Untrusted Data Research Articles

Ontology based Intrusion Detection System in Wireless Sensor Network for Active Attacks

WSNs are vulnerable to attacks and have deemed special attention for developing mechanism for securing against various threats that could effect the overall infrastructure. WSNs are open to miscellaneous classes of attacks and security breaches are intolerable in WSNs. Threats like untrusted data transmissions, settlement in open and unfavorable environments are still open research issues. Safekeeping is an essential and complex requirement in WSNs. These issues raise the need to develop a security-based mechanism for Wireless Sensor Network to categorize the different attacks based on their relevance. A detailed survey of active attacks is highlighted based on the nature and attributes of those attacks. An Ontology based mechanism is developed and tested for active attack in WSNs

English

SQLIA has been now a major threat to the growing popularity of web application. The main target of this attack is the database. This allows attackers to obtain unauthorised access to database .In this paper we survey different types of SQLIAs and prevention methods. To address this problem we propose a mixed approach for prevention of SQLIA .This paper ensures that the untrusted data are validated against a list of allowable values. Least privilege principle is applied to SQL account used by web application. We avoid query concatenation at almost all costs and use parameterized queries wherever possible.

Practical Forward-Secure Range and Sort Queries with Update-Oblivious Linked Lists

Abstract We revisit the problem of privacy-preserving range search and sort queries on encrypted data in the face of an untrusted data store. Our new protocol RASP has several advantages over existing work. First, RASP strengthens privacy by ensuring forward security: after a query for range [a, b], any new record added to the data store is indistinguishable from random, even if the new record falls within range [a, b]. We are able to accomplish this using only traditional hash and block cipher operations, abstaining from expensive asymmetric cryptography and bilinear pairings. Consequently, RASP is highly practical, even for large database sizes. Additionally, we require only cloud storage and not a computational cloud like related works, which can reduce monetary costs significantly. At the heart of RASP, we develop a new update-oblivious bucket-based data structure. We allow for data to be added to buckets without leaking into which bucket it has been added. As long as a bucket is not explicitly queried, the data store does not learn anything about bucket contents. Furthermore, no information is leaked about data additions following a query. Besides formally proving RASP’s privacy, we also present a practical evaluation of RASP on Amazon Dynamo, demonstrating its efficiency and real world applicability.

A Novel Built-In Self-Authentication Technique to Prevent Inserting Hardware Trojans

With the rapid globalization of the semiconductor industry, hardware Trojans have become a significant threat to government agencies and enterprises that require secure and reliable systems for their critical applications. Because of the diversity of hardware Trojans and the randomness associated with process variations, hardware Trojan detection is a challenging problem. In this paper, we propose a novel technique, called built-in self-authentication (BISA), which can be used to make hardware Trojan insertion by untrusted Graphic Data System (GDSII) developer and untrusted foundry considerably more difficult and easier to detect. The unused spaces in the circuit layout represent the best opportunity to insert Trojans by these entities. BISA works by eliminating this spare space and filling it with functional filler cells, instead of nonfunctional filler cells. A self-testing procedure generates a digital signature that will be different if any BISA cells are changed because of hardware Trojan insertion. We demonstrate that BISA can be applied to any flat or bottom-up hierarchical design with negligible overhead in terms of area, power, and timing.

Keyword search encryption scheme resistant against keyword-guessing attack by the untrusted server

The user data stored in an untrusted server, such as the centralized data center or cloud computing server, may be dangerous of eavesdropping if the data format is a plaintext. However, the general ciphertext is difficult to search and thus limited for practical usage. The keyword search encryption is a helpful mechanism that provides a searchable ciphertext for some predefined keywords. The previous studies failed to consider the attack from the data storage server to guess the keyword. This kind of attack may cause some critical information revealed to the untrusted server. This paper proposes a new keyword search encryption model that can effectively resist the keyword-guessing attack performed by the untrusted data storage (testing) server. The testing (query) secret is divided into multiple shares so that the security can be guaranteed if the servers cannot conspire with each other to retrieve all shares of the secret.

EFFICIENT RANKED AND SECURE FILE RETRIEVAL IN CLOUD COMPUTING

Cloud computing facilitates extremely scalable services that can be consumed over internet. An important aspect of the cloud services is that user data are stored remotely in unknown machines in which users do not posses or manage. Since the data’s are stored remotely, we have to keep in mind that sensitive cloud data have to be encrypted before they are outsourced to the commercial public cloud, which makes efficient data utilization service. Searchable encryption file retrieval technique allows users to securely search over encrypted data through search word. Ranking the files based on relevance scores greatly enhances system usability by making it possible relevance ranking instead of sending unwanted results and further ensures the file retrieval accuracy. In this study, we are developing an automated system for both named and un-named documents based on the clustering algorithms. We implement the ranking and searching algorithm to retrieve top k files. We also provides the mapping and encryption algorithm to protect the information. The resulting design is able to provide efficient ranking which will reduce the search time drastically and reduce the communication overhead. The mapping and encryption algorithms protect document against an outside attackers and prevent an untrusted cloud data provider from learning data.

Assessing the quality and trustworthiness of citizen science data

SUMMARYThe Internet, Web 2.0 and Social Networking technologies are enabling citizens to actively participate in ‘citizen science’ projects by contributing data to scientific programmes via the Web. However, the limited training, knowledge and expertise of contributors can lead to poor quality, misleading or even malicious data being submitted. Subsequently, the scientific community often perceive citizen science data as not worthy of being used in serious scientific research—which in turn, leads to poor retention rates for volunteers. In this paper, we describe a technological framework that combines data quality improvements and trust metrics to enhance the reliability of citizen science data. We describe how online social trust models can provide a simple and effective mechanism for measuring the trustworthiness of community‐generated data. We also describe filtering services that remove unreliable or untrusted data and enable scientists to confidently reuse citizen science data. The resulting software services are evaluated in the context of the CoralWatch project—a citizen science project that uses volunteers to collect comprehensive data on coral reef health. Copyright © 2012 John Wiley & Sons, Ltd.

