Biblio

In bound applications, the locations of events reportable by a device network have to be compelled to stay anonymous. That is, unauthorized observers should be unable to notice the origin of such events by analyzing the network traffic. The authors analyze 2 forms of downsides: Communication overhead and machine load problem. During this paper, the authors give a new framework for modeling, analyzing, and evaluating obscurity in device networks. The novelty of the proposed framework is twofold: initial, it introduces the notion of "interval indistinguishability" and provides a quantitative live to model obscurity in wireless device networks; second, it maps supply obscurity to the applied mathematics downside the authors showed that the present approaches for coming up with statistically anonymous systems introduce correlation in real intervals whereas faux area unit unrelated. The authors show however mapping supply obscurity to consecutive hypothesis testing with nuisance Parameters ends up in changing the matter of exposing non-public supply data into checking out associate degree applicable knowledge transformation that removes or minimize the impact of the nuisance data victimization sturdy cryptography algorithmic rule. By doing therefore, the authors remodeled the matter of analyzing real valued sample points to binary codes, that opens the door for committal to writing theory to be incorporated into the study of anonymous networks. In existing work, unable to notice unauthorized observer in network traffic. However this work in the main supported enhances their supply obscurity against correlation check, the most goal of supply location privacy is to cover the existence of real events.

Vehicle-to-grid (V2G), involving both charging and discharging of battery vehicles (BVs), enhances the smart grid substantially to alleviate peaks in power consumption. In a V2G scenario, the communications between BVs and power grid may confront severe cyber security vulnerabilities. Traditionally, authentication mechanisms are solely designed for the BVs when they charge electricity as energy customers. In this paper, we first show that, when a BV interacts with the power grid, it may act in one of three roles: 1) energy demand (i.e., a customer); 2) energy storage; and 3) energy supply (i.e., a generator). In each role, we further demonstrate that the BV has dissimilar security and privacy concerns. Hence, the traditional approach that only considers BVs as energy customers is not universally applicable for the interactions in the smart grid. To address this new security challenge, we propose a role-dependent privacy preservation scheme (ROPS) to achieve secure interactions between a BV and power grid. In the ROPS, a set of interlinked subprotocols is proposed to incorporate different privacy considerations when a BV acts as a customer, storage, or a generator. We also outline both centralized and distributed discharging operations when a BV feeds energy back into the grid. Finally, security analysis is performed to indicate that the proposed ROPS owns required security and privacy properties and can be a highly potential security solution for V2G networks in the smart grid. The identified security challenge as well as the proposed ROPS scheme indicates that role-awareness is crucial for secure V2G networks.

Preserving the availability and integrity of networked computing systems in the face of fast-spreading intrusions requires advances not only in detection algorithms, but also in automated response techniques. In this paper, we propose a new approach to automated response called the response and recovery engine (RRE). Our engine employs a game-theoretic response strategy against adversaries modeled as opponents in a two-player Stackelberg stochastic game. The RRE applies attack-response trees (ART) to analyze undesired system-level security events within host computers and their countermeasures using Boolean logic to combine lower level attack consequences. In addition, the RRE accounts for uncertainties in intrusion detection alert notifications. The RRE then chooses optimal response actions by solving a partially observable competitive Markov decision process that is automatically derived from attack-response trees. To support network-level multiobjective response selection and consider possibly conflicting network security properties, we employ fuzzy logic theory to calculate the network-level security metric values, i.e., security levels of the system's current and potentially future states in each stage of the game. In particular, inputs to the network-level game-theoretic response selection engine, are first fed into the fuzzy system that is in charge of a nonlinear inference and quantitative ranking of the possible actions using its previously defined fuzzy rule set. Consequently, the optimal network-level response actions are chosen through a game-theoretic optimization process. Experimental results show that the RRE, using Snort's alerts, can protect large networks for which attack-response trees have more than 500 nodes.

Recent advances in Wireless Sensor Networks have given rise to many application areas in healthcare such as the new field of Wireless Body Area Networks. The health status of humans can be tracked and monitored using wearable and non-wearable sensor devices. Security in WBAN is very important to guarantee and protect the patient's personal sensitive data and establishing secure communications between BAN sensors and external users is key to addressing prevalent security and privacy concerns. In this paper, we propose secure and efficient key management scheme based on ECC algorithm to protect patient's medical information in healthcare system. Our scheme divided into three phases as setup, registration, verification and key exchange. And we use the identification code which is the SIM card number on a patient's smart phone with the private key generated by the legal use instead of the third party. Also to prevent the replay attack, we use counter number at every process of authenticated message exchange to resist.

