Biblio
Nowadays Wireless Mesh Networks (WMNs) has come up with a promising solution for modern wireless communications. But, one of the major problems with WMN is the mobility of the Mesh Clients (MCs). To offer seamless connectivity to the MCs, their mobility management is necessary. During mobility management one of the major concerns is the communication overhead incurred during handoff of the MCs. For addressing this concern, many schemes have been proposed by the researchers. In this paper, a classification of the existing intra domain mobility management schemes has been presented. The schemes have been numerically analyzed. Finally, their performance has been analyzed and compared with respect to handoff cost considering different mobility rates of the MCs.
Multimedia security and copyright protection has been a popular topic for research and application, due to the explosion of data exchange over the internet and the widespread use of digital media. Watermarking is a process of hiding the digital information inside a digital media. Information hiding as digital watermarks in multimedia enables protection mechanism in decrypted contents. This paper presents a comparative study of existing technique used for digital watermarking an image using Genetic Algorithm and Bacterial Foraging Algorithm (BFO) based optimization technique with proposed one which consists of Genetic Algorithm and Honey Bee based optimization technique. The results obtained after experiment conclude that, new method has indeed outperformed then the conventional technique. The implementation is done over the MATLAB.
Security is playing a very important and crucial role in the field of network communication system and Internet. Kerberos Authentication Protocol is designed and developed by Massachusetts Institute of Technology (MIT) and it provides authentication by encrypting information and allow clients to access servers in a secure manner. This paper describes the design and implementation of Kerberos using Data Encryption Standard (DES). Data encryption standard (DES) is a private key cryptography system that provides the security in the communication system. Java Development Tool Kit as the front end and ms access as the back end are used for implementation.
Heterogeneous Chip Multiprocessors have been shown to provide significant performance and energy efficiency gains over homogeneous designs. Recent research has expanded the dimensions of heterogeneity to include diverse Instruction Set Architectures, called Heterogeneous-ISA Chip Multiprocessors. This work leverages such an architecture to realize substantial new security benefits, and in particular, to thwart Return-Oriented Programming. This paper proposes a novel security defense called HIPStR – Heterogeneous-ISA Program State Relocation – that performs dynamic randomization of run-time program state, both within and across ISAs. This technique outperforms the state-of-the-art just-in-time code reuse (JIT-ROP) defense by an average of 15.6%, while simultaneously providing greater security guarantees against classic return-into-libc, ROP, JOP, brute force, JIT-ROP, and several evasive variants.
Honeynet is a collection of honeypots that are set up to attract as many attackers as possible to learn about their patterns, tactics, and behaviors. However, existing honeypots suffer from a variety of fingerprinting techniques, and the current honeynet architecture does not fully utilize features of residing honeypots due to its coarse-grained data control mechanisms. To address these challenges, we propose an SDN-based intelligent honeynet called HoneyMix. HoneyMix leverages the rich programmability of SDN to circumvent attackers' detection mechanisms and enables fine-grained data control for honeynet. To do this, HoneyMix simultaneously establishes multiple connections with a set of honeypots and selects the most desirable connection to inspire attackers to remain connected. In this paper, we present the HoneyMix architecture and a description of its core components.
Even though some seem to think privacy is dead, we are all still wearing clothes, as Bruce Schneier observed at a recent conference on surveillance[1]. Yet big data and big data analytics are leaving some of us feeling a bit more naked than before. This talk will provide some personal observations on privacy today and then outline some research areas where progress is needed to enable society to gain the benefits of analyzing large datasets without giving up more privacy than necessary. Not since the early 1970s, when computing pioneer Willis Ware chaired the committee that produced the initial Fair Information Practice Principles [2] has privacy been so much in the U.S. public eye. Snowden's revelations, as well as a growing awareness that merely living our lives seems to generate an expanding "digital exhaust." Have triggered many workshops and meetings. A national strategy for privacy research is in preparation by a Federal interagency group. The ability to analyze large datasets rapidly and to extract commercially useful insights from them is spawning new industries. Must this industrial growth come at the cost of substantial privacy intrusions?
The necessity to deploy wireless mesh network is determined by the real world application requirements. WMN does not fit some application well due to latency issues and capacity related problem with paths having more than 2 hops. With the promising IEEE 802.11ac based device a better fairness for multi-hop communications are expected to support broadband application; the rate usually varies according to the link quality and network environment. Careful network planning can effectively improves the throughput and delay of the overall network. We provide model for the placement of router nodes as an optimization process to improve performance. Our aim is to propose a WMNs planning model based on multiobjective constraints like coverage, reliability, and cost of deployment. The bit rate guarantee therefore necessary to limit the number of stations connected to the access point; to takes into account delay and fairness of the network the user's behaviors are derived. We use a multiobjective evolutionary algorithm based metaheuristic to evaluate the performance of our proposed placement algorithm.
