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International Conferences: CyberSA 2015 London |
The 2015 International Conference on Cyber Situational Awareness, Data Analytics and Assessment (CyberSA) was held in London on 8-9 June 2015. Papers presented at the conference focused on the principles, methods, and applications of situational awareness on Cyber Systems, Business Information Systems (BIS), Computer Network Defence (CND), Computer Physical Systems (CPS) and Internet of Things (IoTs).
Hall, M.J.; Hansen, D.D.; Jones, K., “Cross-Domain Situational Awareness and Collaborative Working for Cyber Security,” in Cyber Situational Awareness, Data Analytics and Assessment (CyberSA), 2015 International Conference on, vol., no., pp. 1-8, 8-9 June 2015. doi:10.1109/CyberSA.2015.7166110
Abstract: Enhancing situational awareness is a major goal for organisations spanning many sectors, working across many domains. An increased awareness of the state of environments enables improved decision-making. Endsley's model of situational awareness has improved the understanding for the design of decision-support systems. This paper presents and discusses a theoretical model to extend this to cross-domain working to influence the design of future collaborative systems. A use-case is discussed within a military context of the use of this model for cross-domain working between an operational-domain and cyber security-domain.
Keywords: decision making; decision support systems; groupware; security of data; collaborative working; cross-domain situational awareness; cyber security-domain; future collaborative systems; improved decision-making; operational-domain; Aerodynamics; Collaboration; Context; Decision making; Feeds; Malware; Collaboration; Cross Domain; Cyber Security; Situational Awareness (ID#: 15-6471)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7166110&isnumber=7166109
Neogy, S., “Security Management in Wireless Sensor Networks,” in Cyber Situational Awareness, Data Analytics and Assessment (CyberSA), 2015 International Conference on, vol., no., pp. 1-4, 8-9 June 2015. doi:10.1109/CyberSA.2015.7166112
Abstract: This paper aims to describe the characteristics of Wireless Sensor Networks (WSNs), challenges in designing a resource-constrained and vulnerable network and address security management as the main issue. The work begins with discussion on the attacks on WSNs. As part of protection against the attacks faced by WSNs, key management, the primary requirement of any security practice, is detailed out. This paper also deals with the existing security schemes covering various routing protocols. The paper also touches security issues concerning heterogeneous networks.
Keywords: routing protocols; telecommunication security; wireless sensor networks; WSN; heterogeneous networks; security management schemes; Cryptography; Receivers; Routing; Routing protocols; Wireless sensor networks; attack; cryptography; key management; protocol; routing; security; wireless sensor network (ID#: 15-6472)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7166112&isnumber=7166109
Rickus, A.; Pfluegel, E.; Atkins, N., “Chaos-Based Image Encryption Using an AONT Mode of Operation,” in Cyber Situational Awareness, Data Analytics and Assessment (CyberSA), 2015 International Conference on, vol., no., pp. 1-5, 8-9 June 2015. doi:10.1109/CyberSA.2015.7166113
Abstract: Chaos-based cryptography is a promising and emerging field that offers a large variety of techniques particularly suitable for applications such as image encryption. The fundamental characteristics of chaotic systems are closely related to the properties of a strong cryptosystem. Most research on chaos-based encryption does not concentrate on the aspect of encryption modes of operation. This paper introduces a new chaos-based image encryption scheme using an all-or-nothing transform (AONT) mode of operation. This results in a novel non-separable chaos-based mode which we have implemented and evaluated. Our results show that the AONT mode achieves a security gain with little overhead on the overall efficiency of the encryption.
