Study of the Information Security of File Objects under Information Attacks with a Record of Effect of the Methods of Compression

This report examines important issues pertaining to the different ways of affecting the information security of file objects under information attacks through methods of compression. Accordingly, the report analyzes the three-way relationships which may exist among a selected set of attacks, methods and objects. Thus, a methodology is proposed for evaluation of information security, and a coefficient of information security is created. With respects to this coefficient, using different criteria and methods for evaluation and selection of alternatives, the lowest-risk methods of compression are selected.

On Handling Replay Attacks in Intrusion Detection Systems

We propose a method for detecting and analyzing the so-called replay attacks in intrusion detection systems, when an intruder contributes a small amount of hostile actions to a recorded session of a legitimate user or process, and replays this session back to the system. The proposed approach can be applied if an automata-based model is used to describe behavior of active entities in a computer system.

Computer Networks Security Models - A New Approach for Denial-of-Services Attacks Mitigation

Computer networks are a critical factor for the performance of a modern company. Managing networks is as important as managing any other aspect of the company’s performance and security. There are many tools and appliances for monitoring the traffic and analyzing the network flow security. They use different approaches and rely on a variety of characteristics of the network flows. Network researchers are still working on a common approach for security baselining that might enable early watch alerts. This research focuses on the network security models, particularly the Denial-of-Services (DoS) attacks mitigation, based on a network flow analysis using the flows measurements and the theory of Markov models. The content of the paper comprises the essentials of the author’s doctoral thesis.

Impaired brainstem and thalamic high-frequency oscillatory EEG activity in migraine between attacks

INTRODUCTION: We investigated whether interictal thalamic dysfunction in migraine without aura (MO) patients is a primary determinant or the expression of its functional disconnection from proximal or distal areas along the somatosensory pathway. METHODS: Twenty MO patients and twenty healthy volunteers (HVs) underwent an electroencephalographic (EEG) recording during electrical stimulation of the median nerve at the wrist. We used the functional source separation algorithm to extract four functionally constrained nodes (brainstem, thalamus, primary sensory radial, and primary sensory motor tangential parietal sources) along the somatosensory pathway. Two digital filters (1-400 Hz and 450-750 Hz) were applied in order to extract low- (LFO) and high- frequency (HFO) oscillatory activity from the broadband signal. RESULTS: Compared to HVs, patients presented significantly lower brainstem (BS) and thalamic (Th) HFO activation bilaterally. No difference between the two cortical HFO as well as in LFO peak activations between the two groups was seen. The age of onset of the headache was positively correlated with HFO power in the right brainstem and thalamus. CONCLUSIONS: This study provides evidence for complex dysfunction of brainstem and thalamocortical networks under the control of genetic factors that might act by modulating the severity of migraine phenotype.

International education and the post-9/11 syndrome: A study of international educators in selected Miami-area colleges

This dissertation investigated the relationship between the September 11, 2001 terrorist attacks and the internationalization agenda of U.S. colleges and universities. The construct, post-9/11 syndrome, is used metaphorically to delineate the apparent state of panic and disequilibrium that followed the incident. Three research questions were investigated, with two universities in the Miami-area of South Florida, one private and the other public, as qualitative case studies. The questions are: (a) How are international student advisors and administrators across two types of institutions dealing with the post-9/11 syndrome? (b) What, if any, are the differences in international education after 9/11? (c) What have been the institutional priorities in relation to international education before and after 9/11? Data-gathering methods included interviews with international student/study abroad advisors and administrators with at least 8 years of experience in the function(s) at their institutions, document and institutional data analysis. The interviews were based on the three-part scheme developed by Schuman (1982): context of experience, details of experience and reflection on the meaning of experiences. Taped interviews, researcher insights, and member checks of transcripts constituted an audit trail for this study. Key findings included a progressive decline in Fall to Fall enrollment of international students at UM by 13.05% in the 5 years after 9/11, and by 6.15% at FIU in the seven post-9/11 years. In both institutions, there was an upsurge in interest in study abroad during the same period but less than 5% of enrolled students ventured abroad annually. I summarized the themes associated with the post-9/11 environment of international education as perceived by my participants at both institutions as 3Ms, 3Ts, and 1D: Menace of Anxiety and Fear, Menace of Insularity and Insecurity, Menace of Over-Regulation and Bigotry, Trajectory of Opportunity, Trajectory of Contradictions, Trajectory of Illusion, Fatalism and Futility, and Dominance of Technology. Based on these findings, I recommended an integrated Internationalization At Home Plus Collaborative Outreach (IAHPCO) approach to internationalization that is based on a post-9/11 recalibration of national security and international education as complementary rather than diametrically opposed concepts.