This paper proposes a new hybrid technique for combined encryption text and image based on hyperchaos system. Since antiquity, man has continued looking for ways to send messages to his correspondents in order to communicate with them safely. It needed, through successive epochs, both physical and intellectual efforts in order to find an effective and appropriate communication technique. On another note, there is a behavior between the rigid regularity and randomness. This behavior is called chaos. In fact, it is a new field of investigation that is opened along with a new understanding of the frequently misunderstood long effects. The chaotic cryptography is thus born by inclusion of chaos in encryption algorithms. This article is in this particular context. Its objective is to create and implement an encryption algorithm based on a hyperchaotic system. This algorithm is composed of four methods: two for encrypting images and two for encrypting texts. The user chose the type of the input of the encryption (image or text) and as well as of the output. This new algorithm is considered a renovation in the science of cryptology, with the hybrid methods. This research opened a new features.
Mobile ad hoc network is one of the popular network technology used for rapid deployment in critical situations. Because the nature of network is ad hoc therefore a number of issues exist. In order to investigate the security in mobile ad hoc network a number of research articles are explored and it is observed that most of the attacks are deployed on the basis of poor routing methodology. For providing the security in the ad hoc networks an opinion based trust model is proposed which is working on the basis of the network properties. In this model two techniques are used one is trust calculation that helps in finding most trustworthy node and other is opinion evaluation by which most secure route to the destination is obtained. By the experimental outcomes the results are compared with the traditional approach of trust based security. According to the obtained results the performance of the network becomes efficient in all the evaluated parameters as compared to the traditional technique. Thus proposed model is more adoptable for secure routing in MANET.
Logistic regression is a powerful machine learning tool to classify data. When dealing with sensitive data such as private or medical information, cares are necessary. In this paper, we propose a secure system for protecting the training data in logistic regression via homomorphic encryption. Perhaps surprisingly, despite the non-polynomial tasks of training in logistic regression, we show that only additively homomorphic encryption is needed to build our system. Our system is secure and scalable with the dataset size.
Information flow analyses traditionally use the Program Dependence Graph (PDG) as a supporting data-structure. This graph relies on Ferrante et al.'s notion of control dependences to represent implicit flows of information. A limitation of this approach is that it may create O(textbarItextbar x textbarEtextbar) implicit flow edges in the PDG, where I are the instructions in a program, and E are the edges in its control flow graph. This paper shows that it is possible to compute information flow analyses using a different notion of implicit dependence, which yields a number of edges linear on the number of definitions plus uses of variables. Our algorithm computes these dependences in a single traversal of the program's dominance tree. This efficiency is possible due to a key property of programs in Static Single Assignment form: the definition of a variable dominates all its uses. Our algorithm correctly implements Hunt and Sands system of security types. Contrary to their original formulation, which required O(IxI) space and time for structured programs, we require only O(I). We have used our ideas to build FlowTracker, a tool that uncovers side-channel vulnerabilities in cryptographic algorithms. FlowTracker handles programs with over one-million assembly instructions in less than 200 seconds, and creates 24% less implicit flow edges than Ferrante et al.'s technique. FlowTracker has detected an issue in a constant-time implementation of Elliptic Curve Cryptography; it has found several time-variant constructions in OpenSSL, one issue in TrueCrypt and it has validated the isochronous behavior of the NaCl library.
Go is a programming language developed at Google, with channel-based concurrent features based on CSP. Go can detect global communication deadlocks at runtime when all threads of execution are blocked, but deadlocks in other paths of execution could be undetected. We present a new static analyser for concurrent Go code to find potential communication errors such as communication mismatch and deadlocks at compile time. Our tool extracts the communication operations as session types, which are then converted into Communicating Finite State Machines (CFSMs). Finally, we apply a recent theoretical result on choreography synthesis to generate a global graph representing the overall communication pattern of a concurrent program. If the synthesis is successful, then the program is free from communication errors. We have implemented the technique in a tool, and applied it to analyse common Go concurrency patterns and an open source application with over 700 lines of code.
