Biblio

With the increase in signal's bandwidth, the conventional analog to digital converters (ADCs), operating on the basis of Shannon/Nyquist theorem, are forced to work at very high rates leading to low dynamic range and high power consumptions. This paper here tells about one Analog to Information converter developed based on compressive sensing techniques. The high sampling rates, which is the main drawback for ADCs, is being successfully reduced to 4 times lower than the conventional rates. The system is also accompanied with the advantage of low power dissipation.

Most of the detection approaches like Signature based, Anomaly based and Specification based are not able to analyze and detect all types of malware. Signature-based approach for malware detection has one major drawback that it cannot detect zero-day attacks. The fundamental limitation of anomaly based approach is its high false alarm rate. And specification-based detection often has difficulty to specify completely and accurately the entire set of valid behaviors a malware should exhibit. Modern malware developers try to avoid detection by using several techniques such as polymorphic, metamorphic and also some of the hiding techniques. In order to overcome these issues, we propose a new approach for malware analysis and detection that consist of the following twelve stages Inbound Scan, Inbound Attack, Spontaneous Attack, Client-Side Exploit, Egg Download, Device Infection, Local Reconnaissance, Network Surveillance, & Communications, Peer Coordination, Attack Preparation, and Malicious Outbound Propagation. These all stages will integrate together as interrelated process in our proposed approach. This approach had solved the limitations of all the three approaches by monitoring the behavioral activity of malware at each any every stage of life cycle and then finally it will give a report of the maliciousness of the files or software's.

Formal techniques provide exhaustive design verification, but computational margins have an important negative impact on its efficiency. Sequential equivalence checking is an effective approach, but traditionally it has been only applied between circuit descriptions with one-to-one correspondence for states. Applying it between RTL descriptions and high-level reference models requires removing signals, variables and states exclusive of the RTL description so as to comply with the state correspondence restriction. In this paper, we extend a previous formal methodology for RTL verification with high-level models, to check also the signals and protocol implemented in the RTL design. This protocol implementation is compared formally to a description captured from the specification. Thus, we can prove thoroughly the sequential behavior of a design under verification.
 

Android "Health-DR." is innovative idea for ambulatory appliances. In rapid developing technology, we are providing "Health-DR." application for the insurance agent, dispensary, patients, physician, annals management (security) for annals. So principally, the ample of record are maintain in to the hospitals. The application just needs to be installed in the customer site with IT environment. Main purpose of our application is to provide the healthy environment to the patient. Our cream focus is on the "Health-DR." application meet to the patient regiment. For the personal use of member, we provide authentication service strategy for "Health-DR." application. Prospective strategy includes: Professional Authentications (User Authentication) by doctor to the patient, actuary and dispensary. Remote access is available to the medical annals, doctor affability and patient affability. "Health-DR." provides expertness anytime and anywhere. The application is middleware to isolate the information from affability management, client discovery and transit of database. Annotations of records are kept in the bibliography. Mainly, this paper focuses on the conversion of E-Health application with flexible surroundings.
 

Due to the development of cloud computing and NoSQL database, more and more sensitive information are stored in NoSQL databases, which exposes quite a lot security vulnerabilities. This paper discusses security features of MongoDB database and proposes a transparent middleware implementation. The analysis of experiment results show that this transparent middleware can efficiently encrypt sensitive data specified by users on a dataset level. Existing application systems do not need too many modifications in order to apply this middleware.

This paper proposes a new network-based cyber intrusion detection system (NIDS) using multicast messages in substation automation systems (SASs). The proposed network-based intrusion detection system monitors anomalies and malicious activities of multicast messages based on IEC 61850, e.g., Generic Object Oriented Substation Event (GOOSE) and Sampled Value (SV). NIDS detects anomalies and intrusions that violate predefined security rules using a specification-based algorithm. The performance test has been conducted for different cyber intrusion scenarios (e.g., packet modification, replay and denial-of-service attacks) using a cyber security testbed. The IEEE 39-bus system model has been used for testing of the proposed intrusion detection method for simultaneous cyber attacks. The false negative ratio (FNR) is the number of misclassified abnormal packets divided by the total number of abnormal packets. The results demonstrate that the proposed NIDS achieves a low fault negative rate.
 