Keywords: chaos; cryptography; image processing; transforms; AONT mode of operation; all-or-nothing transform mode of operation; chaos-based cryptography; chaos-based image encryption; nonseparable chaos-based mode; Chaotic communication; Ciphers; Encryption; Logistics; AONT encryption mode of operation; Baker map; Chaos-based cryptography; Logistic map
(ID#: 15-6473)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7166113&isnumber=7166109
Enache, A.-C.; Ionita, M.; Sgarciu, V., “An Immune Intelligent Approach for Security Assurance,” in Cyber Situational Awareness, Data Analytics and Assessment (CyberSA), 2015 International Conference on, vol., no., pp. 1-5, 8-9 June 2015. doi:10.1109/CyberSA.2015.7166116
Abstract: Information Security Assurance implies ensuring the integrity, confidentiality and availability of critical assets for an organization. The large amount of events to monitor in a fluid system in terms of topology and variety of new hardware or software, overwhelms monitoring controls. Furthermore, the multi-facets of cyber threats today makes it difficult even for security experts to handle and keep up-to-date. Hence, automatic “intelligent” tools are needed to address these issues. In this paper, we describe a ‘work in progress’ contribution on intelligent based approach to mitigating security threats. The main contribution of this work is an anomaly based IDS model with active response that combines artificial immune systems and swarm intelligence with the SVM classifier. Test results for the NSL-KDD dataset prove the proposed approach can outperform the standard classifier in terms of attack detection rate and false alarm rate, while reducing the number of features in the dataset.
Keywords: artificial immune systems; pattern classification; security of data; support vector machines; NSL-KDD dataset; SVM classifier; anomaly based IDS model; artificial immune system; asset availability; asset confidentiality; asset integrity; attack detection rate; cyber threats; false alarm rate; immune intelligent approach; information security assurance; intrusion detection system; security threats mitigation; support vector machines; swarm intelligence; Feature extraction; Immune system; Intrusion detection; Particle swarm optimization; Silicon; Support vector machines; Binary Bat Algorithm; Dendritic Cell Algorithm; IDS; SVM (ID#: 15-6474)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7166116&isnumber=7166109
Wurzenberger, M.; Skopik, F.; Settanni, G.; Fiedler, R., “Beyond Gut Instincts: Understanding, Rating and Comparing Self-Learning IDSs,” in Cyber Situational Awareness, Data Analytics and Assessment (CyberSA), 2015 International Conference on, vol., no., pp. 1-1, 8-9 June 2015. doi:10.1109/CyberSA.2015.7166117
Abstract: Today ICT networks are the economy's vital backbone. While their complexity continuously evolves, sophisticated and targeted cyber attacks such as Advanced Persistent Threats (APTs) become increasingly fatal for organizations. Numerous highly developed Intrusion Detection Systems (IDSs) promise to detect certain characteristics of APTs, but no mechanism which allows to rate, compare and evaluate them with respect to specific customer infrastructures is currently available. In this paper, we present BAESE, a system which enables vendor independent and objective rating and comparison of IDSs based on small sets of customer network data.
Keywords: security of data; APT; BAESE system; ICT networks; advanced persistent threats; customer infrastructures; customer network data; cyber attacks; economy vital backbone; intrusion detection systems; self-learning IDS; Analytical models; Complexity theory; Data models; Intrusion detection; Organizations; Safety (ID#: 15-6475)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7166117&isnumber=7166109
Bode, M.A.; Alese, B.K.; Oluwadare, S.A.; Thompson, A.F.-B., “Risk Analysis in Cyber Situation Awareness Using Bayesian Approach,” in Cyber Situational Awareness, Data Analytics and Assessment (CyberSA), 2015 International Conference on, vol., no., pp. 1-12, 8-9 June 2015. doi:10.1109/CyberSA.2015.7166119
Abstract: The unpredictable cyber attackers and threats have to be detected in order to determine the outcome of risk in a network environment. This work develops a Bayesian network classifier to analyse the network traffic in a cyber situation. It is a tool that aids reasoning under uncertainty to determine certainty. It further analyze the level of risk using a modified risk matrix criteria. The classifier developed was experimented with various records extracted from the KDD Cup'99 dataset with 490,021 records. The evaluations showed that the Bayesian Network classifier is a suitable model which resulted in same performance level for classifying the Denial of Service (DoS) attacks with Association Rule Mining while as well as Genetic Algorithm, the Bayesian Network classifier performed better in classifying probe and User to Root (U2R) attacks and classified DoS equally. The result of the classification showed that Bayesian network classifier is a classification model that thrives well in network security. Also, the level of risk analysed from the adapted risk matrix showed that DoS attack has the most frequent occurrence and falls in the generally unacceptable risk zone.
