Threat Model. Following Fig. 1, we assume that an
Threat Model. Xxxxx-Xxx (DY) model is employed, which entails an insecure channel communication and an untrustworthy nature between the parties [56]. Thus, the malicious attacker can easily eavesdrop and tamper the exchanged messages. The worst-case scenario, for instance, might involve seizing a drone, that is hovering, and then compromising its data. The prevalent “Xxxxxxx and Xxxxxxxx’x adversary model (CK- adversary model)” is, reportedly, the de facto standard for modelling the authenticated key exchange protocols. The CK- adversary model entails that the adversary can also hack the secret credentials, secret keys and the session states. Therefore, it has become an essential requirement that “the leakage of some forms of secret credentials, such as session ephemeral secrets or secret key, should have the minimum possible consequence on the secrecy of other secret credentials of the communicating participants” [58].
Threat Model. Quest’s threat security model is based on the following general characteristics: • Confidentiality - The information contained in the Colorado Campaign Finance Database should remain private until the filings are completed by the committees and candidates. Certain document images must be flagged as confidential and not available for public viewing (i.e. Candidate Personal Financial Disclosure Statement). • Integrity - The application and supporting architecture should ensure only authorized users are able to add and update records. • Availability – The system and resulting data must be available. Committees and candidates must maintain the ability to file reports on a tight schedule. The public must have access to the data in a timely manner. Based on these characteristics, the following security threats will be managed as part of this Agreement: Table 4.1 – Quest Security Threat Model Category Risk Mitigation Confidentiality Data could be viewed by public prior to being filed by the candidate or committee. Implement application security measures to ensure application design does not allow public to see data until the associated reports are filed. Integrity Unauthorized users could access and update records for committees and candidates. Implement application security to address data access, web site security, login security, session timeout, page rendering, user account and permission management, user ID and password management and event logging. Also ensure data security through audit logging and data backup procedures. Integrity Unauthorized users may access the servers remotely via network vulnerabilities and manipulate the application data. Maintain remote access to servers on a secure, limited and as needed basis. Category Risk Mitigation Availability Unauthorized persons may access the physical servers. Enforce physical security measures, including: • Only Terremark employees may enter the data center floor • Card access, hand geometry scanners & audible alarms • Multi-zoned, 24/7 monitored access areas w/CCTV surveillance on all external & internal doors • Badge access into gateway • Badge plus biometrics into server suite Availability Power outage, cooling system failure, or fire may result in the system being unavailable. Maintain environmental measures, including: • HVAC closed loop drycooler system (not chilled water) • Total cooling capacity > 1,360 tons • 56/20 ton Liebert Air Handlers & 17 drycooler units on roof • 24/7 environmental monitor...
Threat Model. Within the KSS, the KSMS, the CM and the PL are considered honest-but-curious entities. They will perform the protocol honestly, but they are curious to extract private information about users. Owners are passive adver- saries while consumers and outsiders may be malicious. The car’s OBU is trusted and equipped with a Hardware Security Module (HSM) [34, 45] that supports secure key storage and cryptographic operations such as symmetric and public- key encryption, following the EVITA [17] and PRESERVE [34] specifications. Users’ PDs are untrusted as they can get stolen, lost or broken.
Threat Model. We define the threat model as follows: • The adversary has the ability to intercept all data transmitted over unsecured channels, and he/she can inject new data and replace or replay the previously sent data. • All KDCs are semi-trusted parties, which means that they may misbehave themselves, but do not conspire with any other KDC [30]. • With the help of a Tamper-Proof Device (TPD), we assume that even if the adversary compromises the KDC, he/she cannot extract any secret keys from it. • The adversary has the ability to capture any number of GNs and can access all the secret information stored in the GN’s memory by capturing attack.
