{"title":"A systematic review and taxonomy of web applications threats","authors":"Yassine Sadqi, Yassine Maleh","doi":"10.1080/19393555.2020.1853855","DOIUrl":"https://doi.org/10.1080/19393555.2020.1853855","url":null,"abstract":"ABSTRACT Nowadays, web application security is one of the relevant issues in the IT security domain due to the continued growth in the number of web-related attacks. As a result, attacks, with various and varied motivations, have developed and become increasingly sophisticated. They mainly target data related to economic activities. Thus, they cause significant damage to the overall functioning of information systems. To address the various threats, several robust taxonomies exist in the literature. Each taxonomy and classification has advantages and limitations. We first define the different threat classifications related to the context of Web applications. The objective of this analysis is to provide a synthesis of the advantages and disadvantages of each classification. The current work analyses different taxonomies for web applications threats, in order to propose our proper taxonomy. The proposed taxonomy takes advantage of the benefits of existing taxonomies and provides an integrated approach for classifying both client-side and server-side attacks. The finding will help researchers to find a clear and detailed taxonomy of the different threats related to web applications.","PeriodicalId":103842,"journal":{"name":"Information Security Journal: A Global Perspective","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132680205","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Md. Rashedul Islam, T. R. Tanni, S. Parvin, M. J. Sultana, Ayasha Siddiqa
{"title":"A modified LSB image steganography method using filtering algorithm and stream of password","authors":"Md. Rashedul Islam, T. R. Tanni, S. Parvin, M. J. Sultana, Ayasha Siddiqa","doi":"10.1080/19393555.2020.1854902","DOIUrl":"https://doi.org/10.1080/19393555.2020.1854902","url":null,"abstract":"ABSTRACT Data is one of the most significant assets nowadays and needs to address correctly in the growing risk of cybersecurity. Additionally, every year, data is stolen and modified from the internet when transmitting. Therefore, to improve security while transmission, there are two techniques available called cryptography and steganography. In cryptography, the information is encrypted to ciphertexts using a private key, but the message’s existence is visible to others, no matter how unbreakable they are. On the other hand, steganography hides the secret data in an ordinary non-secret file to avoid visual detection. This paper proposed a new data hiding method using LSB image steganography, where confidential information uses only the selected image pixel. For that, image pixel information is used to filter the complete image to decide the candidate pixel, and a user-defined password is used to secure the LSB steganography. For better security, before applying steganography, the AES method encrypts the secret message. In the experiment, MSE and PSNR value are measured to assess the quality of the resultant stego image. The stego image provides higher PSNR and less MSE value as compared to other studied methods, which illustrate the flexibility of the proposed method.","PeriodicalId":103842,"journal":{"name":"Information Security Journal: A Global Perspective","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122377283","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A four-part typology to assess organizational and individual security awareness","authors":"Mathias Reveraert, Tom Sauer","doi":"10.1080/19393555.2020.1855374","DOIUrl":"https://doi.org/10.1080/19393555.2020.1855374","url":null,"abstract":"ABSTRACT This article provides a four-part typology of security awareness. We argue that existing awareness typologies that distinguish problem awareness from solution awareness and that separate descriptive awareness from prescriptive awareness are on its own insufficient and need to be merged to have a complete picture of security awareness. Renaming and bridging both distinctions leads to four security awareness types: (1) Cognitive awareness of the threat; (2) Attitudinal awareness of the threat; (3) Cognitive awareness of the mitigation; and (4) Attitudinal awareness of the mitigation. Each type is subsequently explained in greater detail and illustrated by referring to the 2020 worldwide outbreak of COVID-19. Furthermore, it is demonstrated that the typology is applicable to study both organizational awareness and individual awareness.","PeriodicalId":103842,"journal":{"name":"Information Security Journal: A Global Perspective","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123885500","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Facial blemishes detection and encryption with secure force algorithm into HCC2D code for biometric-passport","authors":"Z. Choudhury, M. Rabbani","doi":"10.1080/19393555.2020.1846823","DOIUrl":"https://doi.org/10.1080/19393555.2020.1846823","url":null,"abstract":"ABSTRACT A biometric passport includes demographic information and biometric details. It contains some applications that are currently and probable concerning national security such as frontier protection, illegal immigration, criminals, terrorists, and fake passport. Over the fifteen years, most of the countries have adopted biometric-passports based on International Civil Aviation Organization (ICAO) and Machine Readable Travel Documents (MRTD) standardization. However, the Radio Frequency Identification (RFID) system contains a threat scenario that exists in privacy violation issues such as identity theft, data leakage threats, host listing, and tracking. To overcome these issues, this paper proposed a face recognition based on facial blemishes detection and encrypted into the High Capacity Color 2-Dimensional (HCC2D) code for biometric passport security. This includes facial blemishes features detection to generate the template and encrypted by applying the Secure Force (SF) algorithm to secure biometric information. Facial blemishes are detected by applying the Active Appearance Model (AAM) using Principle Component Analysis (PCA) and Canny edge detector with Speeded Up Robust Features (SURF) detection algorithm. The proposed technique attained a 93.06% accuracy level for the dataset Indian Institute of Technology Kanpur (IITK). This technique will enhance biometric passport security to protect the biometric information from an intruder.","PeriodicalId":103842,"journal":{"name":"Information Security Journal: A Global Perspective","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134598958","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A security-attribute-based access control along with user revocation for shared data in multi-owner cloud system","authors":"S. Raj, B. Kumar, G. Venkatesan","doi":"10.1080/19393555.2020.1842568","DOIUrl":"https://doi.org/10.1080/19393555.2020.1842568","url":null,"abstract":"ABSTRACT Cloud storage is a cloud implementation that facilitates agencies to set up in-house information storage installations. Cloud storage actually creates security problems. When the information is communicated by groups; both cloud-specific and standard insider threats are visible. A key research problem is the secure sharing among group members, which confronts the internal threats of legitimate and malevolent users. In this paper, in this paper, an effective structured data sharing mechanism for user revocation in the multi-owner cloud system is proposed. The proposed method is based on the following five entities: data owner, cloud storage, central authority, and cryptographic server, and data users. The data owner will submit to cryptographic servers’ data, user list and parameters capable of generating an Access Control List (ACL). A trusted third party is a cryptographic server that provides the symmetric key that triggers the encrypted data. The cryptographic server then divides the key into three sections for each user within the group. Quantitative findings indicate the sustainability of the mechanism proposed in contrast with conventional schemes.","PeriodicalId":103842,"journal":{"name":"Information Security Journal: A Global Perspective","volume":"53 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130765495","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"The Security Enhancement of Symmetric Key Crypto Mechanism based on Double Stage Secret Model","authors":"Sreeparna Chakrabarti, G. S. Babu","doi":"10.1080/19393555.2020.1842945","DOIUrl":"https://doi.org/10.1080/19393555.2020.1842945","url":null,"abstract":"ABSTRACT All smart services in cloud computing platforms have a data-sharing process to execute the task. Moreover, several crypto techniques were implemented to provide efficient and secure data transmission channel. However, it has been suffered with a number of issues because of several harmful attacks and unauthenticated key retrieval. Thus in the wireless medium, transferring the data amid two users are challengeable task. To overcome this issue, a novel Double-Stage Secret (DSS) cryptosystem is proposed to prevent the attacks in the communication channel, here the encryption and decryption function is processed based on some specific condition. If the DSS condition is satisfied then the client or user is requested to decrypt the message. To validate the secure and success rate of the proposed model, an efficient novel back sniff is developed and launched in the data transmission channel and its secure range is evaluated. In addition, the simulation of this research is done by Java, running on net beans IDE 8.2 in windows 10 platform and the results illustrated that the proposed model has attained high performance by gaining a high secure rate and less processing time of encryption and decryption than the existing algorithms.","PeriodicalId":103842,"journal":{"name":"Information Security Journal: A Global Perspective","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122868114","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
P. Mishra, Deevashwer Rathee, D. Duong, Masaya Yasuda
{"title":"Fast secure matrix multiplications over ring-based homomorphic encryption","authors":"P. Mishra, Deevashwer Rathee, D. Duong, Masaya Yasuda","doi":"10.1080/19393555.2020.1836288","DOIUrl":"https://doi.org/10.1080/19393555.2020.1836288","url":null,"abstract":"ABSTRACT As widespread development of biometrics, concerns about security and privacy are rapidly increasing. Secure matrix computation is one of the most fundamental and useful operations for statistical analysis and machine learning with protecting the confidentiality of input data. Secure computation can be achieved by homomorphic encryption, supporting meaningful operations over encrypted data. HElib is a software library that implements the Brakerski-Gentry-Vaikuntanathan (BGV) homomorphic scheme, in which secure matrix-vector multiplication is proposed for operating matrices. Recently, Duong et al. (Tatra Mt. Publ) proposed a new method for secure single matrix multiplication over a ring-LWE-based scheme. In