Biblio

Smartphones are a new type of mobile devices that users can install additional mobile software easily. In the almost all smartphone applications, client-server model is used because end-to-end communication is prevented by NAT routers. Recently, some smartphone applications provide real time services such as voice and video communication, online games etc. In these applications, end-to-end communication is suitable to reduce transmission delay and achieve efficient network usage. Also, IP mobility and security are important matters. However, the conventional IP mobility mechanisms are not suitable for these applications because most mechanisms are assumed to be installed in OS kernel. We have developed a novel IP mobility mechanism called NTMobile (Network Traversal with Mobility). NTMobile supports end-to-end IP mobility in IPv4 and IPv6 networks, however, it is assumed to be installed in Linux kernel as with other technologies. In this paper, we propose a new type of end-to-end mobility platform that provides end-to-end communication, mobility, and also secure data exchange functions in the application layer for smartphone applications. In the platform, we use NTMobile, which is ported as the application program. Then, we extend NTMobile to be suitable for smartphone devices and to provide secure data exchange. Client applications can achieve secure end-to-end communication and secure data exchange by sharing an encryption key between clients. Users also enjoy IP mobility which is the main function of NTMobile in each application. Finally, we confirmed that the developed module can work on Android system and iOS system.
 

Single sign-on (SSO) is an identity management technique that provides users the ability to use multiple Web services with one set of credentials. However, when the authentication server is down or unavailable, users cannot access Web services, even if the services are operating normally. Therefore, enabling continuous use is important in single sign on. In this paper, we present security framework to overcome credential problems of accessing multiple web application. We explain system functionality with authorization and Authentication. We consider these methods from the viewpoint of continuity, security and efficiency makes the framework highly secure.

This paper presents the relative merits of IR and microwave sensor technology and their combination with wireless camera for the development of a wall mounted wireless intrusion detection system and explain the phases by which the intrusion information are collected and sent to the central control station using wireless mesh network for analysis and processing the collected data. These days every protected zone is facing numerous security threats like trespassing or damaging of important equipments and a lot more. Unwanted intrusion has turned out to be a growing problem which has paved the way for a newer technology which detects intrusion accurately. Almost all organizations have their own conventional arrangement of protecting their zones by constructing high wall, wire fencing, power fencing or employing guard for manual observation. In case of large areas, manually observing the perimeter is not a viable option. To solve this type of problem we have developed a wall-mounted wireless fencing system. In this project I took the responsibility of studying how the different units could be collaborated and how the data collected from them could be further processed with the help of software, which was developed by me. The Intrusion detection system constitutes an important field of application for IR and microwave based wireless sensor network. A state of the art wall-mounted wireless intrusion detection system will detect intrusion automatically, through multi-level detection mechanism (IR, microwave, active RFID & camera) and will generate multi-level alert (buzzer, images, segment illumination, SMS, E-Mail) to notify security officers, owners and also illuminate the particular segment where the intrusion has happened. This system will enable the authority to quickly handle the emergency through identification of the area of incident at once and to take action quickly. IR based perimeter protection is a proven technology. However IR-based intrusion detection system is not a full-proof solution since (1) IR may fail in foggy or dusty weather condition & hence it may generate false alarm. Therefore we amalgamate this technology with Microwave based intrusion detection which can work satisfactorily in foggy weather. Also another significant arena of our proposed system is the Camera-based intrusion detection. Some industries require this feature to capture the snap-shots of the affected location instantly as the intrusion happens. The Intrusion information data are transmitted wirelessly to the control station via multi hop routing (using active RFID or IEEE 802.15.4 protocol). The Control station will receive intrusion information at real time and analyze the data with the help of the Intrusion software. It then sends SMS to the predefined numbers of the respective authority through GSM modem attached with the control station engine.

By enabling a direct comparison of different security solutions with respect to their relative effectiveness, a network security metric may provide quantifiable evidences to assist security practitioners in securing computer networks. However, research on security metrics has been hindered by difficulties in handling zero-day attacks exploiting unknown vulnerabilities. In fact, the security risk of unknown vulnerabilities has been considered as something unmeasurable due to the less predictable nature of software flaws. This causes a major difficulty to security metrics, because a more secure configuration would be of little value if it were equally susceptible to zero-day attacks. In this paper, we propose a novel security metric, k-zero day safety, to address this issue. Instead of attempting to rank unknown vulnerabilities, our metric counts how many such vulnerabilities would be required for compromising network assets; a larger count implies more security because the likelihood of having more unknown vulnerabilities available, applicable, and exploitable all at the same time will be significantly lower. We formally define the metric, analyze the complexity of computing the metric, devise heuristic algorithms for intractable cases, and finally demonstrate through case studies that applying the metric to existing network security practices may generate actionable knowledge.