Over transactional database systems MultiVersion concurrency control is maintained for secure, fast and efficient access to the shared data file implementation scenario. An effective coordination is supposed to be set up between owners and users also the developers & system operators, to maintain inter-cloud & intra-cloud communication Most of the services & application offered in cloud world are real-time, which entails optimized compatibility service environment between master and slave clusters. In the paper, offered methodology supports replication and triggering methods intended for data consistency and dynamicity. Where intercommunication between different clusters is processed through middleware besides slave intra-communication is handled by verification & identification protection. The proposed approach incorporates resistive flow to handle high impact systems that identifies and verifies multiple processes. Results show that the new scheme reduces the overheads from different master and slave servers as they are co-located in clusters which allow increased horizontal and vertical scalability of resources.
In this paper, we propose a practical and efficient word and phrase proximity searchable encryption protocols for cloud based relational databases. The proposed advanced searchable encryption protocols are provably secure. We formalize the security assurance with cryptographic security definitions and prove the security of our searchable encryption protocols under Shannon's perfect secrecy assumption. We have tested the proposed protocols comprehensively on Amazon's high performance computing server using mysql database and presented the results. The proposed protocols ensure that there is zero overhead of space and communication because cipher text size being equal to plaintext size. For the same reason, the database schema also does not change for existing applications. In this paper, we also present results of comprehensive analysis for Song, Wagner, and Perrig scheme.
In part I of a three-part series on active surveillance using depth-sensing technology, this paper proposes an algorithm to identify outdoor intrusion activities by monitoring skeletal positions from Microsoft Kinect sensor in real-time. This algorithm implements three techniques to identify a premise intrusion. The first technique observes a boundary line along the wall (or fence) of a surveilled premise for skeletal trespassing detection. The second technique observes the duration of a skeletal object within a region of a surveilled premise for loitering detection. The third technique analyzes the differences in skeletal height to identify wall climbing. Experiment results suggest that the proposed algorithm is able to detect trespassing, loitering and wall climbing at a rate of 70%, 85% and 80% respectively.
The production and sale of counterfeit and substandard pharmaceutical products, such as essential medicines, is an important global public health problem. We describe a chemometric passport-based approach to improve the security of the pharmaceutical supply chain. Our method is based on applying nuclear quadrupole resonance (NQR) spectroscopy to authenticate the contents of medicine packets. NQR is a non-invasive, non-destructive, and quantitative radio frequency (RF) spectroscopic technique. It is sensitive to subtle features of the solid-state chemical environment and thus generates unique chemical fingerprints that are intrinsically difficult to replicate. We describe several advanced NQR techniques, including two-dimensional measurements, polarization enhancement, and spin density imaging, that further improve the security of our authentication approach. We also present experimental results that confirm the specificity and sensitivity of NQR and its ability to detect counterfeit medicines.
Given the increasing complexity of modern electronics and the cost of fabrication, entities from around the globe have become more heavily involved in all phases of the electronics supply chain. In this environment, hardware Trojans (i.e., malicious modifications or inclusions made by untrusted third parties) pose major security concerns, especially for those integrated circuits (ICs) and systems used in critical applications and cyber infrastructure. While hardware Trojans have been explored significantly in academia over the last decade, there remains room for improvement. In this article, we examine the research on hardware Trojans from the last decade and attempt to capture the lessons learned. A comprehensive adversarial model taxonomy is introduced and used to examine the current state of the art. Then the past countermeasures and publication trends are categorized based on the adversarial model and topic. Through this analysis, we identify what has been covered and the important problems that are underinvestigated. We also identify the most critical lessons for those new to the field and suggest a roadmap for future hardware Trojan research.
In this work we put forward our novel approach using graph partitioning and Micro-Community detection techniques. We firstly use algebraic connectivity or Fiedler Eigenvector and spectral partitioning for community detection. We then used modularity maximization and micro level clustering for detecting micro-communities with concept of community energy. We run micro-community clustering algorithm recursively with modularity maximization which helps us identify dense, deeper and hidden community structures. We experimented our MicroCommunity Clustering (MCC) algorithm for various types of complex technological and social community networks such as directed weighted, directed unweighted, undirected weighted, undirected unweighted. A novel fact about this algorithm is that it is scalable in nature.