this paper, we generalize Duong et al.’s method for secure multiple matrix multiplications over the BGV scheme. We also implement our method using HElib, and show that our method is much faster than the matrix-vector multiplication in HElib for secure matrix multiplications.","PeriodicalId":103842,"journal":{"name":"Information Security Journal: A Global Perspective","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134007599","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A dictionary-based method for detecting machine-generated domains","authors":"Tianyu Wang, Li-Chiou Chen, Y. Genc","doi":"10.1080/19393555.2020.1834650","DOIUrl":"https://doi.org/10.1080/19393555.2020.1834650","url":null,"abstract":"ABSTRACT Internet robots, also known as bots, have transformed the businesses and society with convenience. However, the dynamics of these interactions could be under adversarial circumstances with detrimental effects on network security. Bots that use domain-generation algorithms (DGAs) can generate many random domains dynamically so that static domain blacklists become ineffective in preventing malicious attacks by botnets. Various families of recent botnets have used DGA to establish communication with the bots. Researchers have introduced various detection methods with moderate success. Methods proposed so far either detect only DGAs that use non-variations forms or focus on the classification accuracy instead of time complexity, which would be critical in real-world production. The goal of this article is to explore how machine learning can help in detecting machine-generated domain names. To that end, we propose a dictionary-based n-gram method that can detect 39 DGA variations. We compared our method with existing research and found that our method can improve the performance of the existing classification algorithms. At last, our method can achieve competitive results as the LSTM model while requiring less time and complexity. Our research helps real-time production for DGA detection and provides insight in protecting DNS server and information security.","PeriodicalId":103842,"journal":{"name":"Information Security Journal: A Global Perspective","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127634116","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Feature indexing and search optimization for enhancing the forensic analysis of mobile cloud environment","authors":"Ibrahim Ali Alnajjar, M. Mahmuddin","doi":"10.1080/19393555.2020.1839605","DOIUrl":"https://doi.org/10.1080/19393555.2020.1839605","url":null,"abstract":"ABSTRACT The increased utilization of Mobile Cloud Computing (MCC) technology creates an opportunity for cybercrimes. Modeling the suitable methods for mobile cloud forensic examination and analysis is essential to improve the investigation performance. This paper incorporates data mining and optimization methods to enforce precise handling of the mobile cloud evidence in examination and analysis to improve the investigation performance. It enhances the analysis of the mobile cloud forensics with the incorporation of the evidence indexing, cross-referencing, and keyword searching as the sub-processes. The proposed Forensic Examination and analysis methodology using the Data mining and Optimization (FEDO) approach examines the key features of the evidence and indexes the pieces of evidence with key features to facilitate the investigation over the massive cloud evidence. By analyzing the temporal and geo-information, it applies cross-referencing to alleviate the evidence toward the case-specific evidence. The proposed methodology improves the searching capability of the investigation through the Linearly Decreasing Weight (LDW) strategy based Particle Swarm Optimization (PSO) algorithm. Thus, the experimental results demonstrate that the proposed forensic methodology yields better investigation performance in terms of accuracy of evidence detection.","PeriodicalId":103842,"journal":{"name":"Information Security Journal: A Global Perspective","volume":"12 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120808904","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Osamah M. Al-Matari, Iman M. A. Helal, Sherif A. Mazen, Sherif Elhennawy
{"title":"Integrated framework for cybersecurity auditing","authors":"Osamah M. Al-Matari, Iman M. A. Helal, Sherif A. Mazen, Sherif Elhennawy","doi":"10.1080/19393555.2020.1834649","DOIUrl":"https://doi.org/10.1080/19393555.2020.1834649","url":null,"abstract":"ABSTRACT Organizations receive several cyberattacks on their daily operations, thus the need for auditing. However, there is no unified tool to perform cybersecurity audit tasks which are expensive and tedious. In this paper, we build a cybersecurity framework to perform cybersecurity auditing process in organizations. It covers several types of threats and risks by providing the information systems auditors and cybersecurity professionals with several types of controls. Moreover, it illustrates the essential tools and techniques for cybersecurity auditing. The proposed framework clarifies the security issues through output reports. These reports specify the cybersecurity gaps. Also, it helps practitioners to generate an integrated tool to support cybersecurity auditors learning how to secure organizations and finding a mechanism to achieve the cybersecurity audit tasks.","PeriodicalId":103842,"journal":{"name":"Information Security Journal: A Global Perspective","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129556957","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}