In this paper, we consider the impact of a weaker model of eventual consistency on distributed multi-player games. This model is suitable for networks in which hosts can leave and join at anytime, e.g., in an intermittently connected environment. Such a consistency model is provided by the Secure Infrastructure for Networked Systems (SINS) [24], a reliable middleware framework. SINS allows agents to communicate asynchronously through a distributed transactional key-value store using anonymous publish-subscribe. It uses Lamport's Paxos protocol [17] to replicate state. We consider a multi-player maze game as example to illustrate our consistency model and the impact of network losses/delays therein. The framework based on SINS presented herein provides a vehicle for studying the effect of human elements participating in collaborative simulation of a physical world as in war games.

Recently, cloud computing has been spotlighted as a new paradigm of database management system. In this environment, databases are outsourced and deployed on a service provider in order to reduce cost for data storage and maintenance. However, the service provider might be untrusted so that the two issues of data security, including data confidentiality and query result integrity, become major concerns for users. Existing bucket-based data authentication methods have problem that the original spatial data distribution can be disclosed from data authentication index due to the unsophisticated data grouping strategies. In addition, the transmission overhead of verification object is high. In this paper, we propose a privacy-aware query authentication which guarantees data confidentiality and query result integrity for users. A periodic function-based data grouping scheme is designed to privately partition a spatial database into small groups for generating a signature of each group. The group signature is used to check the correctness and completeness of outsourced data when answering a range query to users. Through performance evaluation, it is shown that proposed method outperforms the existing method in terms of range query processing time up to 3 times.

Recently, cloud computing has been spotlighted as a new paradigm of database management system. In this environment, databases are outsourced and deployed on a service provider in order to reduce cost for data storage and maintenance. However, the service provider might be untrusted so that the two issues of data security, including data confidentiality and query result integrity, become major concerns for users. Existing bucket-based data authentication methods have problem that the original spatial data distribution can be disclosed from data authentication index due to the unsophisticated data grouping strategies. In addition, the transmission overhead of verification object is high. In this paper, we propose a privacy-aware query authentication which guarantees data confidentiality and query result integrity for users. A periodic function-based data grouping scheme is designed to privately partition a spatial database into small groups for generating a signature of each group. The group signature is used to check the correctness and completeness of outsourced data when answering a range query to users. Through performance evaluation, it is shown that proposed method outperforms the existing method in terms of range query processing time up to 3 times.

Recently, cloud computing has been spotlighted as a new paradigm of database management system. In this environment, databases are outsourced and deployed on a service provider in order to reduce cost for data storage and maintenance. However, the service provider might be untrusted so that the two issues of data security, including data confidentiality and query result integrity, become major concerns for users. Existing bucket-based data authentication methods have problem that the original spatial data distribution can be disclosed from data authentication index due to the unsophisticated data grouping strategies. In addition, the transmission overhead of verification object is high. In this paper, we propose a privacy-aware query authentication which guarantees data confidentiality and query result integrity for users. A periodic function-based data grouping scheme is designed to privately partition a spatial database into small groups for generating a signature of each group. The group signature is used to check the correctness and completeness of outsourced data when answering a range query to users. Through performance evaluation, it is shown that proposed method outperforms the existing method in terms of range query processing time up to 3 times.

This paper proposes a novel wireless MAC-layer approach towards achieving channel access anonymity. Nodes autonomously select periodic TDMA-like time-slots for channel access by employing a novel channel sensing strategy, and they do so without explicitly sharing any identity information with other nodes in the network. An add-on hardware module for the proposed channel sensing has been developed and the proposed protocol has been implemented in Tinyos-2.x. Extensive evaluation has been done on a test-bed consisting of Mica2 hardware, where we have studied the protocol's functionality and convergence characteristics. The functionality results collected at a sniffer node using RSSI traces validate the syntax and semantics of the protocol. Experimentally evaluated convergence characteristics from the Tinyos test-bed were also found to be satisfactory.

