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2022-09-29
Al-Alawi, Adel Ismail, Alsaad, Abdulla Jalal, AlAlawi, Ebtesam Ismaeel, Naser Al-Hadad, Ahmed Abdulla.  2021.  The Analysis of Human Attitude toward Cybersecurity Information Sharing. 2021 International Conference on Decision Aid Sciences and Application (DASA). :947–956.
Over the years, human errors have been identified as one of the most critical factors impacting cybersecurity in an organization that has had a substantial impact. The research uses recent articles published on human resources and information cybersecurity. This research focuses on the vulnerabilities and the best solution to mitigate these threats based on literature review methodology. The study also focuses on identifying the human attitude and behavior towards cybersecurity and how that would impact the organization's financial impact. With the help of the Two-factor Taxonomy of the security behavior model developed in past research, the research aims to identify the best practices and compare the best practices with that of the attitude-behavior found and matched to the model. Finally, the study would compare the difference between best practices and the current practices from the model. This would help provide the organization with specific recommendations that would help change their attitude and behavior towards cybersecurity and ensure the organization is not fearful of the cyber threat of human error threat.
2021-08-11
Mathas, Christos-Minas, Vassilakis, Costas, Kolokotronis, Nicholas.  2020.  A Trust Management System for the IoT domain. 2020 IEEE World Congress on Services (SERVICES). :183–188.
In modern internet-scale computing, interaction between a large number of parties that are not known a-priori is predominant, with each party functioning both as a provider and consumer of services and information. In such an environment, traditional access control mechanisms face considerable limitations, since granting appropriate authorizations to each distinct party is infeasible both due to the high number of grantees and the dynamic nature of interactions. Trust management has emerged as a solution to this issue, offering aids towards the automated verification of actions against security policies. In this paper, we present a trust- and risk-based approach to security, which considers status, behavior and associated risk aspects in the trust computation process, while additionally it captures user-to-user trust relationships which are propagated to the device level, through user-to-device ownership links.
2020-10-12
Flores, Pedro, Farid, Munsif, Samara, Khalid.  2019.  Assessing E-Security Behavior among Students in Higher Education. 2019 Sixth HCT Information Technology Trends (ITT). :253–258.
This study was conducted in order to assess the E-security behavior of students in a large higher educational institutions in the United Arab Emirates (UAE). Specifically, it sought to determine the current state of students' E-security behavior in the aspects of malware, password usage, data handling, phishing, social engineering, and online scam. An E- Security Behavior Survey Instrument (EBSI) was used to determine the status of security behavior of the participants in doing their computing activities. To complement the survey tool, focus group discussions were conducted to elicit specific experiences and insights of the participants relative to E-security. The results of the study shows that the overall E-security behavior among students in higher education in the United Arab Emirates (UAE) is moderately favorable. Specifically, the investigation reveals that the students favorably behave when it comes to phishing, social engineering, and online scam. However, they uncertainly behave on malware issues, password usage, and data handling.
2020-03-09
Hăjmăȿan, Gheorghe, Mondoc, Alexandra, Creț, Octavian.  2019.  Bytecode Heuristic Signatures for Detecting Malware Behavior. 2019 Conference on Next Generation Computing Applications (NextComp). :1–6.
For a long time, the most important approach for detecting malicious applications was the use of static, hash-based signatures. This approach provides a fast response time, has a low performance overhead and is very stable due to its simplicity. However, with the rapid growth in the number of malware, as well as their increased complexity in terms of polymorphism and evasion, the era of reactive security solutions started to fade in favor of new, proactive approaches such as behavior based detection. We propose a novel approach that uses an interpreter virtual machine to run proactive behavior heuristics from bytecode signatures, thus combining the advantages of behavior based detection with those of signatures. Based on our approximation, using this approach we succeeded to reduce by 85% the time required to update a behavior based detection solution to detect new threats, while continuing to benefit from the versatility of behavior heuristics.
2020-01-20
Bharathy, A M Viswa, Umapathi, N, Prabaharan, S.  2019.  An Elaborate Comprehensive Survey on Recent Developments in Behaviour Based Intrusion Detection Systems. 2019 International Conference on Computational Intelligence in Data Science (ICCIDS). :1–5.

Intrusion detection system is described as a data monitoring, network activity study and data on possible vulnerabilities and attacks in advance. One of the main limitations of the present intrusion detection technology is the need to take out fake alarms so that the user can confound with the data. This paper deals with the different types of IDS their behaviour, response time and other important factors. This paper also demonstrates and brings out the advantages and disadvantages of six latest intrusion detection techniques and gives a clear picture of the recent advancements available in the field of IDS based on the factors detection rate, accuracy, average running time and false alarm rate.

2019-11-26
Ku, Yeeun, Park, Leo Hyun, Shin, Sooyeon, Kwon, Taekyoung.  2018.  A Guided Approach to Behavioral Authentication. Proceedings of the 2018 ACM SIGSAC Conference on Computer and Communications Security. :2237-2239.

User's behavioral biometrics are promising as authentication factors in particular if accuracy is sufficiently guaranteed. They can be used to augment security in combination with other authentication factors. A gesture-based pattern lock system is a good example of such multi-factor authentication, using touch dynamics in a smartphone. However, touch dynamics can be significantly affected by a shape of gestures with regard to the performance and accuracy, and our concern is that user-chosen patterns are likely far from producing such a good shape of gestures. In this poster, we raise this problem and show our experimental study conducted in this regard. We investigate if there is a reproducible correlation between shape and accuracy and if we can derive effective attribute values for user guidance, based on the gesture-based pattern lock system. In more general, we discuss a guided approach to behavioral authentication.

2019-03-15
Noor, U., Anwar, Z., Noor, U., Anwar, Z., Rashid, Z..  2018.  An Association Rule Mining-Based Framework for Profiling Regularities in Tactics Techniques and Procedures of Cyber Threat Actors. 2018 International Conference on Smart Computing and Electronic Enterprise (ICSCEE). :1-6.

Tactics Techniques and Procedures (TTPs) in cyber domain is an important threat information that describes the behavior and attack patterns of an adversary. Timely identification of associations between TTPs can lead to effective strategy for diagnosing the Cyber Threat Actors (CTAs) and their attack vectors. This study profiles the prevalence and regularities in the TTPs of CTAs. We developed a machine learning-based framework that takes as input Cyber Threat Intelligence (CTI) documents, selects the most prevalent TTPs with high information gain as features and based on them mine interesting regularities between TTPs using Association Rule Mining (ARM). We evaluated the proposed framework with publicly available TTPbased CTI documents. The results show that there are 28 TTPs more prevalent than the other TTPs. Our system identified 155 interesting association rules among the TTPs of CTAs. A summary of these rules is given to effectively investigate threats in the network.