Keywords: Bayes methods; belief networks; computer network security; data mining; inference mechanisms; pattern classification; risk analysis; Bayesian approach; Bayesian network classifier; DoS attacks; KDD Cup 99 dataset;U2R attacks; association rule mining; classified DoS equally; cyber attackers; cyber situation; cyber situation awareness; cyber threats; denial of service attacks; genetic algorithm; modified risk matrix criteria; network environment; network security; network traffic analysis; risk analysis; user to root attacks; Bayes methods; Intrusion detection; Risk management; Telecommunication traffic; Uncertainty; Bayesian approach; Cyber Situation Awareness; KDD Cup'99; Risk matrix (ID#: 15-6476)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7166119&isnumber=7166109
Timonen, J., “Improving Situational Awareness of Cyber Physical Systems Based on Operator's Goals,” in Cyber Situational Awareness, Data Analytics and Assessment (CyberSA), 2015 International Conference on, vol., no., pp. 1-6, 8-9 June 2015. doi:10.1109/CyberSA.2015.7166121
Abstract: This paper focuses on discovering the key areas of Situational Awareness (SA) and Common Operational Picture (COP) in two different environments: the monitoring room and dismounted forces operations in urban areas. The research is based on scientific publications and on two implemented environments. In urban area warfare, the Mobile Urban Area Situational Awareness System is used to evaluate the requirements and usage of dismounted troops. The monitoring room is studied using the Situational Awareness of Critical Infrastructure and Networks System. These empirical environments were implemented during research projects at the Finnish National Defence University. The paper presents a model combining the joint model of laboratories, Endsley's model of SA and the results of goal-driven task analysis for creating a service-based architecture for defining and sharing COP. The main SA model used is Endsley's level model. It has been supplemented with cyber-related perspectives and fits the selected environments well, allowing techniques that can be used to measure the SA level and define the actor's most important goals.
Keywords: military computing; COP; Endsley's level model; SA; common operational picture; critical infrastructure; cyber physical systems; cyber-related perspectives; dismounted forces operations; dismounted troops; goal-driven task analysis; mobile urban area situational awareness system; monitoring room; networks system; requirement evaluation; scientific publications; service-based architecture; urban area warfare; Analytical models; Command and control systems; Computational modeling; Decision making; Monitoring; Stress; Urban areas; Common Operational Picture; Cyber Physical Systems; Situational Awareness; dismounted; operator (ID#: 15-6477)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7166121&isnumber=7166109
Onwubiko, C., “Cyber Security Operations Centre: Security Monitoring for Protecting Business and Supporting Cyber Defense Strategy,” in Cyber Situational Awareness, Data Analytics and Assessment (CyberSA), 2015 International Conference on, vol., no., pp. 1-10, 8-9 June 2015. doi:10.1109/CyberSA.2015.7166125
Abstract: Cyber security operations centre (CSOC) is an essential business control aimed to protect ICT systems and support an organisation's Cyber Defense Strategy. Its overarching purpose is to ensure that incidents are identified and managed to resolution swiftly, and to maintain safe & secure business operations and services for the organisation. A CSOC framework is proposed comprising Log Collection, Analysis, Incident Response, Reporting, Personnel and Continuous Monitoring. Further, a Cyber Defense Strategy, supported by the CSOC framework, is discussed. Overlaid atop the strategy is the well-known Her Majesty's Government (HMG) Protective Monitoring Controls (PMCs). Finally, the difficulty and benefits of operating a CSOC are explained.