Freedom of thought in the aftermath of the Charlie Hebdo attacks

Peer reviewed

The statutory rape crisis: a moral panic?

In this thesis I argue that the statutory rape crisis which materialised following the decisions in CC v Ireland and A v The Governor of Arbour Hill Prison, was a moral panic. I also contend that Mr A, a convicted sex offender who was released during the crisis, was a folk devil. Using data obtained from an ethnographic content analysis of a selection of newspapers, interest group statements, and Oireachtas debates, I demonstrate that the social response to the statutory rape crisis exhibits the key indicators of the moral panic phenomenon put forward by Goode and Ben-Yehuda. These key indicators are: concern, consensus, hostility, disproportionality and volatility. I employ the theory of moral panic to explain why the events of the statutory rape crisis ignited such emotion and why Mr A became a folk devil of the moral panic

Sensor Intelligence for Tackling Energy-Drain Attacks on Wireless Sensor Networks

In this paper we propose a model for intelligent agents (sensors) on a Wireless Sensor Network to guard against energy-drain attacks in an energy-efficient and autonomous manner. This is intended to be achieved via an energy-harvested Wireless Sensor Network using a novel architecture to propagate knowledge to other sensors based on automated reasoning from an attacked sensor.

Criminalising the payment for sex in northern ireland; sketching the contours of a moral panic

This paper examines recent legislative developments in Northern Ireland around Lord Morrow’s Human Trafficking & Exploitation (Further Provisions and Support for Victims) Bill that was passed unanimously in the Northern Ireland Assembly and which uniquely in the United Kingdom now makes it a criminal offence to pay for sexual services. I suggest that issues around sex trafficking, sexual slavery and prostitution in Northern Ireland bear all the hallmarks of Stan Cohen’s famous articulation of a moral panic (Cohen 1972) but also argue that his original for- mulation needs to be recast slightly to take account of the horizontal structuring of moral panics in contemporary society.

Detecting stealthy attacks: Efficient monitoring of suspicious activities on computer networks

Stealthy attackers move patiently through computer networks - taking days, weeks or months to accomplish their objectives in order to avoid detection. As networks scale up in size and speed, monitoring for such attack attempts is increasingly a challenge. This paper presents an efficient monitoring technique for stealthy attacks. It investigates the feasibility of proposed method under number of different test cases and examines how design of the network affects the detection. A methodological way for tracing anonymous stealthy activities to their approximate sources is also presented. The Bayesian fusion along with traffic sampling is employed as a data reduction method. The proposed method has the ability to monitor stealthy activities using 10-20% size sampling rates without degrading the quality of detection.

Data Mining for Network Intrusion Detection : A comparison of data mining algorithms and an analysis of relevant features for detecting cyber-attacks

Data mining can be defined as the extraction of implicit, previously un-known, and potentially useful information from data. Numerous re-searchers have been developing security technology and exploring new methods to detect cyber-attacks with the DARPA 1998 dataset for Intrusion Detection and the modified versions of this dataset KDDCup99 and NSL-KDD, but until now no one have examined the performance of the Top 10 data mining algorithms selected by experts in data mining. The compared classification learning algorithms in this thesis are: C4.5, CART, k-NN and Naïve Bayes. The performance of these algorithms are compared with accuracy, error rate and average cost on modified versions of NSL-KDD train and test dataset where the instances are classified into normal and four cyber-attack categories: DoS, Probing, R2L and U2R. Additionally the most important features to detect cyber-attacks in all categories and in each category are evaluated with Weka’s Attribute Evaluator and ranked according to Information Gain. The results show that the classification algorithm with best performance on the dataset is the k-NN algorithm. The most important features to detect cyber-attacks are basic features such as the number of seconds of a network connection, the protocol used for the connection, the network service used, normal or error status of the connection and the number of data bytes sent. The most important features to detect DoS, Probing and R2L attacks are basic features and the least important features are content features. Unlike U2R attacks, where the content features are the most important features to detect attacks.

Passivity Framework for Modeling, Composing and Mitigating Cyber Attacks

Thesis (Ph.D.)--University of Washington, 2016-08

Personalised TV ads are the future – but is it time to panic?

TV Advertising is evolving quickly. This article examines how the popularity of viewing content on mobile platforms is changing the way we advertise. VOD and OTT media services have meant that advertisers can now automate and personalise their TV advertising. It's having a significant impact on the UK TV business model.