Journal of Cybersecurity and Privacy最新文献

{"title":"Calibrating the Attack to Sensitivity in Differentially Private Mechanisms","authors":"Ayşe Ünsal, Melek Önen","doi":"10.3390/jcp2040042","DOIUrl":"https://doi.org/10.3390/jcp2040042","url":null,"abstract":"This work studies the power of adversarial attacks against machine learning algorithms that use differentially private mechanisms as their weapon. In our setting, the adversary aims to modify the content of a statistical dataset via insertion of additional data without being detected by using the differential privacy to her/his own benefit. The goal of this study is to evaluate how easy it is to detect such attacks (anomalies) when the adversary makes use of Gaussian and Laplacian perturbation using both statistical and information-theoretic tools. To this end, firstly via hypothesis testing, we characterize statistical thresholds for the adversary in various settings, which balances the privacy budget and the impact of the attack (the modification applied on the original data) in order to avoid being detected. In addition, we establish the privacy-distortion trade-off in the sense of the well-known rate-distortion function for the Gaussian mechanism by using an information-theoretic approach. Accordingly, we derive an upper bound on the variance of the attacker’s additional data as a function of the sensitivity and the original data’s second-order statistics. Lastly, we introduce a new privacy metric based on Chernoff information for anomaly detection under differential privacy as a stronger alternative for the (ϵ,δ)-differential privacy in Gaussian mechanisms. Analytical results are supported by numerical evaluations.","PeriodicalId":316237,"journal":{"name":"Journal of Cybersecurity and Privacy","volume":"9 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132606065","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 Survey of the Recent Trends in Deep Learning Based Malware Detection","authors":"Umm-e-Hani Tayyab, Faiza Babar Khan, M. H. Durad, Asifullah Khan, Yeon Soo Lee","doi":"10.3390/jcp2040041","DOIUrl":"https://doi.org/10.3390/jcp2040041","url":null,"abstract":"Monitoring Indicators of Compromise (IOC) leads to malware detection for identifying malicious activity. Malicious activities potentially lead to a system breach or data compromise. Various tools and anti-malware products exist for the detection of malware and cyberattacks utilizing IOCs, but all have several shortcomings. For instance, anti-malware systems make use of malware signatures, requiring a database containing such signatures to be constantly updated. Additionally, this technique does not work for zero-day attacks or variants of existing malware. In the quest to fight zero-day attacks, the research paradigm shifted from primitive methods to classical machine learning-based methods. Primitive methods are limited in catering to anti-analysis techniques against zero-day attacks. Hence, the direction of research moved towards methods utilizing classic machine learning, however, machine learning methods also come with certain limitations. They may include but not limited to the latency/lag introduced by feature-engineering phase on the entire training dataset as opposed to the real-time analysis requirement. Likewise, additional layers of data engineering to cater to the increasing volume of data introduces further delays. It led to the use of deep learning-based methods for malware detection. With the speedy occurrence of zero-day malware, researchers chose to experiment with few shot learning so that reliable solutions can be produced for malware detection with even a small amount of data at hand for training. In this paper, we surveyed several possible strategies to support the real-time detection of malware and propose a hierarchical model to discover security events or threats in real-time. A key focus in this survey is on the use of Deep Learning-based methods. Deep Learning based methods dominate this research area by providing automatic feature engineering, the capability of dealing with large datasets, enabling the mining of features from limited data samples, and supporting one-shot learning. We compare Deep Learning-based approaches with conventional machine learning based approaches and primitive (statistical analysis based) methods commonly reported in the literature.","PeriodicalId":316237,"journal":{"name":"Journal of Cybersecurity and Privacy","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123035904","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 Distributed Model for Privacy Preserving V2I Communication with Strong Unframeability and Efficient Revocation","authors":"Panayiotis Kalogeropoulos, Dimitris Papanikas, P. Kotzanikolaou","doi":"10.3390/jcp2040040","DOIUrl":"https://doi.org/10.3390/jcp2040040","url":null,"abstract":"Although Vehicle to Infrastructure (V2I) communications greatly improve the efficiency of early warning systems for car safety, communication privacy is an important concern. Although solutions exist in the literature for privacy preserving VANET communications, they usually require high trust assumptions for a single authority. In this paper we propose a distributed trust model for privacy preserving V2I communications. Trust is distributed among a certification authority that issues the vehicles’ credentials, and a signing authority that anonymously authenticates V2I messages in a zero knowledge manner. Anonymity is based on bilinear pairings and partially blind signatures. In addition, our system supports enhanced conditional privacy since both authorities and the relevant RSU need to collaborate to trace a message back to a vehicle, while efficient certificateless revocation is supported. Moreover, our scheme provides strong unframeability for honest vehicles. Even if all the entities collude, it is not possible to frame a honest vehicle, by tracing a forged message back to an honest vehicle. The proposed scheme concurrently achieves conditional privacy and strong unframeabilty for vehicles, without assuming a fully trusted authority. Our evaluation results show that the system allows RSUs to efficiently handle multiple messages per second, which suffices for real world implementations.","PeriodicalId":316237,"journal":{"name":"Journal of Cybersecurity and