sassani Sarrafpour, Bahman A., Del Pilar Soria Choque, Rosario, Mitchell Paul, Blake, Mehdipour, Farhad.  2019.  Commercial Security Scanning: Point-on-Sale (POS) Vulnerability and Mitigation Techniques. 2019 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech). :493–498.
Point of Sale (POS) systems has become the technology of choice for most businesses and offering number of advantages over traditional cash registers. They manage staffs, customers, transaction, inventory, sale and labor reporting, price adjustment, as well as keeping track of cash flow, expense management, reducing human errors and more. Whether traditional on-premise POS, or Cloud-Bases POS, they help businesses to run more efficiently. However, despite all these advantages, POS systems are becoming targets of a number of cyber-attacks. Security of a POS system is a key requirement of the Payment Card Industry Data Security Standard (PCI DSS). This paper undertakes research into the PCI DSS and its accompanying standards, in an attempt to break or bypass security measures using varying degrees of vulnerability and penetration attacks in a methodological format. The resounding goal of this experimentation is to achieve a basis from which attacks can be made against a realistic networking environment from whence an intruder can bypass security measures thus exposing a vulnerability in the PCI DSS and potentially exposing confidential customer payment information.
2020-08-03
Juuti, Mika, Szyller, Sebastian, Marchal, Samuel, Asokan, N..  2019.  PRADA: Protecting Against DNN Model Stealing Attacks. 2019 IEEE European Symposium on Security and Privacy (EuroS P). :512–527.
Machine learning (ML) applications are increasingly prevalent. Protecting the confidentiality of ML models becomes paramount for two reasons: (a) a model can be a business advantage to its owner, and (b) an adversary may use a stolen model to find transferable adversarial examples that can evade classification by the original model. Access to the model can be restricted to be only via well-defined prediction APIs. Nevertheless, prediction APIs still provide enough information to allow an adversary to mount model extraction attacks by sending repeated queries via the prediction API. In this paper, we describe new model extraction attacks using novel approaches for generating synthetic queries, and optimizing training hyperparameters. Our attacks outperform state-of-the-art model extraction in terms of transferability of both targeted and non-targeted adversarial examples (up to +29-44 percentage points, pp), and prediction accuracy (up to +46 pp) on two datasets. We provide take-aways on how to perform effective model extraction attacks. We then propose PRADA, the first step towards generic and effective detection of DNN model extraction attacks. It analyzes the distribution of consecutive API queries and raises an alarm when this distribution deviates from benign behavior. We show that PRADA can detect all prior model extraction attacks with no false positives.
2020-07-27
Dangiwa, Bello Ahmed, Kumar, Smitha S.  2018.  A Business Card Reader Application for iOS devices based on Tesseract. 2018 International Conference on Signal Processing and Information Security (ICSPIS). :1–4.
As the accessibility of high-resolution smartphone camera has increased and an improved computational speed, it is now convenient to build Business Card Readers on mobile phones. The project aims to design and develop a Business Card Reader (BCR) Application for iOS devices, using an open-source OCR Engine - Tesseract. The system accuracy was tested and evaluated using a dataset of 55 digital business cards obtained from an online repository. The accuracy result of the system was up to 74% in terms of both text recognition and data detection. A comparative analysis was carried out against a commercial business card reader application and our application performed vastly reasonable.
2020-07-09
Fahrenkrog-Petersen, Stephan A., van der Aa, Han, Weidlich, Matthias.  2019.  PRETSA: Event Log Sanitization for Privacy-aware Process Discovery. 2019 International Conference on Process Mining (ICPM). :1—8.

Event logs that originate from information systems enable comprehensive analysis of business processes, e.g., by process model discovery. However, logs potentially contain sensitive information about individual employees involved in process execution that are only partially hidden by an obfuscation of the event data. In this paper, we therefore address the risk of privacy-disclosure attacks on event logs with pseudonymized employee information. To this end, we introduce PRETSA, a novel algorithm for event log sanitization that provides privacy guarantees in terms of k-anonymity and t-closeness. It thereby avoids disclosure of employee identities, their membership in the event log, and their characterization based on sensitive attributes, such as performance information. Through step-wise transformations of a prefix-tree representation of an event log, we maintain its high utility for discovery of a performance-annotated process model. Experiments with real-world data demonstrate that sanitization with PRETSA yields event logs of higher utility compared to methods that exploit frequency-based filtering, while providing the same privacy guarantees.

