Biblio

The term Cloud Computing is not something that appeared overnight, it may come from the time when computer system remotely accessed the applications and services. Cloud computing is Ubiquitous technology and receiving a huge attention in the scientific and industrial community. Cloud computing is ubiquitous, next generation's in-formation technology architecture which offers on-demand access to the network. It is dynamic, virtualized, scalable and pay per use model over internet. In a cloud computing environment, a cloud service provider offers “house of resources” includes applications, data, runtime, middleware, operating system, virtualization, servers, data storage and sharing and networking and tries to take up most of the overhead of client. Cloud computing offers lots of benefits, but the journey of the cloud is not very easy. It has several pitfalls along the road because most of the services are outsourced to third parties with added enough level of risk. Cloud computing is suffering from several issues and one of the most significant is Security, privacy, service availability, confidentiality, integrity, authentication, and compliance. Security is a shared responsibility of both client and service provider and we believe security must be information centric, adaptive, proactive and built in. Cloud computing and its security are emerging study area nowadays. In this paper, we are discussing about data security in cloud at the service provider end and proposing a network storage architecture of data which make sure availability, reliability, scalability and security.

This paper presents a middleware solution to secure data and network in the e-healthcare system. The e-Healthcare Systems are a primary concern due to the easiest deployment area accessibility of the sensor devices. Furthermore, they are often interacting closely in cooperation with the physical environment and the surrounding people, where such exposure increases security vulnerabilities in cases of improperly managed security of the information sharing among different healthcare organizations. Hence, healthcare-specific security standards such as authentication, data integrity, system security and internet security are used to ensure security and privacy of patients' information. This paper discusses security threats on e-Healthcare Systems where an attacker can access both data and network using masquerade attack Moreover, an efficient and cost effective approach middleware solution is discussed for the delivery of secure services.

With the spectacular increase in online activities like e-transactions, security and privacy issues are at the peak with respect to their significance. Large numbers of database security breaches are occurring at a very high rate on daily basis. So, there is a crucial need in the field of database forensics to make several redundant copies of sensitive data found in database server artifacts, audit logs, cache, table storage etc. for analysis purposes. Large volume of metadata is available in database infrastructure for investigation purposes but most of the effort lies in the retrieval and analysis of that information from computing systems. Thus, in this paper we mainly focus on the significance of metadata in database forensics. We proposed a system here to perform forensics analysis of database by generating its metadata file independent of the DBMS system used. We also aim to generate the digital evidence against criminals for presenting it in the court of law in the form of who, when, why, what, how and where did the fraudulent transaction occur. Thus, we are presenting a system to detect major database attacks as well as anti-forensics attacks by developing an open source database forensics tool. Eventually, we are pointing out the challenges in the field of forensics and how these challenges can be used as opportunities to stimulate the areas of database forensics.

The Internet of Things (IoT) becomes reality. But its restrictions become obvious as we try to connect solutions of different vendors and communities. Apart from communication protocols appropriate identity management mechanisms are crucial for a growing IoT. The recently founded Identities of Things Discussion Group within Kantara Initiative will work on open issues and solutions to manage “Identities of Things” as an enabler for a fast-growing ecosystem.

Identity verification plays an important role in creating trust in the economic system. It can, and should, be done in a way that doesn't decrease individual privacy.

Cloud computing is an emerging paradigm shifting the shape of computing models from being a technology to a utility. However, security, privacy and trust are amongst the issues that can subvert the benefits and hence wide deployment of cloud computing. With the introduction of omnipresent mobile-based clients, the ubiquity of the model increases, suggesting a still higher integration in life. Nonetheless, the security issues rise to a higher degree as well. The constrained input methods for credentials and the vulnerable wireless communication links are among factors giving rise to serious security issues. To strengthen the access control of cloud resources, organizations now commonly acquire Identity Management Systems (IdM). This paper presents that the most popular IdM, namely OAuth, working in scope of Mobile Cloud Computing has many weaknesses in authorization architecture. In particular, authors find two major issues in current IdM. First, if the IdM System is compromised through malicious code, it allows a hacker to get authorization of all the protected resources hosted on a cloud. Second, all the communication links among client, cloud and IdM carries complete authorization token, that can allow hacker, through traffic interception at any communication link, an illegitimate access of protected resources. We also suggest a solution to the reported problems, and justify our arguments with experimentation and mathematical modeling.

