Detection and Filtering of Collaborative Malicious Users in Reputation System using Quality Repository Approach

Online reputation system is gaining popularity as it helps a user to be sure about the quality of a product/service he wants to buy. Nonetheless online reputation system is not immune from attack. Dealing with malicious ratings in reputation systems has been recognized as an important but difficult task. This problem is challenging when the number of true user's ratings is relatively small and unfair ratings plays majority in rated values. In this paper, we have proposed a new method to find malicious users in online reputation systems using Quality Repository Approach (QRA). We mainly concentrated on anomaly detection in both rating values and the malicious users. QRA is very efficient to detect malicious user ratings and aggregate true ratings. The proposed reputation system has been evaluated through simulations and it is concluded that the QRA based system significantly reduces the impact of unfair ratings and improve trust on reputation score with lower false positive as compared to other method used for the purpose.Comment: 14 pages, 5 figures, 5 tables, submitted to ICACCI 2013, Mysore, indi

Multi level trust calculation with improved ant colony optimization for improving quality of service in wireless sensor network

Wireless sensor network (WSN) is the most integral parts of current technology which are used for the real time applications. The major drawbacks in currect technologies are threads due to the creation of false trust values and data congestion. Maximum of the concept of WSNs primarily needs security and optimization. So, we are in the desire to develop a new model which is highly secured and localized. In this paper, we introduced a novel approach namely multi level trust calculation with improved ant colony optimization (MLT-IACO). This approach mainly sub-divided into two sections they are multi level trust calculation which is the combination three levels of trust such as direct trust, indirect trust and random repeat trust. Secondly, improved ant colony optimization technique is used to find the optimal path in the network. By transmitting the data in the optimal path, the congestion and delay of the network is reduced which leads to increase the efficiency. The outcome values are comparatively analyzed based the parameters such as packet delivery ratio, network throughput and average latency. While compared with the earlier research our MLT-IACO approach produce high packet delivery ratio and throughput as well as lower latency and routing overhead

Another Ingredient Contributing to Recent Audit Failures: A Study Providing Insights on Management Integrity

Integrity is evidenced through behavior. It is evidenced by actions an individual\u27s consistent observation of a code of conduct based upon a coherent set of moral (ethical) or artistic values. It suggests such a high level of trustworthiness that it is difficult to conceive of a person being false to a trust. In an audit, beginning with evaluating of the reliability of a client\u27s accounting control systems, the auditor relies heavily on the perceived integrity of management. Thus management integrity has the potential to significantly influence the nature and scope of the independent audit. Decision-making is influenced by personal beliefs and attitudes, which in turn are controlled by the more basic, more enduring structure of the personal values. The influence of personal values extends to management decision-making. This paper is based on a research instrument developed by England to measure the structure of the personal value systems (PVS) of corporate managers. Results indicate which of 66 pre-tested personal values influence corporate decision-making, the twenty-nine Operative Values and which values do not. Trust and Honor, the personal values of interest, are not among the behavior influencing Operative Values. They are classified among the few Primarily Ethical Values. Substantial differences in the role of Trust and Honor in relation to two PVS dimensions, Importance and Success, may significantly influence the integrity of management behavior. Understanding this may assist in understanding and addressing changing audits