In order to conserve wireless sensor network (WSN) lifetime, data aggregation is applied. Some researchers consider the importance of security and propose secure data aggregation protocols. The essential of those secure approaches is to make sure that the aggregators aggregate the data in appropriate and secure way. In this paper we give the description of ESPDA (Energy-efficient and Secure Pattern-based Data Aggregation) and SRDA (Secure Reference-Based Data Aggregation) protocol that work on cluster-based WSN and the deep security analysis that are different from the previously presented one.

Wireless Sensor Networks (WSN) is vulnerable to node capture attacks in which an attacker can capture one or more sensor nodes and reveal all stored security information which enables him to compromise a part of the WSN communications. Due to large number of sensor nodes and lack of information about deployment and hardware capabilities of sensor node, key management in wireless sensor networks has become a complex task. Limited memory resources and energy constraints are the other issues of key management in WSN. Hence an efficient key management scheme is necessary which reduces the impact of node capture attacks and consume less energy. By simulation results, we show that our proposed technique efficiently increases packet delivery ratio with reduced energy consumption.

The Cloud computing offers various services and web based applications over the internet. With the tremendous growth in the development of cloud based services, the security issue is the main challenge and today's concern for the cloud service providers. This paper describes the management of security issues based on Diameter AAA mechanisms for authentication, authorization and accounting (AAA) demanded by cloud service providers. This paper focuses on the integration of Diameter AAA into cloud system architecture.
 

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.

This article is a summary description of the Cognitive Packet Network (CPN) which is an example both of a completely software defined network (SDN) and of a self-aware computer network (SAN) which has been completely implemented and used in numerous experiments. CPN is able to observe its own internal performance as well as the interfaces of the external systems that it interacts with, in order to modify its behaviour so as to adaptively achieve objectives, such as discovering services for its users, improving their Quality of Service (QoS), reduce its own energy consumption, compensate for components which fail or malfunction, detect and react to intrusions, and defend itself against attacks.
 

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.

MANET is an infrastructure less, dynamic, decentralised network. Any node can join the network and leave the network at any point of time. Due to its simplicity and flexibility, it is widely used in military communication, emergency communication, academic purpose and mobile conferencing. In MANET there no infrastructure hence each node acts as a host and router. They are connected to each other by Peer-to-peer network. Decentralised means there is nothing like client and server. Each and every node is acted like a client and a server. Due to the dynamic nature of mobile Ad-HOC network it is more vulnerable to attack. Since any node can join or leave the network without any permission the security issues are more challenging than other type of network. One of the major security problems in ad hoc networks called the black hole problem. It occurs when a malicious node referred as black hole joins the network. The black hole conducts its malicious behavior during the process of route discovery. For any received RREQ, the black hole claims having route and propagates a faked RREP. The source node responds to these faked RREPs and sends its data through the received routes once the data is received by the black hole; it is dropped instead of being sent to the desired destination. This paper discusses some of the techniques put forwarded by researchers to detect and prevent Black hole attack in MANET using AODV protocol and based on their flaws a new methodology also have been proposed.

In a modern software system, when a program fails, a crash report which contains an execution trace would be sent to the software vendor for diagnosis. A crash report which corresponds to a failure could be caused by multiple types of faults simultaneously. Many large companies such as Baidu organize a team to analyze these failures, and classify them into multiple labels (i.e., multiple types of faults). However, it would be time-consuming and difficult for developers to manually analyze these failures and come out with appropriate fault labels. In this paper, we automatically classify a failure into multiple types of faults, using a composite algorithm named MLL-GA, which combines various multi-label learning algorithms by leveraging genetic algorithm (GA). To evaluate the effectiveness of MLL-GA, we perform experiments on 6 open source programs and show that MLL-GA could achieve average F-measures of 0.6078 to 0.8665. We also compare our algorithm with Ml.KNN and show that on average across the 6 datasets, MLL-GA improves the average F-measure of MI.KNN by 14.43%.
 