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.

Cloud computing is one of the emerging computing technology where costs are directly proportional to usage and demand. The advantages of this technology are the reasons of security and privacy problems. The data belongs to the users are stored in some cloud servers which is not under their own control. So the cloud services are required to authenticate the user. In general, most of the cloud authentication algorithms do not provide anonymity of the users. The cloud provider can track the users easily. The privacy and authenticity are two critical issues of cloud security. In this paper, we propose a secure anonymous authentication method for cloud services using identity based group signature which allows the cloud users to prove that they have privilege to access the data without revealing their identities.

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.

The strong development of the Internet of Things (IoT) is dramatically changing traditional perceptions of the current Internet towards an integrated vision of smart objects interacting with each other. While in recent years many technological challenges have already been solved through the extension and adaptation of wireless technologies, security and privacy still remain as the main barriers for the IoT deployment on a broad scale. In this emerging paradigm, typical scenarios manage particularly sensitive data, and any leakage of information could severely damage the privacy of users. This paper provides a concise description of some of the major challenges related to these areas that still need to be overcome in the coming years for a full acceptance of all IoT stakeholders involved. In addition, we propose a distributed capability-based access control mechanism which is built on public key cryptography in order to cope with some of these challenges. Specifically, our solution is based on the design of a lightweight token used for access to CoAP Resources, and an optimized implementation of the Elliptic Curve Digital Signature Algorithm (ECDSA) inside the smart object. The results obtained from our experiments demonstrate the feasibility of the proposal and show promising in order to cover more complex scenarios in the future, as well as its application in specific IoT use cases.

Vehicular ad-hoc networks (VANETs) provides infrastructure less, rapidly deployable, self-configurable network connectivity. The network is the collection vehicles interlinked by wireless links and willing to store and forward data for their peers. As vehicles move freely and organize themselves arbitrarily, message routing is done dynamically based on network connectivity. Compared with other ad-hoc networks, VANETs are particularly challenging due to the part of the vehicles' high rate of mobility and the numerous signal-weakening barrier, such as buildings, in their environments. Due to their enormous potential, VANET have gained an increasing attention in both industry and academia. Research activities range from lower layer protocol design to applications and implementation issues. A secure VANET system, while exchanging information should protect the system against unauthorized message injection, message alteration, eavesdropping. The security of VANET is one of the most critical issues because their information transmission is propagated in open access (wireless) environments. A few years back VANET has received increased attention as the potential technology to enhance active and preventive safety on the road, as well as travel comfort Safekeeping and privacy are mandatory in vehicular communications for a grateful acceptance and use of such technology. This paper is an attempt to highlight the problems occurred in Vehicular Ad hoc Networks and security issues.

The E-mail messaging is one of the most popular uses of the Internet and the multiple Internet users can exchange messages within short span of time. Although the security of the E-mail messages is an important issue, no such security is supported by the Internet standards. One well known scheme, called PGP (Pretty Good Privacy) is used for personal security of E-mail messages. There is an attack on CFB Mode Encryption as used by OpenPGP. To overcome the attacks and to improve the security a new model is proposed which is "Secure Mail using Visual Cryptography". In the secure mail using visual cryptography the message to be transmitted is converted into a gray scale image. Then (2, 2) visual cryptographic shares are generated from the gray scale image. The shares are encrypted using A Chaos-Based Image Encryption Algorithm Using Wavelet Transform and authenticated using Public Key based Image Authentication method. One of the shares is send to a server and the second share is send to the receipent's mail box. The two shares are transmitted through two different transmission medium so man in the middle attack is not possible. If an adversary has only one out of the two shares, then he has absolutely no information about the message. At the receiver side the two shares are fetched, decrypted and stacked to generate the grey scale image. From the grey scale image the message is reconstructed.
 