Secure group communication systems have become increasingly important for many emerging network applications. An efficient and robust group key management approach is indispensable to a secure group communication system. Motivated by the theory of hyper-sphere, this paper presents a new group key management approach with a group controller (GC). In our new design, a hyper-sphere is constructed for a group and each member in the group corresponds to a point on the hyper-sphere, which is called the member's private point. The GC computes the central point of the hyper-sphere, intuitively, whose “distance” from each member's private point is identical. The central point is published such that each member can compute a common group key, using a function by taking each member's private point and the central point of the hyper-sphere as the input. This approach is provably secure under the pseudo-random function (PRF) assumption. Compared with other similar schemes, by both theoretical analysis and experiments, our scheme (1) has significantly reduced memory and computation load for each group member; (2) can efficiently deal with massive membership change with only two re-keying messages, i.e., the central point of the hyper-sphere and a random number; and (3) is efficient and very scalable for large-size groups.

Data deduplication is a technique for eliminating duplicate copies of data, and has been widely used in cloud storage to reduce storage space and upload bandwidth. Promising as it is, an arising challenge is to perform secure deduplication in cloud storage. Although convergent encryption has been extensively adopted for secure deduplication, a critical issue of making convergent encryption practical is to efficiently and reliably manage a huge number of convergent keys. This paper makes the first attempt to formally address the problem of achieving efficient and reliable key management in secure deduplication. We first introduce a baseline approach in which each user holds an independent master key for encrypting the convergent keys and outsourcing them to the cloud. However, such a baseline key management scheme generates an enormous number of keys with the increasing number of users and requires users to dedicatedly protect the master keys. To this end, we propose Dekey , a new construction in which users do not need to manage any keys on their own but instead securely distribute the convergent key shares across multiple servers. Security analysis demonstrates that Dekey is secure in terms of the definitions specified in the proposed security model. As a proof of concept, we implement Dekey using the Ramp secret sharing scheme and demonstrate that Dekey incurs limited overhead in realistic environments.

In a converging world, where borders between countries are surpassed in the digital environment, it is necessary to develop systems that effectively replace the recognition “vis-a-vis” with digital means of recognizing and identifying entities and people. In this work we summarize the current standardization efforts in the area of digital identity management. We identify a number of open challenges that need to be addressed in the near future to ensure the interoperability and usability of digital identity management services in an efficient and privacy maintaining international framework. These challenges for standardization include: the management of identifiers for digital identities at the global level; attribute management including attribute format, structure, and assurance; procedures and protocols to link attributes to digital identities. Attention is drawn to key elements that should be considered in addressing these issues through standardization.

Hash functions, such as SHA (secure hash algorithm) and MD (message digest) families that are built upon Merkle-Damgard construction, suffer many attacks due to the iterative nature of block-by-block message processing. Chum and Zhang [4] proposed a new hash function construction that takes advantage of the randomize-then-combine technique, which was used in the incremental hash functions, to the iterative hash function. In this paper, we implement such hash construction in three ways distinguished by their corresponding padding methods. We conduct the experiment in parallel multi-threaded programming settings. The results show that the speed of proposed hash function is no worse than SHA1.
 

The migration from a vertical to horizontal business model has made it easier to introduce hardware Trojans and counterfeit electronic parts into the electronic component supply chain. Hardware Trojans are malicious modifications made to original IC designs that reduce system integrity (change functionality, leak private data, etc.). Counterfeit parts are often below specification and/or of substandard quality. The existence of Trojans and counterfeit parts creates risks for the life-critical systems and infrastructures that incorporate them including automotive, aerospace, military, and medical systems. In this tutorial, we will cover: (i) Background and motivation for hardware Trojan and counterfeit prevention/detection; (ii) Taxonomies related to both topics; (iii) Existing solutions; (iv) Open challenges; (v) New and unified solutions to address these challenges.
 

