Blockchain technology has recently gained high popularity in data security, primarily to mitigate against data breach and manipulation. Since its inception in 2008, it has been applied in different areas mainly to maintain data integrity and consistency. Blockchain has been tailored to secure data due to its data immutability and distributive technology. Despite the high success rate in data security, the inability to identify compromised insider nodes is one of the significant problems encountered in blockchain architectures. A Blockchain network is made up of nodes that initiate, verify and validate transactions. If compromised, these nodes can manipulate submitted transactions, inject fake transactions, or retrieve unauthorized information that might eventually compromise the stored data's integrity and consistency. This paper proposes a novel method of detecting these compromised blockchain nodes using a server-side authentication process and thwart their activities before getting updated in the blockchain ledger. In evaluating the proposed system, we perform four common insider attacks, which fall under the following three categories: (1)Those attacks targeting the Blockchain to bring it down. (2) the attacks that attempt to inject fake data into the database. (3) The attacks that attempt to hijack or retrieve unauthorized data. We described how we implement themore »
Secure Data Aggregation in Wireless Sensor Networks: Enumeration Attack and Countermeasure
Data aggregation is a key primitive in wireless sensor networks and refers to the process in which the sensed data are processed and aggregated en-route by intermediate sensor nodes. Since sensor nodes are commonly resource constrained, they may be compromised by attackers and instructed to launch various attacks. Despite the rich literature on secure data aggregation, most of the prior work focuses on detecting intermediate nodes from modifying partial aggregation results with two security challenges remaining. First, a compromised sensor node can report arbitrary reading of its own, which is fundamentally difficult to detect but widely considered to have limited impact on the final aggregation result. Second, a compromised sensor node can repeatedly attack the aggregation process to prevent the base station from receiving correct aggregation results, leading to a special form of Denial-of-Service attack. VMAT [1] (published in ICDCS 2011) is a representative secure data aggregation scheme with the capability of pinpointing and revoking compromised sensor nodes, which relies on a secure MIN aggregation scheme and converts other additive aggregation functions such as SUM and COUNT to MIN aggregations. In this paper, we introduce a novel enumeration attack against VMAT to highlight the security vulnerability of a sensor node more »
- Publication Date:
- NSF-PAR ID:
- 10110841
- Journal Name:
- ICC 2019 - 2019 IEEE International Conference on Communications (ICC)
- Page Range or eLocation-ID:
- 1 to 7
- Sponsoring Org:
- National Science Foundation
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Accepted Manuscript1.0
- Publisher's Version of Record
- https://doi.org/10.1109/ICC.2019.8761889