Protecting personal data from untrusted web-based data services

Our society places a heavy emphasis on security and the privacy of personal data. Personal data at the hands of a malicious entity could spell disastrous consequences for the data's owner. There is a whole slew of attacks on the Internet aimed at procuring and misusing personal information for profit.1, 2 And so, recently, there has been a huge thrust towards developing technologies that protect personal data from being misused.3, 4 Governments across the world are passing laws to protect personal information.5 Outsourcing personal information to web-based data services (WDS) is a common recent trend. These services have become very popular, but they require us to trust the service provider and may be vulnerable to both outsider and insider attacks. Ravi Chandra Jammalamadaka of eBay and Sharad Mehrotra and Nalini Venkatasubramanian of the University of California, Irvine, present the design and initial implementation of DataProtector, security middleware that acts as a transparent middleman between browser and web server and enforces security requirements at the level of HTTP requests.

A privacy-aware framework for participatory sensing

With the abundance and ubiquity of mobile devices, a new class of applications is emerging, called participatory sensing (PS), where people can contribute data (e.g., images, video) collected by their mobile devices to central data servers. However, privacy concerns are becoming a major impediment in the success of many participatory sensing systems. While several privacy preserving techniques exist in the context of conventional location-based services, they are not directly applicable to the PS systems because of the extra information that the PS systems can collect from their participants. In this paper, we formally define the problem of privacy in PS systems and identify its unique challenges assuming an un-trusted central data server model. We propose PiRi, a privacy-aware framework for PS systems, which enables participation of the users without compromising their privacy. Our extensive experiments verify the efficiency of our approach.

From Speculation to Security

Dynamic information flow tracking (also known as taint tracking) is an appealing approach to combat various security attacks. However, the performance of applications can severely degrade without hardware support for tracking taints. This paper observes that information flow tracking can be efficiently emulated using deferred exception tracking in microprocessors supporting speculative execution. Based on this observation, we propose SHIFT, a low-overhead, software-based dynamic information flow tracking system to detect a wide range of attacks. The key idea is to treat tainted state (describing untrusted data) as speculative state (describing deferred exceptions). SHIFT leverages existing architectural support for speculative execution to track tainted state in registers and needs to instrument only load and store instructions to track tainted state in memory using a bitmap, which results in significant performance advantages. Moreover, by decoupling mechanisms for taint tracking from security policies, SHIFT can detect a wide range of exploits, including high-level semantic attacks. We have implemented SHIFT using the Itanium processor, which has support for deferred exceptions, and by modifying GCC to instrument loads and stores. A security assessment shows that SHIFT can detect both low-level memory corruption exploits as well as high-level semantic attacks with no false positives. Performance measurements show that SHIFT incurs about 1% overhead for server applications. The performance slowdown for SPEC-INT2000 is 2.81X and 2.27X for tracking at byte-level and wordlevel respectively. Minor architectural improvements to the Itanium processor (adding three simple instructions) can reduce the performance slowdown down to 2.32X and 1.8X for byte-level and word-level tracking, respectively.

The Caernarvon secure embedded operating system

The Caernarvon operating system was developed to demonstrate that a high assurance system for smart cards was technically feasible and commercially viable. The entire system has been designed to be evaluated under the Common Criteria at EAL7, the highest defined level of assurance. Historically, smart card processors have not supported the hardware protection features necessary to separate the OS from the applications, and one application from another. The Caernarvon OS has taken advantage of the first smart card processors with such features to be the first smart card OS to provide this kind of protection. Even when compared with conventional systems where the hardware protection is routine, the Caernarvon OS is noteworthy, because of the EAL7 assurance. This approach facilitated implementation of a formally specified, mandatory security policy providing multi-level security (MLS) suitable for both government agencies and commercial users. The mandatory security policy requires effective authentication of its users that is independent of applications. For this reason, the Caernarvon OS also contains a privacy-preserving, two-way authentication protocol integrated with the Mandatory Security Policy. The Caernarvon OS includes a strong cryptographic library that has been separately certified under the Common Criteria at EAL5+ for use with other systems. The Caernarvon OS implements a secure method for downloading trusted and untrusted application software and data in the field, with the assumption that all applications are potentially hostile. While the initial platform for the operating system was smart cards, the design could also be used in other embedded devices, such as USB tokens, PDAs, cell phones, etc.

Hiding Tree Structured Data and Queries from Untrusted Data Stores

With the increasing use of Web services, many new challenges concerning data security are becoming critical. Especially in mobile services, where clients are generally thin in terms of computation power and storage space, a remote server can be outsourced for the computation or can act as a data store. Unfortunately, such a data store may not always be trustworthy, and clients with sensitive data and queries may want protection from malicious attacks. This article presents a technique to hide tree-structured data from potentially malicious data stores, while allowing clients to traverse the data to locate an object of interest without leaking information to the data store. The two motivating applications for this approach are hiding (1) tree-like XML data as well as XML queries that are in the form of tree-paths, and (2) tree-structured indexes and queries executed on such data structures. We show that this task is achievable through a one-server protocol that introduces only a limited and adjustable communication overhead. This is especially essential in low-bandwidth (such as wireless) distributed environments. The proposed protocol has desirable communication and concurrency performance, as demonstrated by the experiments we have conducted.