Performance Analysis. (a) Portfolio Yield (Finance Charge Collections during the Due Period divided by Principal Receivables in the Trust as of the first day of the Due Period) ___________%
Performance Analysis. Customer may not publish any benchmarking results or other performance analysis of the SIEMonster Technology; Provided, however, that if there is a conflict between the terms of an applicable Open Source Software License and these license terms, restrictions, and conditions, the Open Source Software License controls to the extent of the conflict.
Performance Analysis. We analyze the proposed solution in terms of the correctness, the security and the overall comparison with related solutions. For the security verification, we refer to [8,18–22] to evaluate session key security, mutual authentication, perfect forward security, and data integrity. Moreover, we also demonstrate that the proposed solution is safe when suffering replay attacks, impersonation attacks, privileged insider attacks, and stolen-verifier attacks.
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Performance Analysis. In this section we analyze the characteristics of the key generated by EKA in terms of our design goals of random- ness, time-variance and distinctiveness. The analysis utilizes actual EKG data from 31 subjects obtained from the MIT PhysioBank database (xxxx://xxx.xxxxxxxxx.xxx/physiobank/) for our validation. Each data value has a time-stamp associated with it, as the data was sampled at 125Hz, there is one EKG value every 8 msec. The EKA implementation and analysis was done using Matlab. In this section section, the notations KeyA and KeyB are used to denote keys generated by arbitrary sensors s1 and s2 (located in the same BSN) which are in the process of exchanging keys, respectively.
Performance Analysis. We use the FlexRay network found in BMW 7 series vehi- cles [29] as an industrial use case to analyze the performance of the proposed FlexRay key agreement mechanism and to illustrate the impact of its introduction on the communication cycle. The communication parameters of the FlexRay network designed for BMW 7 series vehicles are presented in Table IV. For the purpose of our analysis we consider that a portion of TABLE V EXECUTION TIME OF ELLIPTIC CURVE OPERATIONS ON THE TRICORE PLATFORM. Algorithm ECDH ECDSA ECDH ECDSA Curve XXXX000X0 SECP256R1 Key size 192 256 Operation Generate Extract Sign Verify Generate Extract Sign Verify Duration 84 ms 82 ms 84 ms 164 ms 136 ms 134 ms 142 ms 284 ms TABLE VI DURATION OF PHYSICAL LAYER AND ECDH KEY EXCHANGE ON THE TRICORE PLATFORM. ECDH Our approach XXXX000X0 SECP256R1 128 bit key 128 bit key 192 bit key 256 bit key MAPO = 31 SWAPO = 63 414.24 ms 696.25 ms 5.107 ms 10.091 ms 10.123 ms MAPO = 31 SWAPO = 31 414.24 ms 696.25 ms 5.047 ms 5.079 ms 10.047 ms MAPO = 20 SWAPO = 20 414.21 ms 696.22 ms 0.095 ms 5.058 ms 5.090 ms MAPO = 10 SWAPO = 10 414.18 ms 696.19 ms 0.081 ms 5.039 ms 5.071 ms MAPO = 5 SWAPO = 5 414.16 ms 696.18 ms 0.073 ms 5.030 ms 5.062 ms MAPO - gdMinislotActionPointOffset SWAPO - gdSymbolWindowActionPointOffset the communication cycle allocated to minislots in the dynamic segment is reallocated to provide space for a maximum sized symbol window. According to the parameters listed in Table III, for a 10 Mbit/s network, this would require reallocating a time space corresponding to approximately 33 minislots. This roughly corresponds to reducing the transmission capacity of the dynamic segment by three 20 byte frames or two frames with a payload of 56 bytes. The same assumption of the max- imum APO (i.e. offset between the start of a transmission slot and the actual transmission time discussed in section IV-E) was considered for the symbol window and the dynamic segment to provide an upper bound on protocol-related transmission overhead and a lower bound on transmission performance. A smaller APO reduces transmission overhead and enables higher transmission throughput in all communication cycle segments including the symbol window. We now compare the performance of our approach to a classical key-exchange based on the widely used Xxxxxx- Xxxxxxx protocol [30] implemented on a FlexRay network. We opt for an implementation based on elliptic curves to minimize the communication overhead. Table V shows the ti...