Skype has been a typical choice for providing VoIP service nowadays and is well-known for its broad range of features, including voice-calls, instant messaging, file transfer and video conferencing, etc. Considering its wide application, from the viewpoint of ISPs, it is essential to identify Skype flows and thus optimize network performance and forecast future needs. However, in general, a host is likely to run multiple network applications simultaneously, which makes it much harder to classify each and every Skype flow from mixed traffic exactly. Especially, current techniques usually focus on host-level identification and do not have the ability to identify Skype traffic at the flow-level. In this paper, we first reveal the unique sequence signatures of Skype UDP flows and then implement a practical online system named SkyTracer for precise Skype traffic identification. To the best of our knowledge, this is the first time to utilize the strong sequence signatures to carry out early identification of Skype traffic. The experimental results show that SkyTracer can achieve very high accuracy at fine-grained level in identifying Skype traffic.

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.

Due to cyber security is an important issue of the cloud computing. Insider threat becomes more and more important for cyber security, it is also much more complex issue. But till now, there is no equivalent to a vulnerability scanner for insider threat. We survey and discuss the history of research on insider threat analysis to know system dynamics is the best method to mitigate insider threat from people, process, and technology. In the paper, we present a system dynamics method to model insider threat. We suggest some concludes for future research who are interested in insider threat issue The study.

The Domain Name System (DNS) is widely seen as a vital protocol of the modern Internet. For example, popular services like load balancers and Content Delivery Networks heavily rely on DNS. Because of its important role, DNS is also a desirable target for malicious activities such as spamming, phishing, and botnets. To protect networks against these attacks, a number of DNS-based security approaches have been proposed. The key insight of our study is to measure the effectiveness of security approaches that rely on DNS in large-scale networks. For this purpose, we answer the following questions, How often is DNS used? Are most of the Internet flows established after contacting DNS? In this study, we collected data from the University of Auckland campus network with more than 33,000 Internet users and processed it to find out how DNS is being used. Moreover, we studied the flows that were established with and without contacting DNS. Our results show that less than 5 percent of the observed flows use DNS. Therefore, we argue that those security approaches that solely depend on DNS are not sufficient to protect large-scale networks.

To improve comprehensive performance of denoising range images, an impulsive noise (IN) denoising method with variable windows is proposed in this paper. Founded on several discriminant criteria, the principles of dropout IN detection and outlier IN detection are provided. Subsequently, a nearest non-IN neighbors searching process and an Index Distance Weighted Mean filter is combined for IN denoising. As key factors of adapatablity of the proposed denoising method, the sizes of two windows for outlier INs detection and INs denoising are investigated. Originated from a theoretical model of invader occlusion, variable window is presented for adapting window size to dynamic environment of each point, accompanying with practical criteria of adaptive variable window size determination. Experiments on real range images of multi-line surface are proceeded with evaluations in terms of computational complexity and quality assessment with comparison analysis among a few other popular methods. It is indicated that the proposed method can detect the impulsive noises with high accuracy, meanwhile, denoise them with strong adaptability with the help of variable window.
 

The United States, including the Department of Defense, relies heavily on information systems and networking technologies to efficiently conduct a wide variety of missions across the globe. With the ever-increasing rate of cyber attacks, this dependency places the nation at risk of a loss of confidentiality, integrity, and availability of its critical information resources; degrading its ability to complete the mission. In this paper, we introduce the operational data classes for establishing situational awareness in cyberspace. A system effectively using our key information components will be able to provide the nation's leadership timely and accurate information to gain an understanding of the operational cyber environment to enable strategic, operational, and tactical decision-making. In doing so, we present, define and provide examples of our key classes of operational data for cyber situational awareness and present a hypothetical case study demonstrating how they must be consolidated to provide a clear and relevant picture to a commander. In addition, current organizational and technical challenges are discussed, and areas for future research are addressed.
 