Communication in Mobile Ad hoc network is done over a shared wireless channel with no Central Authority (CA) to monitor. Responsibility of maintaining the integrity and secrecy of data, nodes in the network are held responsible. To attain the goal of trusted communication in MANET (Mobile Ad hoc Network) lot of approaches using key management has been implemented. This work proposes a composite identity and trust based model (CIDT) which depends on public key, physical identity, and trust of a node which helps in secure data transfer over wireless channels. CIDT is a modified DSR routing protocol for achieving security. Trust Factor of a node along with its key pair and identity is used to authenticate a node in the network. Experience based trust factor (TF) of a node is used to decide the authenticity of a node. A valid certificate is generated for authentic node to carry out the communication in the network. Proposed method works well for self certification scheme of a node in the network.

Communication in Mobile Ad hoc network is done over a shared wireless channel with no Central Authority (CA) to monitor. Responsibility of maintaining the integrity and secrecy of data, nodes in the network are held responsible. To attain the goal of trusted communication in MANET (Mobile Ad hoc Network) lot of approaches using key management has been implemented. This work proposes a composite identity and trust based model (CIDT) which depends on public key, physical identity, and trust of a node which helps in secure data transfer over wireless channels. CIDT is a modified DSR routing protocol for achieving security. Trust Factor of a node along with its key pair and identity is used to authenticate a node in the network. Experience based trust factor (TF) of a node is used to decide the authenticity of a node. A valid certificate is generated for authentic node to carry out the communication in the network. Proposed method works well for self certification scheme of a node in the network.

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.

Wireless Sensor Networking is one of the most promising technologies that have applications ranging from health care to tactical military. Although Wireless Sensor Networks (WSNs) have appealing features (e.g., low installation cost, unattended network operation), due to the lack of a physical line of defense (i.e., there are no gateways or switches to monitor the information flow), the security of such networks is a big concern, especially for the applications where confidentiality has prime importance. Therefore, in order to operate WSNs in a secure way, any kind of intrusions should be detected before attackers can harm the network (i.e., sensor nodes) and/or information destination (i.e., data sink or base station). In this article, a survey of the state-of-the-art in Intrusion Detection Systems (IDSs) that are proposed for WSNs is presented. Firstly, detailed information about IDSs is provided. Secondly, a brief survey of IDSs proposed for Mobile Ad-Hoc Networks (MANETs) is presented and applicability of those systems to WSNs are discussed. Thirdly, IDSs proposed for WSNs are presented. This is followed by the analysis and comparison of each scheme along with their advantages and disadvantages. Finally, guidelines on IDSs that are potentially applicable to WSNs are provided. Our survey is concluded by highlighting open research issues in the field.

This research focuses on hyper visor security from holistic perspective. It centers on hyper visor architecture - the organization of the various subsystems which collectively compromise a virtualization platform. It holds that the path to a secure hyper visor begins with a big-picture focus on architecture. Unfortunately, little research has been conducted with this perspective. This study investigates the impact of monolithic and micro kernel hyper visor architectures on the size and scope of the attack surface. Six architectural features are compared: management API, monitoring interface, hyper calls, interrupts, networking, and I/O. These subsystems are core hyper visor components which could be used as attack vectors. Specific examples and three leading hyper visor platforms are referenced (ESXi for monolithic architecture; Xen and Hyper-V for micro architecture). The results describe the relative strengths and vulnerabilities of both types of architectures. It is concluded that neither design is more secure, since both incorporate security tradeoffs in core processes.

The Internet is vulnerable to bandwidth distributed denial-of-service (BW-DDoS) attacks, wherein many hosts send a huge number of packets to cause congestion and disrupt legitimate traffic. So far, BW-DDoS attacks have employed relatively crude, inefficient, brute force mechanisms; future attacks might be significantly more effective and harmful. To meet the increasing threats, we must deploy more advanced defenses.

The delay-tolerant-network (DTN) model is becoming a viable communication alternative to the traditional infrastructural model for modern mobile consumer electronics equipped with short-range communication technologies such as Bluetooth, NFC, and Wi-Fi Direct. Proximity malware is a class of malware that exploits the opportunistic contacts and distributed nature of DTNs for propagation. Behavioral characterization of malware is an effective alternative to pattern matching in detecting malware, especially when dealing with polymorphic or obfuscated malware. In this paper, we first propose a general behavioral characterization of proximity malware which based on naive Bayesian model, which has been successfully applied in non-DTN settings such as filtering email spams and detecting botnets. We identify two unique challenges for extending Bayesian malware detection to DTNs ("insufficient evidence versus evidence collection risk" and "filtering false evidence sequentially and distributedly"), and propose a simple yet effective method, look ahead, to address the challenges. Furthermore, we propose two extensions to look ahead, dogmatic filtering, and adaptive look ahead, to address the challenge of "malicious nodes sharing false evidence." Real mobile network traces are used to verify the effectiveness of the proposed methods.
 