Performance Analysis. In the following, we show the performance of our proposed scheme. The performance evaluation of the proposed scheme mainly concerns the time complex- ity. For convenience, we suppose some notations are used to analyze the computational complexity as fol- lows: HUB VSAT (Xv , Yv Whv = (Xh)Rv = (Xv)Rh = gRh·Rv mod N ) Xh, Yh Xv = gRv mod N Yv = h(Xv, h(Sv ⊕ t)) mod N Xh = gRh mod N Sv = IDv−d mod N Yh = h(Xh, h(Sv ⊕ t)) mod N
Performance Analysis. This section provides performance analysis of the proposed protocol in terms of the computation complexity and the communication complexity focused on the login phase and the authenticated key agreement phase only. Performance evaluation is provided by comparing the proposed protocol with Xxxxxxx et al.’s [11] protocol. The computational costs are measured by checking the execution time. They are generally conducted by focusing on operations performed by each party within the protocol. Therefore, for analysis of the computational costs, we concentrated on the operations that are conducted by the parties in the network: namely a patient, a server and doctor/nurse. In order to facilitate the analysis of the computational costs, we define the following three notations. Th: time to execute a one-way hash operation Ts: time to execute a symmetric key encryption or decryption Te: for the time to execute an ECC-160 encryption or decryption. We performed an experiment using Crypto++ Library on a system using the 64-bits Windows 7, 3.2 GHz processor, 4 GB memory, Visual C++ 2013 Software, SHA-1 hash function, AES symmetric encryption/decryption and ECC-160 operation [2]. According to the experiment, Th is nearly 0.0002 seconds on average, Ts is nearly 0.0087 seconds and Te is nearly 0.6 seconds, respectively. Table 3 shows a comparison of the computational cost between the related protocols. Xxxxxxx et al.'s [11] protocol takes about 3.725 sec and the proposed protocol takes about 3.672 sec. As a result, the proposed protocol has lower computational overhead than Xxxxxxx et al.’s [11] protocol. Table 3. Computation cost comparisons. EntityProtocol Patient TS Doctor/Nurse Total Xxxxxxx et al. [11] 5Th+3Ts+2Te 6Th+7Ts+2Te 5Th+4Ts+2Te 16Th+14Ts+6Te The proposed 4Th+2Ts+3Te 4Th+4Ts+1Te 4Th+2Ts+2Te 12Th+8Ts+6Te Th: a one-way hash operation time, Ts: a symmetric key operation time, Te: an ECC operation time. The communication cost represents the number of communications, and the size of messages to be transmitted during the protocol run. The proposed protocol requires less number of communications and of bits compared to Xxxxxxx et al.’s [11] protocol. The communication costs are presented in Table 4. The number of communication bits is based on various length of binary sequences such as: hash function-160 bits, identity-160 bits, symmetric encryption-128 bits and ECC element-160 bits. The number of communication bits required in the proposed protocol is given as: ...
Performance Analysis. Thus, we have λ = 1 and r = k. In this case, k v. √
Performance Analysis. + + ≈ + + + + In this section, we analyze the performance of our proposed Fig. 7. Comparison of computation cost. Fig. 8. Comparison of communication cost. We mainly focus on the authentication phase because the registration is executed for only once and the corresponding cost has little influence on the whole system. First, we consider the computation cost on server side. In [6], the computation cost on server side requires six scalar multiplication opera- ≈ + ≈ + + ≈ scheme from three aspects which are computation cost, communication cost and on-chain cost. And we compare it with three related schemes [6], [12], and [24]. In Table III, we demonstrate the comparison of computation overhead to analyze the cost of these schemes on both SD and server. Additionally, the comparison of communication overhead is shown in Table IV. They are the theoretical analysis of the proposed scheme and the other three schemes, and they can point out the reasons for the differences among these schemes. Xxxx et al. [6] built a consortium blockchain using Hyperledger Composer version V0.20.7, running on an x86_64 GNU/Linux system with 1 core and 2 GB RAM for executing smart contract operations. And we refer their experimental results, and the results are illustrated in Table V. We use the cryptographic library called MIRACL Core to test the execution time of cryptography operations under the Ubuntu ≈
