Biblio

The new era of information communication and technology (ICT), everyone wants to store/share their Data or information in online media, like in cloud database, mobile database, grid database, drives etc. When the data is stored in online media the main problem is arises related to data is privacy because different types of hacker, attacker or crackers wants to disclose their private information as publically. Security is a continuous process of protecting the data or information from attacks. For securing that information from those kinds of unauthorized people we proposed and implement of one the technique based on the data modification concept with taking the iris database on weka tool. And this paper provides the high privacy in distributed clustered database environments.

Now a day's cloud computing is power station to run multiple businesses. It is cumulating more and more users every day. Database-as-a-service is service model provided by cloud computing to store, manage and process data on a cloud platform. Database-as-a-service has key characteristics such as availability, scalability, elasticity. A customer does not have to worry about database installation and management. As a replacement, the cloud database service provider takes responsibility for installing and maintaining the database. The real problem occurs when it comes to storing confidential or private information in the cloud database, we cannot rely on the cloud data vendor. A curious cloud database vendor may capture and leak the secret information. For that purpose, Protected Database-as-a-service is a novel solution to this problem that provides provable and pragmatic privacy in the face of a compromised cloud database service provider. Protected Database-as-a-service defines various encryption schemes to choose encryption algorithm and encryption key to encrypt and decrypt data. It also provides "Master key" to users, so that a metadata storage table can be decrypted only by using the master key of the users. As a result, a cloud service vendor never gets access to decrypted data, and even if all servers are jeopardized, in such inauspicious circumstances a cloud service vendor will not be able to decrypt the data. Proposed Protected Database-as-a-service system allows multiple geographically distributed clients to execute concurrent and independent operation on encrypted data and also conserve data confidentiality and consistency at cloud level, to eradicate any intermediate server between the client and the cloud database.

So far, cloud storage has been accepted by an increasing number of people, which is not a fresh notion any more. It brings cloud users a lot of conveniences, such as the relief of local storage and location independent access. Nevertheless, the correctness and completeness as well as the privacy of outsourced data are what worry could users. As a result, most people are unwilling to store data in the cloud, in case that the sensitive information concerning something important is disclosed. Only when people feel worry-free, can they accept cloud storage more easily. Certainly, many experts have taken this problem into consideration, and tried to solve it. In this paper, we survey the solutions to the problems concerning auditing in cloud computing and give a comparison of them. The methods and performances as well as the pros and cons are discussed for the state-of-the-art auditing protocols.

The threats of smartphone security are mostly from the privacy disclosure and malicious chargeback software which deducting expenses abnormally. They exploit the vulnerabilities of previous permission mechanism to attack to mobile phones, and what's more, it might call hardware to spy privacy invisibly in the background. As the existing Android operating system doesn't support users the monitoring and auditing of system resources, a dynamic supervisory mechanism of process behavior based on Dalvik VM is proposed to solve this problem. The existing android system framework layer and application layer are modified and extended, and special underlying services of system are used to realize a dynamic supervisory on the process behavior of Dalvik VM. Via this mechanism, each process on the system resources and the behavior of each app process can be monitored and analyzed in real-time. It reduces the security threats in system level and positions that which process is using the system resource. It achieves the detection and interception before the occurrence or the moment of behavior so that it protects the private information, important data and sensitive behavior of system security. Extensive experiments have demonstrated the accuracy, effectiveness, and robustness of our approach.

Steganography is the art of the hidden data in such a way that it detection of hidden knowledge prevents. As the necessity of security and privacy increases, the need of the hiding secret data is ongoing. In this paper proposed an enhanced detection of the 1-2-4 LSB steganography and RSA cryptography in Gray Scale and Color images. For color images, we apply 1-2-4 LSB on component of the RGB, then encrypt information applying RSA technique. For Gray Images, we use LSB to then encrypt information and also detect edges of gray image. In the experimental outcomes, calculate PSNR and MSE. We calculate peak signal noise ratio for quality and brightness. This method makes sure that the information has been encrypted before hiding it into an input image. If in any case the cipher text got revealed from the input image, the middle person other than receiver can't access the information as it is in encrypted form.

Due to the noise in the images, the edges extracted from these noisy images are always discontinuous and inaccurate by traditional operators. In order to solve these problems, this paper proposes multi-direction edge detection operator to detect edges from noisy images. The new operator is designed by introducing the shear transformation into the traditional operator. On the one hand, the shear transformation can provide a more favorable treatment for directions, which can make the new operator detect edges in different directions and overcome the directional limitation in the traditional operator. On the other hand, all the single pixel edge images in different directions can be fused. In this case, the edge information can complement each other. The experimental results indicate that the new operator is superior to the traditional ones in terms of the effectiveness of edge detection and the ability of noise rejection.