Intrusion Detection System In IoT

Intrusion detection detects misbehaving nodes in a network. In Internet of Things(IoT), IPv6 Routing for Low-Power and Lossy Networks (RPL) is the standard routing protocol. In IoT, devices commonly have low energy, storage and memory, which is why the implemented intrusion algorithm in this thesis will try to minimize the usage of these resources. IDS for RPL-networks have been implemented before, but the use of resources or the number of packets sent was too high to be successful when finding malicious nodes. In this thesis, Trust-based Intrusion Detection System (TIDS), a trust based intrusion detection system was implemented. Each node in the network should observe and evaluate its neighbors based on whether or not they were acting according to the RPL protocol. These observation were sent to a centralized node where these observations were analyzed. The trust values used are based on Subjective Logic; values for belief, disbelief and uncertainty are used to analyze the observations received from the normal nodes. The number of detected nodes, false positives, false negatives, energy usage, memory and number of nodes were measured. An attack's detection time is also measured. Seven different experiments were conducted based on this IDS. They were chosen to investigate the different number of nodes and attackers in the network, when the observations should be sent to the border router and whether the border router is always in listening mode. This showed that the implemented IDS captures between 50-100\% of the attackers based on what type of experiment was executed and it also introduces between 2 and 15 false positives. Concerning the resource usage, the IDS uses between 5000-6400 bytes of storage and 700-1000 bytes of memory. The energy consumption in the border router increases with 488 mW when the IDS is implemented, while the normal nodes does not see an increase in the energy consumption. The results of the thesis are promising, but needs more work to be extended to the RPL protocol. Regarding energy consumption, the border router with IDS is using more energy than without. The normal nodes however, do not have an increased energy consumption because of the IDS. The proposed IDS detects every attacker, but does also introduce false positives. The number of false positives can be reduced by improving the way sinkhole attack is captured

A Novel Trust Evaluation Process for Secure Localization using a Decentralized Blockchain in Wireless Sensor Networks

In this research paper, blockchain-based trust management model is proposed to enhance trust relationship among beacon nodes and to eradicate malicious nodes in Wireless Sensor Networks (WSNs). This composite trust evaluation involves behavioral-based trust as well as data-based trust. Various metrics such as closeness, honesty, intimacy and frequency of interaction are taken into account to compute behavioral-based trust of beacon nodes. Further, the composite (behavior and data) trust value of each beacon nodes is broadcast to Base Stations (BS) to generate a blockchain of trust values. Subsequently, the management model discards the beacon node with least trust value and that ensures reliability and consistency of localization in WSNs. The simulated results of the proposed algorithm are compared with the existing ones in terms of detection accuracy, False Positive Rate (FPR) and False Negative Rate (FNR) and Average Energy Consumption (AEC)

The news values of fake news

Fake news poses a significant threat to society by undermining public trust and consensus on critical issues. Although there is a considerable amount of research on the linguistic features of fake news texts, a comprehensive understanding of how language is used to persuade and promote specific ideologies within them is still lacking. This study addresses this gap by analyzing fake news discourse through the lens of news values. We apply the Discursive News Values Analysis (DNVA) framework and key semantic domain analysis to a corpus of fake news stories on vaccination, climate change, and COVID-19. We identify a set of news values that differentiate fake from mainstream news discourse. Our findings reveal that fake news emphasizes negativity, unexpectedness, consonance, and facticity, while also relying on the previously undocumented news values of subversiveness, causality, religiosity, and historicity. These values form a powerful discursive toolkit exploited by fake news writers to craft compelling false narratives

The news values of fake news

Fake news poses a significant threat to society by undermining public trust and consensus on critical issues. Although there is a considerable amount of research on the linguistic features of fake news texts, a comprehensive understanding of how language is used to persuade and promote specific ideologies within them is still lacking. This study addresses this gap by analyzing fake news discourse through the lens of news values. We apply the Discursive News Values Analysis (DNVA) framework and key semantic domain analysis to a corpus of fake news stories on vaccination, climate change, and COVID-19. We identify a set of news values that differentiate fake from mainstream news discourse. Our findings reveal that fake news emphasizes negativity, unexpectedness, consonance, and facticity, while also relying on the previously undocumented news values of subversiveness, causality, religiosity, and historicity. These values form a powerful discursive toolkit exploited by fake news writers to craft compelling false narratives

Dealing with “Humanewashing” Claims: Vital Farms’ Crucial Next Step

Vital Farms prides itself in their ethical and environmentally-friendly production of pasture-raised eggs, butter, and ghee. A popular tagline for the company is “keeping it bullsh*t-free.” This is core to their company mission and values. However, they are currently facing a PETA class action lawsuit for potential humanewashing and greenwashing, essentially false advertising. So, what happens when the Certified B-Corporation is under attack for the very thing that sets it apart from its competition? Is it possible to rebuild trust with the public and regain ethical standing after bad PR? What are humanewashing and greenwashing, and is Vital Farms guilty