Keywords: government data processing; security of data; CSOC framework; HMG protective monitoring controls; Her Majestys Government; ICT systems; business control; business protection; cyber defense strategy support; cyber security operations centre; information and communications technology; security monitoring; Business; Computer crime; Monitoring; System-on-chip; Timing; Analysis; CSOC; CSOC Benefits & Challenges; CSOC Strategy; Correlation; Cyber Incident Response; Cyber Security Operations Centre; Cyber Situational Awareness; CyberSA; Log Source; Risk Management; SOC (ID#: 15-6478)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7166125&isnumber=7166109
Skopik, F.; Wurzenberger, M.; Settanni, G.; Fiedler, R., “Establishing National Cyber Situational Awareness Through Incident Information Clustering,” in Cyber Situational Awareness, Data Analytics and Assessment (CyberSA), 2015 International Conference on, vol., no., pp. 1-8, 8-9 June 2015. doi:10.1109/CyberSA.2015.7166126
Abstract: The number and type of threats to modern information and communication networks has increased massively in the recent years. Furthermore, the system complexity and interconnectedness has reached a level which makes it impossible to adequately protect networked systems with standard security solutions. There are simply too many unknown vulnerabilities, potential configuration mistakes and therefore enlarged attack surfaces and channels. A promising approach to better secure today's networked systems is information sharing about threats, vulnerabilities and indicators of compromise across organizations; and, in case something went wrong, to report incidents to national cyber security centers. These measures enable early warning systems, support risk management processes, and increase the overall situational awareness of organizations. Several cyber security directives around the world, such as the EU Network and Information Security Directive and the equivalent NIST Framework, demand specifically national cyber security centers and policies for organizations to report on incidents. However, effective tools to support the operation of such centers are rare. Typically, existing tools have been developed with the single organization as customer in mind. These tools are often not appropriate either for the large amounts of data or for the application use case at all. In this paper, we therefore introduce a novel incident clustering model and a system architecture along with a prototype implementation to establish situational awareness about the security of participating organizations. This is a vital prerequisite to plan further actions towards securing national infrastructure assets.
Keywords: business data processing; national security; organisational aspects; pattern clustering; security of data; software architecture; EU Network and Information Security Directive; NIST framework; attack channels; attack surfaces; cyber security directives; early warning systems; incident information clustering; information and communication networks; information sharing; national cyber security centers; national cyber situational awareness; national infrastructure assets; networked systems protection; organizations; risk management processes; standard security solutions; system architecture; system complexity; system interconnectedness; threats; Clustering algorithms; Computer security; Information management; Market research; Organizations; Standards organizations (ID#: 15-6479)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7166126&isnumber=7166109
Aggarwal, P.; Grover, A.; Singh, S.; Maqbool, Z.; Pammi, V.S.C.; Dutt, V., “Cyber Security: A Game-Theoretic Analysis of Defender and Attacker Strategies in Defacing-Website Games,” in Cyber Situational Awareness, Data Analytics and Assessment (CyberSA), 2015 International Conference on, vol., no., pp. 1-8, 8-9 June 2015.doi:10.1109/CyberSA.2015.7166127
Abstract: The rate at which cyber-attacks are increasing globally portrays a terrifying picture upfront. The main dynamics of such attacks could be studied in terms of the actions of attackers and defenders in a cyber-security game. However currently little research has taken place to study such interactions. In this paper we use behavioral game theory and try to investigate the role of certain actions taken by attackers and defenders in a simulated cyber-attack scenario of defacing a website. We choose a Reinforcement Learning (RL) model to represent a simulated attacker and a defender in a 2×4 cyber-security game where each of the 2 players could take up to 4 actions. A pair of model participants were computationally simulated across 1000 simulations where each pair played at most 30 rounds in the game. The goal of the attacker was to deface the website and the goal of the defender was to prevent the attacker from doing so. Our results show that the actions taken by both the attackers and defenders are a function of attention paid by these roles to their recently obtained outcomes. It was observed that if attacker pays more attention to recent outcomes then he is more likely to perform attack actions. We discuss the implication of our results on the evolution of dynamics between attackers and defenders in cyber-security games.