This paper address the problem of shadow detection and removal in traffic vision analysis. Basically, the presence of the shadow in the traffic sequences is imminent, and therefore leads to errors at segmentation stage and often misclassified as an object region or as a moving object. This paper presents a shadow removal method, based on both color and texture features, aiming to contribute to retrieve efficiently the moving objects whose detection are usually under the influence of cast-shadows. Additionally, in order to get a shadow-free foreground segmentation image, a morphology reconstruction algorithm is used to recover the foreground disturbed by shadow removal. Once shadows are detected, an automatic shadow removal model is proposed based on the information retrieved from the histogram shape. Experimental results on a real traffic sequence is presented to test the proposed approach and to validate the algorithm's performance.
Anonymous Identity-Based Broadcast Encryption (AIBBE) allows a sender to broadcast a ciphertext to multi-receivers, and keeps receivers' anonymity. The existing AIBBE schemes fail to achieve efficient decryption or strong security, like the constant decryption complexity, the security under the adaptive attack, or the security in the standard model. Hence, we propose two new AIBBE schemes to overcome the drawbacks of previous schemes in the state-of-art. The biggest contribution in our work is the proposed AIBBE scheme with constant decryption complexity and the provable security under the adaptive attack in the standard model. This scheme should be the first one to obtain advantages in all above mentioned aspects, and has sufficient contribution in theory due to its strong security. We also propose another AIBBE scheme in the Random Oracle (RO) model, which is of sufficient interest in practice due to our experiment.
Embedded devices are becoming more widespread, interconnected, and web-enabled than ever. However, recent studies showed that embedded devices are far from being secure. Moreover, many embedded systems rely on web interfaces for user interaction or administration. Web security is still difficult and therefore the web interfaces of embedded systems represent a considerable attack surface. In this paper, we present the first fully automated framework that applies dynamic firmware analysis techniques to achieve, in a scalable manner, automated vulnerability discovery within embedded firmware images. We apply our framework to study the security of embedded web interfaces running in Commercial Off-The-Shelf (COTS) embedded devices, such as routers, DSL/cable modems, VoIP phones, IP/CCTV cameras. We introduce a methodology and implement a scalable framework for discovery of vulnerabilities in embedded web interfaces regardless of the devices' vendor, type, or architecture. To reach this goal, we perform full system emulation to achieve the execution of firmware images in a software-only environment, i.e., without involving any physical embedded devices. Then, we automatically analyze the web interfaces within the firmware using both static and dynamic analysis tools. We also present some interesting case-studies and discuss the main challenges associated with the dynamic analysis of firmware images and their web interfaces and network services. The observations we make in this paper shed light on an important aspect of embedded devices which was not previously studied at a large scale.
When running large human computation tasks in the real-world, honeypots play an important role for assessing the overall quality of the work produced. The generation of such honeypots can be a significant burden on the task owner as they require specific characteristics in their design and implementation and continuous maintenance when operating data pipelines that include a human computation component. In this extended abstract we outline a novel approach for creating honeypots using automatically generated questions from a reference knowledge base with the ability to control such parameters as topic and difficulty.
In this paper we describe a privacy-preserving method for commissioning an IoT device into a cloud ecosystem. The commissioning consists of the device proving its manufacturing provenance in an anonymous fashion without reliance on a trusted third party, and for the device to be anonymously registered through the use of a blockchain system. We introduce the ChainAnchor architecture that provides device commissioning in a privacy-preserving fashion. The goal of ChainAnchor is (i) to support anonymous device commissioning, (ii) to support device-owners being remunerated for selling their device sensor-data to service providers, and (iii) to incentivize device-owners and service providers to share sensor-data in a privacy-preserving manner.
Cooperative MIMO communication is a promising technology which enables realistic solution for improving communication performance with MIMO technique in wireless networks that are composed of size and cost constrained devices. However, the security problems inherent to cooperative communication also arise. Cryptography can ensure the confidentiality in the communication and routing between authorized participants, but it usually cannot prevent the attacks from compromised nodes which may corrupt communications by sending garbled signals. In this paper, we propose a cross-layered approach to enhance the security in query-based cooperative MIMO sensor networks. The approach combines efficient cryptographic technique implemented in upper layer with a novel information theory based compromised nodes detection algorithm in physical layer. In the detection algorithm, a cluster of K cooperative nodes are used to identify up to K - 1 active compromised nodes. When the compromised nodes are detected, the key revocation is performed to isolate the compromised nodes and reconfigure the cooperative MIMO sensor network. During this process, beamforming is used to avoid the information leaking. The proposed security scheme can be easily modified and applied to cognitive radio networks. Simulation results show that the proposed algorithm for compromised nodes detection is effective and efficient, and the accuracy of received information is significantly improved.