In order to deal with shortcomings of security management systems, this work proposes a methodology based on agents paradigm for cybersecurity risk management. In this approach a system is decomposed in agents that may be used to attain goals established by attackers. Threats to business are achieved by attacker's goals in service and deployment agents. To support a proactive behavior, sensors linked to security mechanisms are analyzed accordingly with a model for Situational Awareness(SA)[4].
 

The Communities vary from country to country. There are civil societies and rural communities, which also differ in terms of geography climate and economy. This shows that the use of social networks vary from region to region depending on the demographics of the communities. So, in this paper, we researched the most important problems of the Social Network, as well as the risk which is based on the human elements. We raised the problems of social networks in the transformation of societies to another affected by the global economy. The social networking integration needs to strengthen social ties that lead to the existence of these problems. For this we focused on the Internet security risks over the social networks. And study on Risk Management, and then look at resolving various problems that occur from the use of social networks.
 

Educational software systems have an increasingly significant presence in engineering sciences. They aim to improve students' attitudes and knowledge acquisition typically through visual representation and simulation of complex algorithms and mechanisms or hardware systems that are often not available to the educational institutions. This paper presents a novel software system for CryptOgraphic ALgorithm visuAl representation (COALA), which was developed to support a Data Security course at the School of Electrical Engineering, University of Belgrade. The system allows users to follow the execution of several complex algorithms (DES, AES, RSA, and Diffie-Hellman) on real world examples in a step by step detailed view with the possibility of forward and backward navigation. Benefits of the COALA system for students are observed through the increase of the percentage of students who passed the exam and the average grade on the exams during one school year.
 

This paper proposed a MIMO cross-layer precoding secure communications via pattern controlled by higher layer cryptography. By contrast to physical layer security system, the proposed scheme could enhance the security in adverse situations where the physical layer security hardly to be deal with. Two One typical situation is considered. One is that the attackers have the ideal CSI and another is eavesdropper's channel are highly correlated to legitimate channel. Our scheme integrates the upper layer with physical layer secure together to gaurantee the security in real communication system. Extensive theoretical analysis and simulations are conducted to demonstrate its effectiveness. The proposed method is feasible to spread in many other communicate scenarios.
 

Cloud computing is an application and set of services given through the internet. However it is an emerging technology for shared infrastructure but it lacks with an access rights and security mechanism. As it lacks security issues for the cloud users our system focuses only on the security provided through the token management system. It is based on the internet where computing is done through the virtual shared servers for providing infrastructure, software, platform and security as a services. In which security plays an important role in the cloud service. Hence, this security has been given with three types of services such as mutual authentication, directory services, token granting for the resources. Since, existing token issuing mechanism does not provide scalability to large data sets and also increases memory overhead between the client and the server. Hence, our proposed work focuses on providing tokens to the users, which addresses the problem of scalability and memory overhead. The proposed framework of token management system monitors the entire operations of the cloud and there by managing the entire cloud infrastructure. Our model comes under the new category of cloud model known as "Security as a Service". This paper provides the security framework as an architectural model to verify user authorization and data correctness of the resource stored thereby provides guarantee to the data owner for their resource stored into the cloud This framework also describes about the storage of token in a secured manner and it also facilitates search and usage of tokens for auditing purpose and supervision of the users.
 