Keywords: Web sites; computer crime; computer games; game theory; learning (artificial intelligence);RL model; attacker strategies; attacks dynamics; behavioral game theory; cyber-attacks; cyber-security game; defacing Website games; defender strategies; game-theoretic analysis; reinforcement learning; Cognitive science; Computational modeling; Computer security; Cost function; Games; Probabilistic logic; attacker; cognitive modeling; cyber security; cyber-attacks; defender; reinforcement-learning model (ID#: 15-6480)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7166127&isnumber=7166109
Bjerkestrand, T.; Tsaptsinos, D.; Pfluegel, E., “An Evaluation of Feature Selection and Reduction Algorithms for Network IDS Data,” in Cyber Situational Awareness, Data Analytics and Assessment (CyberSA), 2015 International Conference on, vol., no., pp. 1-2, 8-9 June 2015. doi:10.1109/CyberSA.2015.7166129
Abstract: Intrusion detection is concerned with monitoring and analysing events occurring in a computer system in order to discover potential malicious activity. Data mining, which is part of the procedure of knowledge discovery in databases, is the process of analysing the collected data to find patterns or correlations. As the amount of data collected, store and processed only increases, so does the significance and importance of intrusion detection and data mining. A dataset that has been particularly exposed to research is the dataset used for the Third International Knowledge Discovery and Data Mining Tools competition, KDD99. The KDD99 dataset has been used to identify what data mining techniques relate to certain attack and employed to demonstrate that decision trees are more efficient than the Naïve Bayes model when it comes to detecting new attacks. When it comes to detecting network intrusions, the C4.5 algorithm performs better than SVM. The aim of our research is to evaluate and compare the usage of various feature selection and reduction algorithms against publicly available datasets. In this contribution, the focus is on feature selection and reduction algorithms. Three feature selection algorithms, consisting of an attribute evaluator and a test method, have been used. Initial results indicate that the performance of the classifier is unaffected by reducing the number of attributes.
Keywords: Bayes methods; data mining; decision trees; feature selection; security of data; C4.5 algorithm; KDD99 dataset; SVM; computer system; data mining technique; decision tree; feature selection; intrusion detection; naive Bayes model; network IDS data; network intrusion; potential malicious activity; reduction algorithm; third international knowledge discovery and data mining tools competition; Algorithm design and analysis; Classification algorithms; Data mining; Databases; Intrusion detection; Knowledge discovery; Training; KDD dataset; feature selection and reduction; intrusion detection; knowledge discovery (ID#: 15-6481)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7166129&isnumber=7166109
Evangelopoulou, M.; Johnson, C.W., “Empirical Framework for Situation Awareness Measurement Techniques in Network Defense,” in Cyber Situational Awareness, Data Analytics and Assessment (CyberSA), 2015 International Conference on, vol., no., pp. 1-4, 8-9 June 2015. doi:10.1109/CyberSA.2015.7166132
Abstract: This paper presents an empirical framework for implementing Situation Awareness Measurement Techniques in a Network Defense environment. Bearing in mind the rise of Cyber-crime and the importance of Cyber security, the role of the security analyst (or as this paper will refer to them, defenders) is critical. In this paper the role of Situation Awareness Measurement Techniques will be presented and explained briefly. Input from previous studies will be given and an empirical framework of how to measure Situation Awareness in a computing network environment will be offered in two main parts. The first one will include the networking infrastructure of the system. The second part will be focused on specifying which Situation Awareness Techniques are going to be used and which Situation Awareness critical questions need to be asked to improve future decision making in cyber-security. Finally, a discussion will take place concerning the proposed approach, the chosen methodology and further validation.