Application domains in which early performance evaluation is needed are becoming more complex. In addition to traditional measures of complexity due, for example, to the number of components, their interactions, complicated control coordination and schemes, emerging applications may require adaptive response and reconfiguration the impact of externally observable (security) parameters. In this paper we introduce an approach for effective modeling and analysis of performance and security tradeoffs. The approach identifies a suitable allocation of resources that meet performance requirements, while maximizing measurable security effects. We demonstrate this approach through the analysis of performance sensitivity of a Border Inspection Management System (BIMS) with changing security mechanisms (e.g. biometric system parameters for passenger identification). The final result is a model-based approach that allows us to take decisions about BIMS performance and security mechanisms on the basis of rates of traveler arrivals and traveler identification security guarantees. We describe the experience gained when applying this approach to daily flight arrival schedule of a real airport.

To deliver sample estimates provided with the necessary probability foundation to permit generalization from the sample data subset to the whole target population being sampled, probability sampling strategies are required to satisfy three necessary not sufficient conditions: 1) All inclusion probabilities be greater than zero in the target population to be sampled. If some sampling units have an inclusion probability of zero, then a map accuracy assessment does not represent the entire target region depicted in the map to be assessed. 2) The inclusion probabilities must be: a) knowable for nonsampled units and b) known for those units selected in the sample: since the inclusion probability determines the weight attached to each sampling unit in the accuracy estimation formulas, if the inclusion probabilities are unknown, so are the estimation weights. This original work presents a novel (to the best of these authors' knowledge, the first) probability sampling protocol for quality assessment and comparison of thematic maps generated from spaceborne/airborne very high resolution images, where: 1) an original Categorical Variable Pair Similarity Index (proposed in two different formulations) is estimated as a fuzzy degree of match between a reference and a test semantic vocabulary, which may not coincide, and 2) both symbolic pixel-based thematic quality indicators (TQIs) and sub-symbolic object-based spatial quality indicators (SQIs) are estimated with a degree of uncertainty in measurement in compliance with the well-known Quality Assurance Framework for Earth Observation (QA4EO) guidelines. Like a decision-tree, any protocol (guidelines for best practice) comprises a set of rules, equivalent to structural knowledge, and an order of presentation of the rule set, known as procedural knowledge. The combination of these two levels of knowledge makes an original protocol worth more than the sum of its parts. The several degrees of novelty of the proposed probability sampling protocol are highlighted in this paper, at the levels of understanding of both structural and procedural knowledge, in comparison with related multi-disciplinary works selected from the existing literature. In the experimental session, the proposed protocol is tested for accuracy validation of preliminary classification maps automatically generated by the Satellite Image Automatic Mapper (SIAM™) software product from two WorldView-2 images and one QuickBird-2 image provided by DigitalGlobe for testing purposes. In these experiments, collected TQIs and SQIs are statistically valid, statistically significant, consistent across maps, and in agreement with theoretical expectations, visual (qualitative) evidence and quantitative quality indexes of operativeness (OQIs) claimed for SIAM™ by related papers. As a subsidiary conclusion, the statistically consistent and statistically significant accuracy validation of the SIAM™ pre-classification maps proposed in this contribution, together with OQIs claimed for SIAM™ by related works, make the operational (automatic, accurate, near real-time, robust, scalable) SIAM™ software product eligible for opening up new inter-disciplinary research and market opportunities in accordance with the visionary goal of the Global Earth Observation System of Systems initiative and the QA4EO international guidelines.

Homeland Security (HS) is a growing field of study in the U.S. today, generally covering risk management, terrorism studies, policy development, and other topics related to the broad field. Information security threats to both the public and private sectors are growing in intensity, frequency, and severity, and are a very real threat to the security of the nation. While there are many models for information security education at all levels of higher education, these programs are invariably offered as a technical course of study, these curricula are generally not well suited to HS students. As a result, information systems and cyber security principles are under represented in the typical HS program. The authors propose a course of study in cyber security designed to capitalize on the intellectual strengths of students in this discipline and that are consistent with the broad suite of professional needs in this discipline.

This paper addresses a robust methodology for developing a statistically sound, robust prognostic condition index and encapsulating this index as a series of highly accurate, transparent, human-readable rules. These rules can be used to further understand degradation phenomena and also provide transparency and trust for any underlying prognostic technique employed. A case study is presented on a wind turbine gearbox, utilising historical supervisory control and data acquisition (SCADA) data in conjunction with a physics of failure model. Training is performed without failure data, with the technique accurately identifying gearbox degradation and providing prognostic signatures up to 5 months before catastrophic failure occurred. A robust derivation of the Mahalanobis distance is employed to perform outlier analysis in the bivariate domain, enabling the rapid labelling of historical SCADA data on independent wind turbines. Following this, the RIPPER rule learner was utilised to extract transparent, human-readable rules from the labelled data. A mean classification accuracy of 95.98% of the autonomously derived condition was achieved on three independent test sets, with a mean kappa statistic of 93.96% reported. In total, 12 rules were extracted, with an independent domain expert providing critical analysis, two thirds of the rules were deemed to be intuitive in modelling fundamental degradation behaviour of the wind turbine gearbox.