With the growing observed success of big data use, many challenges appeared. Timeless, scalability and privacy are the main problems that researchers attempt to figure out. Privacy preserving is now a highly active domain of research, many works and concepts had seen the light within this theme. One of these concepts is the de-identification techniques. De-identification is a specific area that consists of finding and removing sensitive information either by replacing it, encrypting it or adding a noise to it using several techniques such as cryptography and data mining. In this report, we present a new model of de-identification of textual data using a specific Immune System algorithm known as CLONALG.

The modern day approach in boulevard network centers on efficient factor in safe routing. The safe routing must follow up the low risk cities. The troubles in routing are a perennial one confronting people day in and day out. The common goal of everyone using a boulevard seems to be reaching the desired point through the fastest manner which involves the balancing conundrum of multiple expected and unexpected influencing factors such as time, distance, security and cost. It is universal knowledge that travelling is an almost inherent aspect in everyone's daily routine. With the gigantic and complex road network of a modern city or country, finding a low risk community for traversing the distance is not easy to achieve. This paper follows the code based community for detecting the boulevard network and fuzzy technique for identifying low risk community.

The majority of applications use a prompt for a username and password. Passwords are recommended to be unique, long, complex, alphanumeric and non-repetitive. These reasons that make passwords secure may prove to be a point of weakness. The complexity of the password provides a challenge for a user and they may choose to record it. This compromises the security of the password and takes away its advantage. An alternate method of security is Keystroke Biometrics. This approach uses the natural typing pattern of a user for authentication. This paper proposes a new method for reducing error rates and creating a robust technique. The new method makes use of multiple sensors to obtain information about a user. An artificial neural network is used to model a user's behavior as well as for retraining the system. An alternate user verification mechanism is used in case a user is unable to match their typing pattern.

The increasing exploitation of the internet leads to new uncertainties, due to interdependencies and links between cyber and physical layers. As an example, the integration between telecommunication and physical processes, that happens when the power grid is managed and controlled, yields to epistemic uncertainty. Managing this uncertainty is possible using specific frameworks, usually coming from fuzzy theory such as Evidence Theory. This approach is attractive due to its flexibility in managing uncertainty by means of simple rule-based systems with data coming from heterogeneous sources. In this paper, Evidence Theory is applied in order to evaluate risk. Therefore, the authors propose a frame of discernment with a specific property among the elements based on a graph representation. This relationship leads to a smaller power set (called Reduced Power Set) that can be used as the classical power set, when the most common combination rules, such as Dempster or Smets, are applied. The paper demonstrates how the use of the Reduced Power Set yields to more efficient algorithms for combining evidences and to application of Evidence Theory for assessing risk.

Security in mobile handsets of telecommunication standards such as GSM, Project 25 and TETRA is very important, especially when governments and military forces use handsets and telecommunication devices. Although telecommunication could be quite secure by using encryption, coding, tunneling and exclusive channel, attackers create new ways to bypass them without the knowledge of the legitimate user. In this paper we introduce a new, simple and economical circuit to warn the user in cases where the message is not encrypted because of manipulation by attackers or accidental damage. This circuit not only consumes very low power but also is created to sustain telecommunication devices in aspect of security and using friendly. Warning to user causes the best practices of telecommunication devices without wasting time and energy for fault detection.

RFID-enabled product supply chain visibility is usually implemented by building up a view of the product history of its activities starting from manufacturing or even earlier with a dynamically updated e-pedigree for track-and-trace, which is examined and authenticated at each node of the supply chain for data consistence with the pre-defined one. However, while effectively reducing the risk of fakes, this visibility can't guarantee that the product is authentic without taking further security measures. To the best of our knowledge, this requires deeper understandings on associations of object events with the counterfeiting activities, which is unfortunately left blank. In this paper, the taxonomy of counterfeiting possibilities is initially developed and analyzed, the structure of EPC-based events is then re-examined, and an object-centric coding mechanism is proposed to construct the object-based event “pedigree” for such event exception detection and inference. On this basis, the system architecture framework to achieve the objectivity of object event visibility for anti-counterfeiting is presented, which is also applicable to other aspects of supply chain management.

The stability and effectiveness of supply chain financing union are directly affected by income fluctuation and unequal distribution problems, subsequently making the economic interests of the involved parties impacted. In this paper, the incomes of the parties in the union were distributed using Shapley value from the perspective of cooperative game under the background of the supply chain financing based on third-party trading platform, and then correction factors were weighted by introducing risk correction factors and combining with analytic hierarchy process (AHP), in order to improve the original model. Finally, the feasibility of the scheme was proved using example.