Keywords: computer crime; computer network security; decision making; computing network environment; cyber-crime; cybersecurity; decision making; network defense environment; situation awareness measurement techniques; Computer security; Decision making; Human factors; Measurement techniques; Monitoring; Unsolicited electronic mail; Cyber Security; CyberSA; Decision Making; Intrusion Detection; Network Defense; Situation Awareness; Situation Awareness Measurement Techniques
(ID#: 15-6482)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7166132&isnumber=7166109
Shovgenya, Y.; Skopik, F.; Theuerkauf, K., “On Demand for Situational Awareness for Preventing Attacks on the Smart Grid,” in Cyber Situational Awareness, Data Analytics and Assessment (CyberSA), 2015 International Conference on, vol., no., pp. 1-4, 8-9 June 2015. doi:10.1109/CyberSA.2015.7166133
Abstract: Renewable energy sources and widespread small-scale power generators change the structure of the power grid, where actual power consumers also temporarily become suppliers. Smart grids require continuous management of complex operations through utility providers, which leads to increasing interconnections and usage of ICT-enabled industrial control systems. Yet, often insufficiently implemented security mechanisms and the lack of appropriate monitoring solutions will make the smart grid vulnerable to malicious manipulations that may possibly result in severe power outages. Having a thorough understanding about the operational characteristics of smart grids, supported by clearly defined policies and processes, will be essential to establishing situational awareness, and thus, the first step for ensuring security and safety of the power supply.
Keywords: electric generators; electricity supply industry; industrial control; power consumption; power generation control; power generation reliability; power system interconnection; power system management; power system security; renewable energy sources; smart power grids; ICT-enabled industrial control system; actual power consumer; implemented security mechanism; power supply safety; power supply security; renewable energy source; situational awareness; small-scale power generator; smart power grid; Europe; Generators; Power generation; Renewable energy sources; Security; Smart grids; Smart meters; industrial control systems; situational awareness; smart generator; smart grid (ID#: 15-6483)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7166133&isnumber=7166109
Adenusi, D.; Alese, B.K; Kuboye, B.M.; Thompson, A.F.-B., “Development of Cyber Situation Awareness Model,” in Cyber Situational Awareness, Data Analytics and Assessment (CyberSA), 2015 International Conference on, vol., no., pp. 1-11, 8-9 June 2015. doi:10.1109/CyberSA.2015.7166135
Abstract: This study designed and simulated cyber situation awareness model for gaining experience of cyberspace condition. This was with a view to timely detecting anomalous activities and taking proactive decision safeguard the cyberspace. The situation awareness model was modelled using Artificial Intelligence (AI) technique. The cyber situation perception sub-model of the situation awareness model was modelled using Artificial Neural Networks (ANN). The comprehension and projection submodels of the situation awareness model were modelled using Rule-Based Reasoning (RBR) techniques. The cyber situation perception sub-model was simulated in MATLAB 7.0 using standard intrusion dataset of KDD'99. The cyber situation perception sub-model was evaluated for threats detection accuracy using precision, recall and overall accuracy metrics. The simulation result obtained for the performance metrics showed that the cyber-situation sub-model of the cybersituation model better with increase in number of training data records. The cyber situation model designed was able to meet its overall goal of assisting network administrators to gain experience of cyberspace condition. The model was capable of sensing the cyberspace condition, perform analysis based on the sensed condition and predicting the near future condition of the cyberspace.
Keywords: artificial intelligence; inference mechanisms; knowledge based systems; mathematics computing; neural nets; security of data; AI technique; ANN; Matlab 7.0; RBR techniques; anomalous activities detection; artificial neural networks; cyber situation awareness model; cyberspace condition; proactive decision safeguard; rule-based reasoning; training data records; Artificial neural networks; Computational modeling; Computer security; Cyberspace; Data models; Intrusion detection; Mathematical model; Artificial Intelligence; Awareness; cyber-situation; cybersecurity; cyberspace (ID#: 15-6484)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7166135&isnumber=7166109
Laing, C.; Vickers, P., “Context Informed Intelligent Information Infrastructures for Better Situational Awareness,” in Cyber Situational Awareness, Data Analytics and Assessment (CyberSA), 2015 International Conference on, vol., no., pp. 1-7, 8-9 June 2015. doi:10.1109/CyberSA.2015.7166136
Abstract: In this multi-disciplinary project, we intend to explore the advantages of an information fusion system in which the infrastructure finds new ways to reflect upon its own state and new ways to express this state that provides a good fit to human communication and cognition processes. This interplay should then generate a better and more responsive humancomputer symbiosis. The outcomes of this project will help to develop context and content aware networks that are better able to extract meaning and understanding from network data and behaviour.