Privacy","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133745655","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":"Detection of SQL Injection Attack Using Machine Learning Techniques: A Systematic Literature Review","authors":"Maha Alghawazi, D. Alghazzawi, Suaad S. Alarifi","doi":"10.3390/jcp2040039","DOIUrl":"https://doi.org/10.3390/jcp2040039","url":null,"abstract":"An SQL injection attack, usually occur when the attacker(s) modify, delete, read, and copy data from database servers and are among the most damaging of web application attacks. A successful SQL injection attack can affect all aspects of security, including confidentiality, integrity, and data availability. SQL (structured query language) is used to represent queries to database management systems. Detection and deterrence of SQL injection attacks, for which techniques from different areas can be applied to improve the detect ability of the attack, is not a new area of research but it is still relevant. Artificial intelligence and machine learning techniques have been tested and used to control SQL injection attacks, showing promising results. The main contribution of this paper is to cover relevant work related to different machine learning and deep learning models used to detect SQL injection attacks. With this systematic review, we aims to keep researchers up-to-date and contribute to the understanding of the intersection between SQL injection attacks and the artificial intelligence field.","PeriodicalId":316237,"journal":{"name":"Journal of Cybersecurity and Privacy","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126360252","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":"Exploratory Study on Kali NetHunter Lite: A Digital Forensics Approach","authors":"Miloš Stanković, Umit Karabiyik","doi":"10.3390/jcp2030038","DOIUrl":"https://doi.org/10.3390/jcp2030038","url":null,"abstract":"Mobile devices, specifically smartphones, have become a necessity in everyday life, as we perform many essential day-to-day tasks using these devices. With the projected increase in mobile devices to 18.22 billion by 2025, the reliance on smartphones will only grow. This demand for smartphones has allowed various companies to start developing their own devices and custom operating systems, each of which puts its own touch on them. In addition, current smartphones have increased processing power, providing users with a computer experience in their pockets. Software developers have taken this opportunity to bridge the gap between personal computers and smartphones by creating the same software for personal computers and mobile devices. Kali Linux is one of the most popular penetration testing tools for desktop use and has been adapted to operate on mobile devices under the name Kali NetHunter. Kali NetHunter has three different versions on mobile platforms that provide various levels of capabilities. Kali NetHunter is just one example in which an application or an operating system applies to a specific niche of users. Highly customized operating systems or applications do not receive the same attention as field research, leaving them unfamiliar to mobile forensic investigators when used maliciously. In this paper, we conducted an exploratory study on the Kali NetHunter Lite application after it was installed and its embedded tools were utilized. Our results show a detailed analysis of the file system and reveal the data from the tests carried out during various phases. Furthermore, the locations of the folders involved in the process were described.","PeriodicalId":316237,"journal":{"name":"Journal of Cybersecurity and Privacy","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129100122","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":"Generic Patterns for Intrusion Detection Systems in Service-Oriented Automotive and Medical Architectures","authors":"A. Puder, Marcel Rumez, D. Grimm, E. Sax","doi":"10.3390/jcp2030037","DOIUrl":"https://doi.org/10.3390/jcp2030037","url":null,"abstract":"To implement new software functions and more flexible updates in the future as well as to provide cloud-based functionality, the service-oriented architecture (SOA) paradigm is increasingly being integrated into automotive electrical and electronic architecture (E/E architectures). In addition to the automotive industry, the medical industry is also researching SOA-based solutions to increase the interoperability of devices (vendor-independent). The resulting service-oriented communication is no longer fully specified during design time, which affects information security measures. In this paper, we compare different SOA protocols for the automotive and medical fields. Furthermore, we explain the underlying communication patterns and derive features for the development of an SOA-based Intrusion Detection System (IDS).","PeriodicalId":316237,"journal":{"name":"Journal of Cybersecurity and Privacy","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116485733","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":"Contactless Fingerprint Recognition Using Deep Learning—A Systematic Review","authors":"Mokter Mahmud Chowdhury, M. Imtiaz","doi":"10.3390/jcp2030036","DOIUrl":"https://doi.org/10.3390/jcp2030036","url":null,"abstract":"Contactless fingerprint identification systems have been introduced to address the deficiencies of contact-based fingerprint systems. A number of studies have been reported regarding contactless fingerprint processing, including classical image processing, the machine-learning pipeline, and a number of deep-learning-based algorithms. The deep-learning-based methods were reported to have higher accuracies than their counterparts. This study was thus motivated to present a systematic review of these successes and the reported limitations. Three methods were researched for this review: (i) the finger photo capture method and corresponding image sensors, (ii) the classical preprocessing method to prepare a finger image for a recognition task, and (iii) the deep-learning approach for contactless fingerprint recognition. Eight scientific articles were identified that matched all inclusion and exclusion criteria. Based on inferences from this review, we have discussed how deep learning methods could benefit the field of biometrics and the potential gaps that deep-learning approaches need to address for real-world biometric applications.","PeriodicalId":316237,"journal":{"name":"Journal