In recent years, The vulnerability of agricultural products chain is been exposed because of the endlessly insecure events appeared in every areas and every degrees from the natural disasters on the each node operation of agricultural products supply chain in recently years. As an very important place of HUNAN Province because of its abundant agricultural products, the Eastern Area's security in agricultural products supply chain was related to the safety and stability of economic development in the entire region. In order to make the more objective, scientific, practical of risk management in the empirical analysis, This item is based on the AHP-FCS method to deal with the qualitative to quantitative analysis about risk management of agricultural product supply chain, to identify and evaluate the probability and severity of all the risk possibility.

The ownership transfer of RFID tag means a tagged product changes control over the supply chain. Recently, Doss et al. proposed two secure RFID tag ownership transfer (RFID-OT) protocols based on quadratic residues. However, we find that they are vulnerable to the desynchronization attack. The attack is probabilistic. As the parameters in the protocols are adopted, the successful probability is 93.75%. We also show that the use of the pseudonym of the tag h(TID) and the new secret key KTID are not feasible. In order to solve these problems, we propose the improved schemes. Security analysis shows that the new protocols can resist in the desynchronization attack and other attacks. By optimizing the performance of the new protocols, it is more practical and feasible in the large-scale deployment of RFID tags.

Networked systems have adapted Radio Frequency identification technology (RFID) to automate their business process. The Networked RFID Systems (NRS) has some unique characteristics which raise new privacy and security concerns for organizations and their NRS systems. The businesses are always having new realization of business needs using NRS. One of the most recent business realization of NRS implementation on large scale distributed systems (such as Internet of Things (IoT), supply chain) is to ensure visibility and traceability of the object throughout the chain. However, this requires assurance of security and privacy to ensure lawful business operation. In this paper, we are proposing a secure tracker protocol that will ensure not only visibility and traceability of the object but also genuineness of the object and its travel path on-site. The proposed protocol is using Physically Unclonable Function (PUF), Diffie-Hellman algorithm and simple cryptographic primitives to protect privacy of the partners, injection of fake objects, non-repudiation, and unclonability. The tag only performs a simple mathematical computation (such as combination, PUF and division) that makes the proposed protocol suitable to passive tags. To verify our security claims, we performed experiment on Security Protocol Description Language (SPDL) model of the proposed protocol using automated claim verification tool Scyther. Our experiment not only verified our claims but also helped us to eliminate possible attacks identified by Scyther.

A novel approach is developed for analyzing power system vulnerability related to extraordinary events. Vulnerability analyses are necessary for identification of barriers to prevent such events and as a basis for the emergency preparedness. Identification of cause and effect relationships to reveal vulnerabilities related to extraordinary events is a complex and difficult task. In the proposed approach, the analysis starts by identifying the critical consequences. Then the critical contingencies and operating states, and which external threats and causes that may result in such severe consequences, are identified. This is opposed to the traditional risk and vulnerability analysis which starts by analyzing threats and what can happen as a chain of events. The vulnerability analysis methodology is tested and demonstrated on real systems.

In the Internet-of-Things (IoT), users might share part of their data with different IoT prosumers, which offer applications or services. Within this open environment, the existence of an adversary introduces security risks. These can be related, for instance, to the theft of user data, and they vary depending on the security controls that each IoT prosumer has put in place. To minimize such risks, users might seek an “optimal” set of prosumers. However, assuming the adversary has the same information as the users about the existing security measures, he can then devise which prosumers will be preferable (e.g., with the highest security levels) and attack them more intensively. This paper proposes a decision-support approach that minimizes security risks in the above scenario. We propose a non-cooperative, two-player game entitled Prosumers Selection Game (PSG). The Nash Equilibria of PSG determine subsets of prosumers that optimize users' payoffs. We refer to any game solution as the Nash Prosumers Selection (NPS), which is a vector of probabilities over subsets of prosumers. We show that when using NPS, a user faces the least expected damages. Additionally, we show that according to NPS every prosumer, even the least secure one, is selected with some non-zero probability. We have also performed simulations to compare NPS against two different heuristic selection algorithms. The former is proven to be approximately 38% more effective in terms of security-risk mitigation.

Security decision-making is a critical task in tackling security threats affecting a system or process. It often involves selecting a suitable resolution action to tackle an identified security risk. To support this selection process, decision-makers should be able to evaluate and compare available decision options. This article introduces a modelling language that can be used to represent the effects of resolution actions on the stakeholders' goals, the crime process, and the attacker. In order to reach this aim, we develop a multidisciplinary framework that combines existing knowledge from the fields of software engineering, crime science, risk assessment, and quantitative decision analysis. The framework is illustrated through an application to a case of identity theft.

The use of multi-terminal HVDC to integrate wind power coming from the North Sea opens de door for a new transmission system model, the DC-Independent System Operator (DC-ISO). DC-ISO will face highly stressed and varying conditions that requires new risk assessment tools to ensure security of supply. This paper proposes a novel risk-based static security assessment methodology named risk-based DC security assessment (RB-DCSA). It combines a probabilistic approach to include uncertainties and a fuzzy inference system to quantify the systemic and individual component risk associated with operational scenarios considering uncertainties. The proposed methodology is illustrated using a multi-terminal HVDC system where the variability of wind speed at the offshore wind is included.

