A wireless sensor network (WSN) principally is composed of many sensor nodes and a single in situ base station (BS), which are randomly distributed in a given area of interest. These sensor nodes transmit their measurements to the BS over multihop wireless paths. In addition to collecting and processing the sensed data, the BS performs network management operations. Because of the importance of the BS to the WSN, it is the most attractive target of attacks for an adversary. Basically, the adversary opts to locate the BS and target it with denial-of-service attack to temporarily or indefinitely disrupt the WSN operation. The adversary can intercept the data packet transmissions and use traffic analysis techniques such as evidence theory to uncover the routing topology. To counter such an attack, this paper presents a novel technique for boosting the BS anonymity by grouping nodes into clusters and creating multiple mesh-based routing topologies among the cluster heads (CHs). By applying the closed space-filling curves such as the Moore curve, for forming a mesh, the CHs are offered a number of choices for disseminating aggregated data to the BS through inter-CH paths. Then, the BS forwards the aggregated data as well so that it appears as one of the CHs. The simulation results confirm the effectiveness of the proposed technique in boosting the anonymity of the BS. KEYWORDS anonymity, location privacy, traffic analysis, wireless sensor network 1 | INTRODUCTIONRecent advances in microelectronics have made it possible to integrate sensing and communication capabilities in miniaturized devices that are often referred to in the literature as sensor nodes. Interconnecting a large set of these nodes forms a wireless sensor network (WSN) that can serve unattended in harsh environments. A typical WSN includes an in situ base station (BS) that gathers data from the sensor nodes. WSNs are deemed effective in serving applications such as a military surveillance and target tracking where continuous monitoring of an area of interest is critical and human presence is risky and/or prohibitively expensive. In most of these WSN applications, sensor nodes have limited capabilities, eg, limited communication range, energy (battery) supply, and processing capacity. To overcome communication range limitations and to save energy, we find that sensor nodes transmit their measurements to the BS over multihop wireless paths. 1,2 On the other hand, the BS is not resource constrained and can perform network management and process the collected data. Because of the importance of the BS to the WSN, it can be the focus of an adversary who attempts to inflict the most damage to the network operation. The goal of the adversary will be to locate the BS and target it with denial-of-service attack so that the utility of the WSN is nullified. 3,4 Contemporary security mechanisms, such as packet header encryption and anonymous routing mechanisms, are often applied to conceal the BS's identity. [5][6][7][8][9] However, these security mechanisms do not ...
Wireless Sensor Networks (WSNs) have become an attractive choice for many applications that serve in hostile setup. The operation model of a WSN makes it possible for an adversary to determine the location of the base-station (BS) in the network by intercepting transmissions and employing traffic analysis techniques such as Evidence Theory. By locating the BS, the adversary can then target it with denial-of-service attacks. This paper promotes a novel strategy for countering such an attack by adaptively combining packet payloads. The idea is to trade off packet delivery latency for BS location anonymity. Basically, a node on a data route will delay the forwarding of a packet until one or multiple additional packets arrive and the payloads are then combined in a single packet. Such an approach decreases the number of evidences that an adversary will collect and makes the traffic analysis inclusive in implicating the BS position. Given the data delivery delay that will be imposed, the proposed technique is to be adaptively applied when the BS anonymity needs a boost. The simulation results confirm the effectiveness of the proposed technique.
With the increase in technological development, trafficking in persons has become one of the world’s most pressing issues, with a large number of countries having been affected over the past few years. This research deals with the role of digital technologies implemented through cyberspace in detecting and combating trafficking in person’s crimes. Moreover, the research clarifies the concept of cyber-trafficking, in addition to addressing the different types of cyber-trafficking in person’s crimes. The research found that trafficking in persons is a serious crime because it violates human rights. In addition, the research found that the rate of trafficking has increased due to the global accessibility that the Internet has provided, posing great risks to the public and increasing the rate of cyber-trafficking crimes. Furthermore, the research found that the reasons of trafficking in persons were numerous due to the development of digital technologies at the beginning of the twenty-first century, with the most common motive being for illegal financial profit. Combating trafficking in persons has become an important political priority for many governments around the world, and any future success in eliminating trafficking in persons in its various forms will depend on the extent to which governments and relevant organizations are prepared to develop digital technologies and use them to combat and prevent cyber-trafficking crimes.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.