of Cybersecurity and Privacy","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127017361","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":"Exploiting Online Services to Enable Anonymous and Confidential Messaging","authors":"Pedro Sousa, António Pinto, Pedro Pinto","doi":"10.3390/jcp2030035","DOIUrl":"https://doi.org/10.3390/jcp2030035","url":null,"abstract":"Messaging services are usually provided within social network platforms and allow these platforms to collect additional information about users, such as what time, for how long, with whom, and where a user communicates. This information allows the identification of users and is available to the messaging service provider even when communication is encrypted end-to-end. Thus, a gap still exists for alternative messaging services that enable anonymous and confidential communication and that are independent of a specific online service. Online services can still be used to support this messaging service, but in a way that enables users to communicate anonymously and without the knowledge and scrutiny of the online services. In this paper, we propose messaging using steganography and online services to support anonymous and confidential communication. In the proposed messaging service, only the sender and the receiver are aware of the existence of the exchanged data, even if the online services used or other third parties have access to the exchanged secret data containers. This work reviews the viability of using existing online services to support the proposed messaging service. Moreover, a proof-of-concept of the proposed message service is implemented and tested using two online services acting as proxies in the exchange of encrypted information disguised within images and links to those images. The obtained results confirm the viability of such a messaging service.","PeriodicalId":316237,"journal":{"name":"Journal of Cybersecurity and Privacy","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115239176","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 Synopsis of “The Impact of Motivation, Price, and Habit on Intention to Use IoT-Enabled Technology: A Correlational Study”","authors":"Christina L. Phibbs, Shawon S. M. Rahman","doi":"10.3390/jcp2030034","DOIUrl":"https://doi.org/10.3390/jcp2030034","url":null,"abstract":"Older adults in the U.S. are interested in maintaining independence, aging at home longer, and staying active. Their substantial size, market share, and household wealth sparked the interest of investors and developers in remote monitoring, smart homes, ambient-assisted living, tracking, applications, and sensors via the IoT. This study used the unified theory of acceptance and use of technology extended (UTAUT2). The overarching research question was: “To what extent do performance, effort, influence, conditions, motivation, price, and habit affect older adults’ behavioral intent to use IoT technologies in their homes?” The research methodology for this study was a nonexperimental correlation of the variables that affect older adults’ intention to use IoT-enabled technologies in their homes. The population was adults 60 plus years in northern Virginia. The sample consisted of 316 respondents. The seven predictors cumulatively influenced older adults’ behavioral intent to use IoT-enabled technologies, F(7, 308) = 133.50, p < 0.001, R2 = 0.75. The significant predictors of behavioral intention to use IoT technologies were performance expectancy (B = 0.244, t(308) = 4.427, p < 0.001), social influence (B = 0.138, t(308) = 3.4775, p = 0.001), facilitating conditions (B = 0.184, t(308) = 2.999, p = 0.003), hedonic motivation (B = 0.153, t(308) = 2.694, p = 0.007), price value (B = 0.140, t(308) = 3.099, p = 0.002), and habit (B = 0.378, t(308) = 8.696, p < 0.001). Effort expectancy was insignificant (B = −0.026, t(308) = −0.409, p = 0.683). This study filled the gap in research on older adults’ acceptance of IoT by focusing specifically on that population. The findings help reduce the risk of solutions driven by technological and organizational requirements rather than the older adults’ unique needs and requirements. The study revealed that older adults may be susceptible to undue influence to adopt IoT solutions. These socioeconomic dimensions of the UTAUT2 are essential to the information technology field because the actualizing of IoT-enabled technologies in private homes depends on older adults’ participation and adoption. This research is beneficial to IoT developers, implementers, cybersecurity researchers, healthcare providers, caregivers, and managers of in-home care providers regarding adding IoT technologies in their homes.","PeriodicalId":316237,"journal":{"name":"Journal of Cybersecurity and Privacy","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133866442","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":"Security and Privacy Management in Internet of Medical Things (IoMT): A Synthesis","authors":"Rachida Hireche, Houssem Mansouri, A. Pathan","doi":"10.3390/jcp2030033","DOIUrl":"https://doi.org/10.3390/jcp2030033","url":null,"abstract":"The Internet of Medical Things (IoMT) has become a strategic priority for future e-healthcare because of its ability to improve patient care and its scope of providing more reliable clinical data, increasing efficiency, and reducing costs. It is no wonder that many healthcare institutions nowadays like to harness the benefits offered by the IoMT. In fact, it is an infrastructure with connected medical devices, software applications, and care systems and services. However, the accelerated adoption of connected devices also has a serious side effect: it obscures the broader need to meet the requirements of standard security for modern converged environments (even beyond connected medical devices). Adding up different types and numbers of devices risks creating significant security vulnerabilities. In this paper, we have undertaken a study of various security techniques dedicated to this environment during recent years. This study enables us to classify these techniques and to characterize them in order to benefit from their positive aspects.","PeriodicalId":316237,"journal":{"name":"Journal of Cybersecurity and Privacy","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133669206","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}