Privacy preservation is very essential in various real life applications such as medical science and financial analysis. This paper focuses on implementation of an asymmetric secure multi-party computation protocol using anonymization and public-key encryption where all parties have access to trusted third party (TTP) who (1) doesn't add any contribution to computation (2) doesn't know who is the owner of the input received (3) has large number of resources (4) decryption key is known to trusted third party (TTP) to get the actual input for computation of final result. In this environment, concern is to design a protocol which deploys TTP for computation. It is proposed that the protocol is very proficient (in terms of secure computation and individual privacy) for the parties than the other available protocols. The solution incorporates protocol using asymmetric encryption scheme where any party can encrypt a message with the public key but decryption can be done by only the possessor of the decryption key (private key). As the protocol works on asymmetric encryption and packetization it ensures following: (1) Confidentiality (Anonymity) (2) Security (3) Privacy (Data).

In 2013, Biswas and Misic proposed a new privacy-preserving authentication scheme for WAVE-based vehicular ad hoc networks (VANETs), claiming that they used a variant of the Elliptic Curve Digital Signature Algorithm (ECDSA). However, our study has discovered that the authentication scheme proposed by them is vulnerable to a private key reveal attack. Any malicious receiving vehicle who receives a valid signature from a legal signing vehicle can gain access to the signing vehicle private key from the learned valid signature. Hence, the authentication scheme proposed by Biswas and Misic is insecure. We thus propose an improved version to overcome this weakness. The proposed improved scheme also supports identity revocation and trace. Based on this security property, the CA and a receiving entity (RSU or OBU) can check whether a received signature has been generated by a revoked vehicle. Security analysis is also conducted to evaluate the security strength of the proposed authentication scheme.

A scheme for preserving privacy in MobilityFirst (MF) clean-slate future Internet architecture is proposed in this paper. The proposed scheme, called Anonymity in MobilityFirst (AMF), utilizes the three-tiered approach to effectively exploit the inherent properties of MF Network such as Globally Unique Flat Identifier (GUID) and Global Name Resolution Service (GNRS) to provide anonymity to the users. While employing new proposed schemes in exchanging of keys between different tiers of routers to alleviate trust issues, the proposed scheme uses multiple routers in each tier to avoid collaboration amongst the routers in the three tiers to expose the end users.

Communicating vehicles will change road traffic as we know it. With current versions of European and US standards in mind, the authors discuss privacy and traffic surveillance issues in vehicular network technology and outline research directions that could address these issues.

Data is one of the most valuable assets for organization. It can facilitate users or organizations to meet their diverse goals, ranging from scientific advances to business intelligence. Due to the tremendous growth of data, the notion of big data has certainly gained momentum in recent years. Cloud computing is a key technology for storing, managing and analyzing big data. However, such large, complex, and growing data, typically collected from various data sources, such as sensors and social media, can often contain personally identifiable information (PII) and thus the organizations collecting the big data may want to protect their outsourced data from the cloud. In this paper, we survey our research towards development of efficient and effective privacy-enhancing (PE) techniques for management and analysis of big data in cloud computing.We propose our initial approaches to address two important PE applications: (i) privacy-preserving data management and (ii) privacy-preserving data analysis under the cloud environment. Additionally, we point out research issues that still need to be addressed to develop comprehensive solutions to the problem of effective and efficient privacy-preserving use of data.
 

The growing popularity and development of data mining technologies bring serious threat to the security of individual,'s sensitive information. An emerging research topic in data mining, known as privacy-preserving data mining (PPDM), has been extensively studied in recent years. The basic idea of PPDM is to modify the data in such a way so as to perform data mining algorithms effectively without compromising the security of sensitive information contained in the data. Current studies of PPDM mainly focus on how to reduce the privacy risk brought by data mining operations, while in fact, unwanted disclosure of sensitive information may also happen in the process of data collecting, data publishing, and information (i.e., the data mining results) delivering. In this paper, we view the privacy issues related to data mining from a wider perspective and investigate various approaches that can help to protect sensitive information. In particular, we identify four different types of users involved in data mining applications, namely, data provider, data collector, data miner, and decision maker. For each type of user, we discuss his privacy concerns and the methods that can be adopted to protect sensitive information. We briefly introduce the basics of related research topics, review state-of-the-art approaches, and present some preliminary thoughts on future research directions. Besides exploring the privacy-preserving approaches for each type of user, we also review the game theoretical approaches, which are proposed for analyzing the interactions among different users in a data mining scenario, each of whom has his own valuation on the sensitive information. By differentiating the responsibilities of different users with respect to security of sensitive information, we would like to provide some useful insights into the study of PPDM.