Threat Model. In our scenario, we assume mutually-distrusting, rational parties using a payment channel to exchange payments. The threat model includes two potential threats and focuses on the inability of nodes to revoke previous states of the pay- ment channel. Notably, the node that receives the payment faces the threat of the inability to report a misbehaving peer before the contest period expires. On the other hand, the node sending the payment faces the threat of the inability to unlock her money from the channel. The receiver expects a non-repudiation property of the system. After several payments, none of the parties will be Parking Sensor Smart Car Ethereum Register Template Smart Contract Local Copy Sensor Data Public Address 0x00 Off-Chain Execution New Payment Channel Offline Payment(s) Close Channel Sign Final State Side-Chain On-Chain Commit(s) Side-Chain(s) Side-Chain(s) Icons by flaticon (CC 3.0 BY) Challenge Period
Threat Model. This letter adopts the Xxxxxxx-Xxxxxxxx (CK) threat model [1]. In this treat model, attackers are Turing machines with probabilistic polynomial time, who are able to completely control the communication channel of participants and can delay, eavesdrop, modify, replay and insert messages arbitrarily. Furthermore, for adversaries in non-authenticated links, they can also initiate a series of queries to obtain the secret information of participants and related sessions. Specifically, an adversary E is permitted to use following queries to communicate with a protocol entity P (or an oracle), where the protocol entity can be either SMi or UCj . If an attacker cannot distinguish the session key negotiated by protocol participants with an independent random number under the allowable attack capability, we say that the key agreement protocol satisfies security. • Execute(SMi, UCj ): This query simulates E’s passive attacks. E is able to obtain all the messages transmitted between SMi and UCj by this query. • Hk(m): This query returns a random number Huk to adversary E. • Send(P, m): This query simulates E’s active attacks. After E sends a message m to P , P returns a corresponding response. • SSReveal(P ): This query lets E get the session-specific state information held by P . However, it does not output the long-term private key held by P by this query. • SKReveal(P ): By this query, E is permitted to acquire the session key held by P . • Corrupt(P ): By this query, E is permitted to acquire the long-term private key held by P . • Expire(P ): By this query, E is permitted to delete a completed session’s session key held by P . • Test(P ): This query measures the session key’s semantic security. In this query, a coin d is flipped by P , where d = 0, 1. The real session key is returned by P if d = 1. Otherwise, P randomly selects a number and sends it to E. Some related definitions are as follows. Q
Threat Model. We cryptanalyze protocol security using the popular Dolev-Yao(DY) model [21]. By using this threat model, malicious attackers can capture, modify, add, or delete messages sent over insecure channels. And we also consider the following assumptions: • A malicious adversary can steal or obtain a legitimate user’s device, and perform side-channel attacks [22] to obtain key information stored in the device. • A malicious adversary is able to masquerade as a legitimate user and trick authority entities for accessing resources. • An adversary may obtain an authority entity’s secret key. Subsequently, the adversary can compute a previous session key to trick user or authority entities. We also follow the claims of [1–3]. Therefore, we assume that attackers can perform side channel attack or power analysis attack over TPDs or OBUs. Subsequently, attackers can obtain values stored in TPDs. Adversaries can perform a variety of attacks including impersonation, spoofing, identity guessing attacks using values obtained from compromised TPDs.
Threat Model. Fig. 2: Network framework
Threat Model. A threat model is an imperative module of the designing of an AKA protocol. The threat model is a process for enhancing security by classifying vulnerabilities and objectives and then defining preventive measures of threats to the system. In this framework, a threat is a potential malicious attack from an adversary that can cause damage to the assets. We base the threat model on the following assumptions; - Any IoT device may be corrupted and turned into a device controlled by the adversary. We refer to this as a malicious device. We assume that all cryptographic keys of the malicious device are known to the adversary - An adversary can extract the information from MC or any device by examining power consumption and leaked information - An adversary is able to eavesdrop on all the communications between the entities involved in the communication chancel over a public channel - An adversary has the potential to modify a message, delete, redirect and resend the eavesdropped transmitted messages - An adversary can be a legal user or an outsider in any system - An adversary can guess low entropy secret and identity individually easily but guessing two secret parameters is computationally infeasible in polynomial time - It is assumed that the protocol used in the AKA system is known to the attacker - Kerckhoffs’s principle: A cryptosystem should be secure even if everything about the system, except the session key, is public knowledge [14].