The need for cyber security professionals continues to grow and education systems are responding in a variety of way. The US government has weighed in with two efforts, the NICE effort led by NIST and the CAE effort jointly led by NSA and DHS. Industry has unfilled needs and the CAE program is changing to meet both NICE and industry needs. This paper analyzes these efforts and examines several critical, yet unaddressed issues facing school programs as they adapt to new criteria and guidelines. Technical issues are easy to enumerate, yet it is the programmatic and student success factors that will define successful programs.

Decreasing the potential for catastrophic consequences poses a significant challenge for high-risk industries. Organizations are under many different pressures, and they are continuously trying to adapt to changing conditions and recover from disturbances and stresses that can arise from both normal operations and unexpected events. Reducing risks in complex systems therefore requires that organizations develop and enhance traits that increase resilience. Resilience provides a holistic approach to safety, emphasizing the creation of organizations and systems that are proactive, interactive, reactive, and adaptive. This approach relies on disciplines such as system safety and emergency management, but also requires that organizations develop indicators and ways of knowing when an emergency is imminent. A resilient organization must be adaptive, using hands-on activities and lessons learned efforts to better prepare it to respond to future disruptions. It is evident from the discussions of each of the traits of resilience, including their limitations, that there are no easy answers to reducing safety risks in complex systems. However, efforts to strengthen resilience may help organizations better address the challenges associated with the ever-increasing complexities of their systems.

Cyber-physical systems (CPS) can potentially benefit a wide array of applications and areas. Here, the authors look at some of the challenges surrounding CPS, and consider a feasible solution for creating a robust, secure, and cost-effective architecture.

Cloud computing brings in a lot of advantages for enterprise IT infrastructure; virtualization technology, which is the backbone of cloud, provides easy consolidation of resources, reduction of cost, space and management efforts. However, security of critical and private data is a major concern which still keeps back a lot of customers from switching over from their traditional in-house IT infrastructure to a cloud service. Existence of techniques to physically locate a virtual machine in the cloud, proliferation of software vulnerability exploits and cross-channel attacks in-between virtual machines, all of these together increases the risk of business data leaks and privacy losses. This work proposes a framework to mitigate such risks and engineer customer trust towards enterprise cloud computing. Everyday new vulnerabilities are being discovered even in well-engineered software products and the hacking techniques are getting sophisticated over time. In this scenario, absolute guarantee of security in enterprise wide information processing system seems a remote possibility; software systems in the cloud are vulnerable to security attacks. Practical solution for the security problems lies in well-engineered attack mitigation plan. At the positive side, cloud computing has a collective infrastructure which can be effectively used to mitigate the attacks if an appropriate defense framework is in place. We propose such an attack mitigation framework for the cloud. Software vulnerabilities in the cloud have different severities and different impacts on the security parameters (confidentiality, integrity, and availability). By using Markov model, we continuously monitor and quantify the risk of compromise in different security parameters (e.g.: change in the potential to compromise the data confidentiality). Whenever, there is a significant change in risk, our framework would facilitate the tenants to calculate the Mean Time to Security Failure (MTTSF) cloud and allow them to adopt a dynamic mitigation plan. This framework is an add-on security layer in the cloud resource manager and it could improve the customer trust on enterprise cloud solutions.

A frequent claim that has not been validated is that signature based network intrusion detection systems (SNIDS) cannot detect zero-day attacks. This paper studies this property by testing 356 severe attacks on the SNIDS Snort, configured with an old official rule set. Of these attacks, 183 attacks are zero-days' to the rule set and 173 attacks are theoretically known to it. The results from the study show that Snort clearly is able to detect zero-days' (a mean of 17% detection). The detection rate is however on overall greater for theoretically known attacks (a mean of 54% detection). The paper then investigates how the zero-days' are detected, how prone the corresponding signatures are to false alarms, and how easily they can be evaded. Analyses of these aspects suggest that a conservative estimate on zero-day detection by Snort is 8.2%.