Threats which come from database insiders or database outsiders have formed a big challenge to the protection of integrity and confidentiality in many database systems. To overcome this situation a new domain called a Database Forensic (DBF) has been introduced to specifically investigate these dynamic threats which have posed many problems in Database Management Systems (DBMS) of many organizations. DBF is a process to identify, collect, preserve, analyse, reconstruct and document all digital evidences caused by this challenge. However, until today, this domain is still lacks having a standard and generic knowledge base for its forensic investigation methods / tools due to many issues and challenges in its complex processes. Therefore, this paper will reveal an approach adapted from a software engineering domain called metamodelling which will unify these DBF complex knowledge processes into an artifact, a metamodel (DBF Metamodel). In future, the DBF Metamodel could benefit many DBF investigation users such as database investigators, stockholders, and other forensic teams in offering various possible solutions for their problem domain.
 

Big data's explosive growth has prompted the US government to release new reports that address the issues--particularly related to privacy--resulting from this growth. The Web extra at http://youtu.be/j49eoe5g8-c is an audio recording from the Computing and the Law column, in which authors Brian M. Gaff, Heather Egan Sussman, and Jennifer Geetter discuss how big data's explosive growth has prompted the US government to release new reports that address the issues--particularly related to privacy--resulting from this growth.
 

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.

With the arrival of the big data era, information privacy and security issues become even more crucial. The Mining Associations with Secrecy Konstraints (MASK) algorithm and its improved versions were proposed as data mining approaches for privacy preserving association rules. The MASK algorithm only adopts a data perturbation strategy, which leads to a low privacy-preserving degree. Moreover, it is difficult to apply the MASK algorithm into practices because of its long execution time. This paper proposes a new algorithm based on data perturbation and query restriction (DPQR) to improve the privacy-preserving degree by multi-parameters perturbation. In order to improve the time-efficiency, the calculation to obtain an inverse matrix is simplified by dividing the matrix into blocks; meanwhile, a further optimization is provided to reduce the number of scanning database by set theory. Both theoretical analyses and experiment results prove that the proposed DPQR algorithm has better performance.
 

With the arrival of the big data era, information privacy and security issues become even more crucial. The Mining Associations with Secrecy Konstraints (MASK) algorithm and its improved versions were proposed as data mining approaches for privacy preserving association rules. The MASK algorithm only adopts a data perturbation strategy, which leads to a low privacy-preserving degree. Moreover, it is difficult to apply the MASK algorithm into practices because of its long execution time. This paper proposes a new algorithm based on data perturbation and query restriction (DPQR) to improve the privacy-preserving degree by multi-parameters perturbation. In order to improve the time-efficiency, the calculation to obtain an inverse matrix is simplified by dividing the matrix into blocks; meanwhile, a further optimization is provided to reduce the number of scanning database by set theory. Both theoretical analyses and experiment results prove that the proposed DPQR algorithm has better performance.
 

For the first time in the history of humanity, more them half of the population is now living in big cities. This scenario has raised concerns related systems that provide basic services to citizens. Even more, those systems has now the responsibility to empower the citizen with information and values that may aid people on daily decisions, such as related to education, transport, healthy and others. This environment creates a set of services that, interconnected, can develop a brand new range of solutions that refers to a term often called System of Systems. In this matter, focusing in a smart city, new challenges related to information security raises, those concerns may go beyond the concept of privacy issues exploring situations where the entire environment could be affected by issues different them only break the confidentiality of a data. This paper intends to discuss and propose 9 security issues that can be part of a smart city environment, and that explores more them just citizens privacy violations.
 

This paper has conducted analyzing the accident case of data spill to study policy issues for ICT security from a social science perspective focusing on risk. The results from case analysis are as follows. First, ICT risk can be categorized 'severe, strong, intensive and individual' from the level of both probability and impact. Second, strategy of risk management can be designated 'avoid, transfer, mitigate, accept' by understanding their own culture type of relative group such as 'hierarchy, egalitarianism, fatalism and individualism'. Third, personal data has contained characteristics of big data such like 'volume, velocity, variety' for each risk situation. Therefore, government needs to establish a standing organization responsible for ICT risk policy and management in a new big data era. And the policy for ICT risk management needs to balance in considering 'technology, norms, laws, and market' in big data era.