Keywords: cognition; human computer interaction; information networks; knowledge based systems; sensor fusion; ubiquitous computing; cognition process; context informed intelligent information infrastructures; human communication; human-computer symbiosis; information fusion system; multidisciplinary project; situational awareness; Computers; Context; Monitoring; Real-time systems; Sonification; System-on-chip; Telecommunication traffic; context informed; information infrastructures; situational awareness (ID#: 15-6485)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7166136&isnumber=7166109
Nasir, M.A.; Nefti-Meziani, S.; Sultan, S.; Manzoor, U., “Potential Cyber-Attacks Against Global Oil Supply Chain,” in Cyber Situational Awareness, Data Analytics and Assessment (CyberSA), 2015 International Conference on, vol., no., pp. 1-7, 8-9 June 2015. doi:10.1109/CyberSA.2015.7166137
Abstract: The energy sector has been actively looking into cyber risk assessment at a global level, as it has a ripple effect; risk taken at one step in supply chain has an impact on all the other nodes. Cyber-attacks not only hinder functional operations in an organization but also waves damaging effects to the reputation and confidence among shareholders resulting in financial losses. Organizations that are open to the idea of protecting their assets and information flow and are equipped; enough to respond quickly to any cyber incident are the ones who prevail longer in global market. As a contribution we put forward a modular plan to mitigate or reduce cyber risks in global supply chain by identifying potential cyber threats at each step and identifying their immediate countermeasures.
Keywords: globalisation; organisational aspects; petroleum industry; risk management; security of data; supply chain management; cyber incident; cyber risk assessment; cyber-attack; damaging effect; energy sector; financial losses; global market; global oil supply chain; global supply chain; information flow; organization; ripple effect; Companies; Computer hacking; Information management; Supply chains; Temperature sensors; cyber-attacks; cyber-attacks countermeasures; oil supply chain; threats to energy sector (ID#: 15-6486)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7166137&isnumber=7166109
Dahri, K.; Rajput, S.; Memon, S.; Das Dhomeja, L., “Smart Activities Monitoring System (SAMS) for Security Applications,” in Cyber Situational Awareness, Data Analytics and Assessment (CyberSA), 2015 International Conference on, vol., no., pp.1-5, 8-9 June 2015. doi:10.1109/CyberSA.2015.7166138
Abstract: In this paper, an android based SAMS (Smart Activities Monitoring System) application for smart phone is proposed. This application is developed with the aim of increasing the national security in Pakistan. In last decade, various incidents including militant attacks and ransom-demands have been reported in which cell phones played a central role in communication between the culprits. The tracking of these criminals is very important and the government needs to adopt technologies to track mobile phones if they are being used for dangerous activities. In this paper, an android based application is presented which is designed and tested to track a suspect without his/her attention. This application tracks a smartphone by obtaining its current location and monitors a suspect remotely by retrieving information such as call logs, message logs etc. It also detects the face of the suspect and covertly captures the picture using cell phone camera and then sends it via multiple messages. Moreover, the monitoring user can also make calls to the phone which the culprit is using in stealth mode to hear the conversation happening in surroundings of the user without the knowledge of suspect.
Keywords: law administration; mobile computing; police data processing; security; smart phones; Android based application; SAMS; criminal activity; law enforcement agency; security application; smart activities monitoring system; smart phone; Cellular phones; Global Positioning System; Mobile communication; Monitoring; Servers; Smart phones; GPS location; security apps; smartphones; tracking (ID#: 15-6487)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7166138&isnumber=7166109
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