In recent years, Attribute Based Access Control (ABAC) has evolved as the preferred logical access control methodology in the Department of Defense and Intelligence Community, as well as many other agencies across the federal government. Gartner recently predicted that “by 2020, 70% of enterprises will use attribute-based access control (ABAC) as the dominant mechanism to protect critical assets, up from less that 5% today.” A definition and introduction to ABAC can be found in NIST Special Publication 800-162, Guide to Attribute Based Access Control (ABAC) Definition and Considerations and Intelligence Community Policy Guidance (ICPG) 500.2, Attribute-Based Authorization and Access Management. Within ABAC, attributes are used to make critical access control decisions, yet standards for attribute assurance have just started to be researched and documented. This presentation outlines factors influencing attributes that an authoritative body must address when standardizing attribute assurance and proposes some notional implementation suggestions for consideration. Attribute Assurance brings a level of confidence to attributes that is similar to levels of assurance for authentication (e.g., guidelines specified in NIST SP 800-63 and OMB M-04-04). There are three principal areas of interest when considering factors related to Attribute Assurance. Accuracy establishes the policy and technical underpinnings for semantically and syntactically correct descriptions of Subjects, Objects, or Environmental conditions. Interoperability considers different standards and protocols used for secure sharing of attributes between systems in order to avoid compromising the integrity and confidentiality of the attributes or exposing vulnerabilities in provider or relying systems or entities. Availability ensures that the update and retrieval of attributes satisfy the application to which the ABAC system is applied. In addition, the security and backup capability of attribute repositories need to be considered. Similar to a Level of Assurance (LOA), a Level of Attribute Assurance (LOAA) assures a relying party that the attribute value received from an Attribute Provider (AP) is accurately associated with the subject, resource, or environmental condition to which it applies. An Attribute Provider (AP) is any person or system that provides subject, object (or resource), or environmental attributes to relying parties regardless of transmission method. The AP may be the original, authoritative source (e.g., an Applicant). The AP may also receive information from an authoritative source for repacking or store-and-forward (e.g., an employee database) to relying parties or they may derive the attributes from formulas (e.g., a credit score). Regardless of the source of the AP's attributes, the same standards should apply to determining the LOAA. As ABAC is implemented throughout government, attribute assurance will be a critical, limiting factor in its acceptance. With this presentation, we hope to encourage dialog between attribute relying parties, attribute providers, and federal agencies that will be defining standards for ABAC in the immediate future.
 

A small battery driven bio-patch, attached to the human body and monitoring various vital signals such as temperature, humidity, heart activity, muscle and brain activity, is an example of a highly resource constrained system, that has the demanding task to assess correctly the state of the monitored subject (healthy, normal, weak, ill, improving, worsening, etc.), and its own capabilities (attached to subject, working sensors, sufficient energy supply, etc.). These systems and many other systems would benefit from a sense of itself and its environment to improve robustness and sensibility of its behavior. Although we can get inspiration from fields like neuroscience, robotics, AI, and control theory, the tight resource and energy constraints imply that we have to understand accurately what technique leads to a particular feature of awareness, how it contributes to improved behavior, and how it can be implemented cost-efficiently in hardware or software. We review the concepts of environment- and self-models, semantic interpretation, semantic attribution, history, goals and expectations, prediction, and self-inspection, how they contribute to awareness and self-awareness, and how they contribute to improved robustness and sensibility of behavior.

Variable Precision Rough Set (VPRS) model is one of the most important extensions of the Classical Rough Set (RS) theory. It employs a majority inclusion relation mechanism in order to make the Classical RS model become more fault tolerant, and therefore the generalization of the model is improved. This paper can be viewed as an extension of previous investigations on attribution reduction problem in VPRS model. In our investigation, we illustrated with examples that the previously proposed reduct definitions may spoil the hidden classification ability of a knowledge system by ignoring certian essential attributes in some circumstances. Consequently, by proposing a new β-consistent notion, we analyze the relationship between the structures of Decision Table (DT) and different definitions of reduct in VPRS model. Then we give a new notion of β-complement reduct that can avoid the defects of reduct notions defined in previous literatures. We also supply the method to obtain the β- complement reduct using a decision table splitting algorithm, and finally demonstrate the feasibility of our approach with sample instances.