This paper proposes an enhanced method for personal authentication based on finger Knuckle Print using Kekre's wavelet transform (KWT). Finger-knuckle-print (FKP) is the inherent skin patterns of the outer surface around the phalangeal joint of one's finger. It is highly discriminable and unique which makes it an emerging promising biometric identifier. Kekre's wavelet transform is constructed from Kekre's transform. The proposed system is evaluated on prepared FKP database that involves all categories of FKP. The total database of 500 samples of FKP. This paper focuses the different image enhancement techniques for the pre-processing of the captured images. The proposed algorithm is examined on 350 training and 150 testing samples of database and shows that the quality of database and pre-processing techniques plays important role to recognize the individual. The experimental result calculate the performance parameters like false acceptance rate (FAR), false rejection rate (FRR), True Acceptance rate (TAR), True rejection rate (TRR). The tested result demonstrated the improvement in EER (Error Equal Rate) which is very much important for authentication. The experimental result using Kekre's algorithm along with image enhancement shows that the finger knuckle recognition rate is better than the conventional method.
 

Mobile malware threats (e.g., on Android) have recently become a real concern. In this paper, we evaluate the state-of-the-art commercial mobile anti-malware products for Android and test how resistant they are against various common obfuscation techniques (even with known malware). Such an evaluation is important for not only measuring the available defense against mobile malware threats, but also proposing effective, next-generation solutions. We developed DroidChameleon, a systematic framework with various transformation techniques, and used it for our study. Our results on 10 popular commercial anti-malware applications for Android are worrisome: none of these tools is resistant against common malware transformation techniques. In addition, a majority of them can be trivially defeated by applying slight transformation over known malware with little effort for malware authors. Finally, in light of our results, we propose possible remedies for improving the current state of malware detection on mobile devices.

Data mining is the process of finding correlations in the relational databases. There are different techniques for identifying malicious database transactions. Many existing approaches which profile is SQL query structures and database user activities to detect intrusion, the log mining approach is the automatic discovery for identifying anomalous database transactions. Mining of the Data is very helpful to end users for extracting useful business information from large database. Multi-level and multi-dimensional data mining are employed to discover data item dependency rules, data sequence rules, domain dependency rules, and domain sequence rules from the database log containing legitimate transactions. Database transactions that do not comply with the rules are identified as malicious transactions. The log mining approach can achieve desired true and false positive rates when the confidence and support are set up appropriately. The implemented system incrementally maintain the data dependency rule sets and optimize the performance of the intrusion detection process.
 

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.

In Eurocrypt 2011, Obana proposed a (k, n) secret-sharing scheme that can identify up to ⌊((k− 2)/2)⌋ cheaters. The number of cheaters that this scheme can identify meets its upper bound. When the number of cheaters t satisfies t≤ ⌊((k− 1)/3)⌋, this scheme is extremely efficient since the size of share |Vi| can be written as |Vi| = |S|/ɛ, which almost meets its lower bound, where |S| denotes the size of secret and ε denotes the successful cheating probability; when the number of cheaters t is close to ⌊ ((k− 2)/2)⌋, the size of share is upper bounded by |Vi| = (n·(t + 1) · 2 |S|)/ɛ. A new (k, n) secret-sharing scheme capable of identifying ⌊((k − 2)/2)⌋ cheaters is presented in this study. Considering the general case that k shareholders are involved in secret reconstruction, the size of share of the proposed scheme is |Vi| = (2 |S| )/ɛ, which is independent of the parameters t and n. On the other hand, the size of share in Obana’s scheme can be rewritten as |Vi | = (n · (t + 1) · 2 |S|)/ɛ under the same condition. With respect to the size of share, the proposed scheme is more efficient than previous one when the number of cheaters t is close to ⌊((k− 2)/2)⌋.

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.