A trap set to detect attempts at unauthorized use of information systems. But setting up these honeypots and keep these guzzling electricity 24X7 is rather expensive. Plus there is always a risk of a skillful hacker or a deadly malware may break through this and compromise the whole system. Honeypot name suggest, a pot that contents full of honey to allure beers, but in networks Scenario honeypot is valuable tool that helps to allure attackers. It helps to detect and analyze malicious activity over your network. However honeypots used for commercial organization do not share data and large honeypot gives read only data. We propose an Arm based device having all capability of honeypots to allure attackers. Current honeypots are based on large Network but we are trying to make s device which have the capabilities to establish in small network and cost effective. This research helps us to make a device based on arm board and CCFIS Software to allure attackers which is easy to install and cost effective. CCFIS Sensor helps us to Capture malware and Analysis the attack. In this we did reverse Engineering of honeypots to know about how it captures malware. During reverse engineering we know about pros and cons of honeypots that are mitigated in CCFIS Sensor. After Completion of device we compared honeypots and CCFIS Sensor to check the effectiveness of device.

To protect complex power-grid control networks, power operators need efficient security assessment techniques that take into account both cyber side and the power side of the cyber-physical critical infrastructures. In this paper, we present CPINDEX, a security-oriented stochastic risk management technique that calculates cyber-physical security indices to measure the security level of the underlying cyber-physical setting. CPINDEX installs appropriate cyber-side instrumentation probes on individual host systems to dynamically capture and profile low-level system activities such as interprocess communications among operating system assets. CPINDEX uses the generated logs along with the topological information about the power network configuration to build stochastic Bayesian network models of the whole cyber-physical infrastructure and update them dynamically based on the current state of the underlying power system. Finally, CPINDEX implements belief propagation algorithms on the created stochastic models combined with a novel graph-theoretic power system indexing algorithm to calculate the cyber-physical index, i.e., to measure the security-level of the system's current cyber-physical state. The results of our experiments with actual attacks against a real-world power control network shows that CPINDEX, within few seconds, can efficiently compute the numerical indices during the attack that indicate the progressing malicious attack correctly.
 

Discrete fractional Fourier transform (DFRFT) is a generalization of discrete Fourier transform. There are a number of DFRFT proposals, which are useful for various signal processing applications. This paper investigates practical solutions toward the construction of unconditionally secure communication systems based on DFRFT via cross-layer approach. By introducing a distort signal parameter, the sender randomly flip-flops between the distort signal parameter and the general signal parameter to confuse the attacker. The advantages of the legitimate partners are guaranteed. We extend the advantages between legitimate partners via developing novel security codes on top of the proposed cross-layer DFRFT security communication model, aiming to achieve an error-free legitimate channel while preventing the eavesdropper from any useful information. Thus, a cross-layer strong mobile communication secure model is built.
 

Remote data integrity checking is of crucial importance in cloud storage. It can make the clients verify whether their outsourced data is kept intact without downloading the whole data. In some application scenarios, the clients have to store their data on multicloud servers. At the same time, the integrity checking protocol must be efficient in order to save the verifier's cost. From the two points, we propose a novel remote data integrity checking model: ID-DPDP (identity-based distributed provable data possession) in multicloud storage. The formal system model and security model are given. Based on the bilinear pairings, a concrete ID-DPDP protocol is designed. The proposed ID-DPDP protocol is provably secure under the hardness assumption of the standard CDH (computational Diffie-Hellman) problem. In addition to the structural advantage of elimination of certificate management, our ID-DPDP protocol is also efficient and flexible. Based on the client's authorization, the proposed ID-DPDP protocol can realize private verification, delegated verification, and public verification.
 

Remote data integrity checking is of crucial importance in cloud storage. It can make the clients verify whether their outsourced data is kept intact without downloading the whole data. In some application scenarios, the clients have to store their data on multicloud servers. At the same time, the integrity checking protocol must be efficient in order to save the verifier's cost. From the two points, we propose a novel remote data integrity checking model: ID-DPDP (identity-based distributed provable data possession) in multicloud storage. The formal system model and security model are given. Based on the bilinear pairings, a concrete ID-DPDP protocol is designed. The proposed ID-DPDP protocol is provably secure under the hardness assumption of the standard CDH (computational Diffie-Hellman) problem. In addition to the structural advantage of elimination of certificate management, our ID-DPDP protocol is also efficient and flexible. Based on the client's authorization, the proposed ID-DPDP protocol can realize private verification, delegated verification, and public verification.