2020-07-06
Mason, Andrew, Zhao, Yifan, He, Hongmei, Gompelman, Raymon, Mandava, Srikanth.  2019.  Online Anomaly Detection of Time Series at Scale. 2019 International Conference on Cyber Situational Awareness, Data Analytics And Assessment (Cyber SA). :1–8.
Cyber breaches can result in disruption to business operations, reputation damage as well as directly affecting the financial stability of the targeted corporations, with potential impacts on future profits and stock values. Automatic network-stream monitoring becomes necessary for cyber situation awareness, and time-series anomaly detection plays an important role in network stream monitoring. This study surveyed recent research on time-series analysis methods in respect of parametric and non-parametric techniques, and popular machine learning platforms for data analysis on streaming data on both single server and cloud computing environments. We believe it provides a good reference for researchers in both academia and industry to select suitable (time series) data analysis techniques, and computing platforms, dependent on the data scale and real-time requirements.
2020-06-08
Sun, Wenhua, Wang, Xiaojuan, Jin, Lei.  2019.  An Efficient Hash-Tree-Based Algorithm in Mining Sequential Patterns with Topology Constraint. 2019 IEEE 21st International Conference on High Performance Computing and Communications; IEEE 17th International Conference on Smart City; IEEE 5th International Conference on Data Science and Systems (HPCC/SmartCity/DSS). :2782–2789.
Warnings happen a lot in real transmission networks. These warnings can affect people's lives. It is significant to analyze the alarm association rules in the network. Many algorithms can help solve this problem but not considering the actual physical significance. Therefore, in this study, we mine the association rules in warning weblogs based on a sequential mining algorithm (GSP) with topology structure. We define a topology constraint from network physical connection data. Under the topology constraint, network nodes have topology relation if they are directly connected or have a common adjacency node. In addition, due to the large amount of data, we implement the hash-tree search method to improve the mining efficiency. The theoretical solution is feasible and the simulation results verify our method. In simulation, the topology constraint improves the accuracy for 86%-96% and decreases the run time greatly at the same time. The hash-tree based mining results show that hash tree efficiency improvements are in 3-30% while the number of patterns remains unchanged. In conclusion, using our method can mine association rules efficiently and accurately in warning weblogs.
2020-06-01
Dhal, Subhasish, Bhuwan, Vaibhav.  2018.  Cryptanalysis and improvement of a cloud based login and authentication protocol. 2018 4th International Conference on Recent Advances in Information Technology (RAIT). :1–6.
Outsourcing services to cloud server (CS) becomes popular in these years. However, the outsourced services often involve with sensitive activity and CS naturally becomes a target of varieties of attacks. Even worse, CS itself can misuse the outsourced services for illegal profit. Traditional online banking system also can make use of a cloud framework to provide economical and high-speed online services to the consumers, which makes the financial dealing easy and convenient. Most of the banking organizations provide services through passbook, ATM, mobile banking, electronic banking (e-banking) etc. Among these, the e-banking and mobile banking are more convenient and becomes essential. Therefore, it is critical to provide an efficient, reliable and more importantly, secure e-banking services to the consumers. The cloud environment is suitable paradigm to a new, small and medium scale banking organization as it eliminates the requirement for them to start with small resources and increase gradually as the service demand rises. However, security is one of the main concerns since it deals with many sensitive data of the valuable customers. In addition to this, the access of various data needs to be restricted to prevent any unauthorized transaction. Nagaraju et al. presented a framework to achieve reliability and security in public cloud based online banking using multi-factor authentication concept. Unfortunately, the login and authentication protocol of this framework is prone to impersonation attack. In this paper, we have revised the framework to avoid this attack.
2020-05-08
Kearney, Paul, Asal, Rasool.  2019.  ERAMIS: A Reference Architecture-Based Methodology for IoT Systems. 2019 IEEE World Congress on Services (SERVICES). 2642-939X:366—367.

Opportunities arising from IoT-enabled applications are significant, but market growth is inhibited by concerns over security and complexity. To address these issues, we propose the ERAMIS methodology, which is based on instantiation of a reference architecture that captures common design features, embodies best practice, incorporates good security properties by design, and makes explicit provision for operational security services and processes.