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This study attempts to explore the potential in employees to positively contribute to organizational information security management. Toward that end, this study developed the concept of proactive information security behavior and examined its connections to individual creativity and two organizational context factors: group culture and decentralized IT governance. Findings of this study supported...
Attack graph technique is a common tool for the evaluation of network security. However, attack graphs are generally too large and complex to be understood and interpreted by security administrators. This paper proposes an analysis framework for security attack graphs for a given IT infrastructure system. First, in order to facilitate the discovery of interconnectivities among vulnerabilities in a...
Cyber-attacks are constantly increasing and can prove difficult to mitigate, even with proper cybersecurity controls. Currently, cyber threat intelligence (CTI) efforts focus on internal threat feeds such as antivirus and system logs. While this approach is valuable, it is reactive in nature as it relies on activity which has already occurred. CTI experts have argued that an actionable CTI program...
Identifying the physical person behind an SNS account has become a critical issue in investigations of SNS-involved crime cases. It is a challenging task because information provided by users on an SNS platform could be false, conflicting, missing and deceptive. One way to gain an accurate profile of a user is to link up all their multiple accounts created on different social platforms, which is referred...
This paper focuses on one type of Covert Storage Channel (CSC) that uses the 6-bit TCP flag header in TCP/IP network packets to transmit secret messages between accomplices. We use relative entropy to characterize the irregularity of network flows in comparison to normal traffic. A normal profile is created by the frequency distribution of TCP flags in regular traffic packets. In detection, the TCP...
This paper takes an unsupervised learning approach for monitoring edge activity within an enterprise computer network. Using NetFlow records, features are gathered across the active connections (edges) in 15-minute time windows. Then, edges are grouped into clusters using the k-means algorithm. This process is repeated over contiguous windows. A series of informative indicators are derived by examining...
Terror operations are carried out by a team of terrorists with their interaction and cooperation. Different tie strengths, such as acquaintances, friends, and family members, influence the construction and reconstruction of the operation team. Understanding the interaction patterns of tie strength might be useful not only for advancing our understanding of terror operations, but ultimately for providing...
Traffic classification plays an important and basic role in network management and cyberspace security. With the widespread use of encryption techniques in network applications, encrypted traffic has recently become a great challenge for the traditional traffic classification methods. In this paper we proposed an end-to-end encrypted traffic classification method with one-dimensional convolution neural...
In order to effectively evaluate the impact on network situation under DDoS attacks, this paper proposes a hierarchical network threat situation assessment method based on D-S evidence theory for DDoS. It is divided into the basic data acquisition layer, the metric indexes extraction layer, the device threat assessment layer and the threat situation assessment layer. Firstly, we calculate indexes...
Over the years social network data has been mined to predict individuals' traits such as intelligence and sexual orientation. While mining social network data can provide many beneficial services to the user such as personalized experiences, it can also harm the user when used in making critical decisions such as employment. In this work, we investigate the reliability of applying data mining techniques...
This paper presents a system that uses machine learning to recognize military vehicles in social media images. To do so, the system draws on recent advances in applying deep neural networks to computer vision tasks, while also making extensive use of openly available libraries, models and data. Training a vehicle recognition system over three classes, the paper reports on two experiments that use...
This article describes a framework for semantic annotation of texts that are submitted for forensic analysis, based on Frame Semantics, and a knowledge base of Forensic Frames — FrameFOR. We demonstrate through experimental evaluations that the application of the Semantic Role Labeling (SRL) techniques and Natural Language Processing (NLP) in digital forensic increases the performance of the forensic...
In the last decade, numerous fake websites have been developed on the World Wide Web to mimic trusted websites, with the aim of stealing financial assets from users and organizations. This form of online attack is called phishing, and it has cost the online community and the various stakeholders hundreds of million Dollars. Therefore, effective counter measures that can accurately detect phishing...
This paper explores the recently published works on iris template protection namely Indexing-First-One hashing. Despite the Indexing-First-One hashing offers high recognition performance with resistant against several major privacy and security attacks, it does not resolve the rotation inconsistent issues existed in conventional iris template due to head tilt/ rotation during user's eyes images acquisition...
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