Today in the world of globalization mobile communication is one of the fastest growing medium though which one sender can interact with other in short time. During the transmission of data from sender to receiver, size of data is important, since more data takes more time. But one of the limitations of sending data through mobile devices is limited use of bandwidth and number of packets transmitted. Also the security of these data is important. Hence various protocols are implemented which not only provides security to the data but also utilizes bandwidth. Here we proposed an efficient technique of sending SMS text using combination of compression and encryption. The data to be send is first encrypted using Elliptic curve Cryptographic technique, but encryption increases the size of the text data, hence compression is applied to this encrypted data so the data gets compressed and is send in short time. The Compression technique implemented here is an efficient one since it includes an algorithm which compresses the text by 99.9%, hence a great amount of bandwidth gets saved.The hybrid technique of Compression-Encryption of SMS text message is implemented for Android Operating Systems.

Contingency analysis is a critical activity in the context of the power infrastructure because it provides a guide for resiliency and enables the grid to continue operating even in the case of failure. In this paper, we augment this concept by introducing SOCCA, a cyber-physical security evaluation technique to plan not only for accidental contingencies but also for malicious compromises. SOCCA presents a new unified formalism to model the cyber-physical system including interconnections among cyber and physical components. The cyber-physical contingency ranking technique employed by SOCCA assesses the potential impacts of events. Contingencies are ranked according to their impact as well as attack complexity. The results are valuable in both cyber and physical domains. From a physical perspective, SOCCA scores power system contingencies based on cyber network configuration, whereas from a cyber perspective, control network vulnerabilities are ranked according to the underlying power system topology.

Contingency analysis is a critical activity in the context of the power infrastructure because it provides a guide for resiliency and enables the grid to continue operating even in the case of failure. In this paper, we augment this concept by introducing SOCCA, a cyber-physical security evaluation technique to plan not only for accidental contingencies but also for malicious compromises. SOCCA presents a new unified formalism to model the cyber-physical system including interconnections among cyber and physical components. The cyber-physical contingency ranking technique employed by SOCCA assesses the potential impacts of events. Contingencies are ranked according to their impact as well as attack complexity. The results are valuable in both cyber and physical domains. From a physical perspective, SOCCA scores power system contingencies based on cyber network configuration, whereas from a cyber perspective, control network vulnerabilities are ranked according to the underlying power system topology.
 

The objective of the paper is to propose a social network security management model for a multi-tenancy SaaS application using Unified Communications as a Service (UCaaS) approach. The earlier security management models do not cover the issues when data inadvertently get exposed to other users due to poor implementation of the access management processes. When a single virtual machine moves or dissolves in the network, many separate machines may bypass the security conditions that had been implemented for its neighbors which lead to vulnerability of the hosted services. When the services are multi-tenant, the issue becomes very critical due to lack of asynchronous asymmetric communications between virtual when more number of applications and users are added into the network creating big data issues and its identity. The TRAIN model for the security management using PC-FAST algorithm is proposed in order to detect and identify the communication errors between the hosted services.
 

A key challenge of future mobile communication research is to strike an attractive compromise between wireless network's area spectral efficiency and energy efficiency. This necessitates a clean-slate approach to wireless system design, embracing the rich body of existing knowledge, especially on multiple-input-multiple-ouput (MIMO) technologies. This motivates the proposal of an emerging wireless communications concept conceived for single-radio-frequency (RF) large-scale MIMO communications, which is termed as SM. The concept of SM has established itself as a beneficial transmission paradigm, subsuming numerous members of the MIMO system family. The research of SM has reached sufficient maturity to motivate its comparison to state-of-the-art MIMO communications, as well as to inspire its application to other emerging wireless systems such as relay-aided, cooperative, small-cell, optical wireless, and power-efficient communications. Furthermore, it has received sufficient research attention to be implemented in testbeds, and it holds the promise of stimulating further vigorous interdisciplinary research in the years to come. This tutorial paper is intended to offer a comprehensive state-of-the-art survey on SM-MIMO research, to provide a critical appraisal of its potential advantages, and to promote the discussion of its beneficial application areas and their research challenges leading to the analysis of the technological issues associated with the implementation of SM-MIMO. The paper is concluded with the description of the world's first experimental activities in this vibrant research field.
 

Principles of agile information systems development (ISD) have attracted the interest of practice as well as research. The goal of this literature review is to validate, update and extend previous reviews in terms of the general state of research on agile ISD. Besides including categories such as the employed research methods and data collection techniques, the importance of theory is highlighted by evaluating the theoretical foundations and contributions of former studies. Since agile ISD is rooted in the IS as well as software engineering discipline, important outlets of both disciplines are included in the search process, resulting in 482 investigated papers. The findings show that quantitative studies and the theoretical underpinnings of agile ISD are lacking. Extreme Programming is still the most researched agile ISD method, and more efforts on Scrum are needed. In consequence, multiple research gaps that need further research attention are identified.